From fe007c6f842547321ce1edb5ca9793687b44d580 Mon Sep 17 00:00:00 2001 From: vigo999 Date: Thu, 1 Jun 2023 01:07:57 +0800 Subject: [PATCH 1/4] add readme --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 40a2ef314..43ce52b5e 100644 --- a/README.md +++ b/README.md @@ -19,7 +19,7 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, - Officially maintained and supported ## Table of Contents - +aa ### Official | Domain | Sub Domain | Network | Ascend | GPU | CPU | -- Gitee From eb07069a22134f51253034779064f65634f4ae96 Mon Sep 17 00:00:00 2001 From: vigo999 Date: Fri, 2 Jun 2023 12:42:55 +0800 Subject: [PATCH 2/4] modify official readme --- README.md | 1120 +++++++++++++++++++++++++------------------- README_CN.md | 525 ++++----------------- research/README.md | 313 +++++++++++++ 3 files changed, 1038 insertions(+), 920 deletions(-) create mode 100644 research/README.md diff --git a/README.md b/README.md index 43ce52b5e..fd6bdabaf 100644 --- a/README.md +++ b/README.md @@ -1,510 +1,652 @@ # ![MindSpore Logo](https://gitee.com/mindspore/mindspore/raw/master/docs/MindSpore-logo.png) -## Welcome to the Model Zoo for MindSpore - -The MindSpore models repository provides different task domains, classic SOTA model implementations and end-to-end solutions. The purpose is to make it easier for MindSpore users to use MindSpore for research and product development. - -In order to facilitate developers to enjoy the benefits of MindSpore framework, we will continue to add typical networks and some of the related pre-trained models. If you have needs for the model zoo, you can file an issue on [gitee](https://gitee.com/mindspore/mindspore/issues) or [MindSpore](https://bbs.huaweicloud.com/forum/forum-1076-1.html), We will consider it in time. - -| Directory | Description | -|-------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| -| [official](official) | • Official maintenance, iteratively updated with the MindSpore version, ensure that no problem in accuracy and performance for released version
• Recommended writing style, use the latest MindSpore interface and recommended features, ensure faster performance while maintaining code readability
• Detailed network information and documentation, including but not limited to model description, dataset usage, specification support, accuracy and performance data, network checkpoint files, MindIR files, etc | -| [research](research) | • Passed the acceptance test in the older MindSpore version, indicate supported MindSpore versions in the README
• Maintained and upgraded on demand, it will not be updated iteratively with the MindSpore version, but only adapt to the corresponding interface changes, Maintenance support is provided by MindSpore developers
• Relatively detailed network information and documentation, including but not limited to model description, dataset usage, specification support, accuracy and performance data, network checkpoint files, MindIR files, etc | -| [community](community) | • Contributed by ecological developer, maintained and upgraded on demand, indicate supported MindSpore versions in the README
• Model file is not necessarily provided | - -- SOTA models using the latest MindSpore APIs - -- The best benefits from MindSpore - -- Officially maintained and supported - -## Table of Contents -aa -### Official - -| Domain | Sub Domain | Network | Ascend | GPU | CPU | +## 欢迎来到MindSpore ModelZoo + +MindSpore models仓中提供了不同任务领域，经典的SOTA模型实现和端到端解决方案。目的是方便MindSpore用户更加方便的利用MindSpore进行研究和产品开发。 + +为了让开发者更好地体验MindSpore框架优势，我们将陆续增加更多的典型网络和相关预训练模型。如果您对ModelZoo有任何需求，请通过[Gitee](https://gitee.com/mindspore/mindspore/issues)或[MindSpore](https://bbs.huaweicloud.com/forum/forum-1076-1.html)与我们联系，我们将及时处理。 + +| 目录 | 描述 | +|------------------------| ------------------------------------------------------------ | +| [official](official) | • 官方维护，随MindSpore版本迭代更新，保证版本出口网络的精度效果
• 推荐写法，使用最新的MindSpore接口和推荐使用的特性，在保证代码可读性的基础上，有更快的性能表现
• 有详细的网络信息和说明文档，包含但不限于模型说明，数据集使用，规格支持，精度性能数据，网络checkpoint文件，MindIR文件等 | +| [research](research) | • 历史支持，测试验收通过的模型，在README里标明支持的MindSpore版本
• 按需维护，内容不会随版本迭代更新，只会适配对应的接口变更，由MindSpore开发人员进行维护支持，按需进行维护升级
• 提供较为详细的网络信息和说明文档，包含但不限于模型说明，数据集使用，规格支持，精度数据，网络checkpoint文件，MindIR文件等 | +| [community](community) | • 生态开发者贡献模型 | + +- 使用最新MindSpore API的SOTA模型 + +- MindSpore优势 + +- 官方维护和支持 + +## 标准网络 +## Computer Vision +### Image Classification + +| model | acc@1 | bs | cards | ms/step | amp | mindcv_config | acc@1 | bs | cards | ms/step | amp | vannila mindspore +:-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | +| vgg11| 71.86 | 32 | 8 | 61.63 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | | | | | | | +| vgg13| 72.87 | 32 | 8 | 66.47 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | | | | | | | +| vgg16| 74.61 | 32 | 8 | 73.68 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | uploading | uploading | uploading | uploading | uploading | [config](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/vgg16) | +| vgg19| 75.21 | 32 | 8 | 81.13 | O2 | [cconfig](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | uploading | uploading | uploading | uploading | uploading | [config](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/vgg19) | +| resnet18| 70.21 | 32 | 8 | 23.98 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | +| resnet34| 74.15 | 32 | 8 | 23.98 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | +| resnet50| 76.69 | 32 | 8 | 31.97 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | +| resnet101| 78.24 | 32 | 8 | 50.76 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | +| resnet152| 78.72 | 32 | 8 | 70.94 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | +| resnetv2_50| 76.90 | 32 | 8 | 35.72 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnetv2) | +| resnetv2_101| 78.48 | 32 | 8 | 56.02 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnetv2) | +| dpn92 | 79.46 | 32 | 8 | 79.89 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | +| dpn98 | 79.94 | 32 | 8 | 106.60 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | +| dpn107 | 80.05 | 32 | 8 | 107.60 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | +| dpn131 | 80.07 | 32 | 8 | 143.57 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | +| densenet121 | 75.64 | 32 | 8 | 48.07 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | +| densenet161 | 79.09 | 32 | 8 | 115.11 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | +| densenet169 | 77.26 | 32 | 8 | 73.14 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | +| densenet201 | 78.14 | 32 | 8 | 96.12 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | +| seresnet18 | 71.81 | 64 | 8 | 50.39 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | +| seresnet34 | 75.36 | 64 | 8 | 50.54 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | +| seresnet50 | 78.31 | 64 | 8 | 98.37 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | +| seresnext26 | 77.18 | 64 | 8 | 73.72 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | +| seresnext50 | 78.71 | 64 | 8 | 113.82 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | +| skresnet18 | 73.09 | 64 | 8 | 65.95 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | +| skresnet34 | 76.71 | 32 | 8 | 43.96 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | +| skresnet50_32x4d | 79.08 | 64 | 8 | 65.95 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | +| resnext50_32x4d | 78.53 | 32 | 8 | 50.25 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | +| resnext101_32x4d | 79.83 | 32 | 8 | 68.85 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | +| resnext101_64x4d | 80.30 | 32 | 8 | 112.48 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | +| resnext152_64x4d | 80.52 | 32 | 8 | 157.06 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | +| rexnet_x09 | 77.07 | 64 | 8 | 145.08 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | +| rexnet_x10 | 77.38 | 64 | 8 | 156.67 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | +| rexnet_x13 | 79.06 | 64 | 8 | 203.04 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | +| rexnet_x15 | 79.94 | 64 | 8 | 231.41 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | +| rexnet_x20 | 80.64 | 64 | 8 | 308.15 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | +| resnest50 | 80.81 | 128 | 8 | 376.18 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnest) | +| resnest101 | 82.50 | 128 | 8 | 719.84 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnest) | +| res2net50 | 79.35 | 32 | 8 | 49.16 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | +| res2net101 | 79.56 | 32 | 8 | 49.96 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | +| res2net50_v1b | 80.32 | 32 | 8 | 93.33 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | +| res2net101_v1b | 95.41 | 32 | 8 | 86.93 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | +| googlenet | 72.68 | 32 | 8 | 23.26 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/googlenet) | +| inceptionv3 | 79.11 | 32 | 8 | 49.96 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inceptionv3) | +| inceptionv4 | 80.88 | 32 | 8 | 93.33 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inceptionv4) | +| mobilenet_v1_025 | 53.87 | 64 | 8 | 75.93 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | +| mobilenet_v1_050 | 65.94 | 64 | 8 | 51.96 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | +| mobilenet_v1_075 | 70.44 | 64 | 8 | 57.55 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | +| mobilenet_v1_100 | 72.95 | 64 | 8 | 44.04 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | +| mobilenet_v2_075 | 69.98 | 256 | 8 | 169.81 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | +| mobilenet_v2_100 | 72.27 | 256 | 8 | 195.06 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | +| mobilenet_v2_140 | 75.56 | 256 | 8 | 230.06 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | +| mobilenet_v3_small | 68.10 | 75 | 8 | 67.19 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv3) | +| mobilenet_v3_large | 75.23 | 75 | 8 | 85.61 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv3) | +| shufflenet_v1_g3_x0_5 | 57.05 | 64 | 8 | 142.69 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv1) | +| shufflenet_v1_g3_x1_5 | 67.77 | 64 | 8 | 267.79 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv1) | +| shufflenet_v2_x0_5 | 57.05 | 64 | 8 | 142.69 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv2) | +| shufflenet_v2_x1_0 | 67.77 | 64 | 8 | 267.79 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv2) | +| shufflenet_v2_x1_5 | 57.05 | 64 | 8 | 142.69 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv2) | +| shufflenet_v2_x2_0 | 67.77 | 64 | 8 | 267.79 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv2) | +| xception | 79.01 | 32 | 8 | 98.03 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/xception) | +| ghostnet_50 | 66.03 | 128 | 8 | 220.88 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | +| ghostnet_100 | 73.78 | 128 | 8 | 222.67 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | +| ghostnet_130 | 75.50 | 128 | 8 | 223.11 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | +| nasnet_a_4x1056 | 73.65 | 256 | 8 | 1562.35 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/nasnet) | +| mnasnet_0.5 | 68.07 | 512 | 8 | 367.05 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | +| mnasnet_0.75 | 71.81 | 256 | 8 | 151.02 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | +| mnasnet_1.0 | 74.28 | 256 | 8 | 153.52 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | +| mnasnet_1.4 | 76.01 | 256 | 8 | 194.90 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | +| efficientnet_b0 | 76.89 | 128 | 8 | 276.77 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/efficientnet) | +| efficientnet_b1 | 78.95 | 128 | 8 | 435.90 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/efficientnet) | +| regnet_x_200mf| 68.74 | 64 | 8 | 47.56 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | +| regnet_x_400mf| 73.16 | 64 | 8 | 47.56 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | +| regnet_x_600mf| 73.34 | 64 | 8 | 48.36 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | +| regnet_x_800mf| 76.04 | 64 | 8 | 47.56 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | +| regnet_y_200mf| 70.30 | 64 | 8 | 58.35 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | +| regnet_y_400mf| 73.91 | 64 | 8 | 77.94 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | +| regnet_y_600mf| 75.69 | 64 | 8 | 79.94 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | +| regnet_y_800mf| 76.52 | 64 | 8 | 81.93 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | +| mixnet_s | 75.52 | 128 | 8 | 340.18 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | +| mixnet_m | 76.64 | 128 | 8 | 384.68 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | +| mixnet_l | 78.73 | 128 | 8 | 389.97 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | +| hrnet_w32 | 80.64 | 128 | 8 | 335.73 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/hrnet) | +| hrnet_w48 | 81.19 | 128 | 8 | 463.63 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/hrnet) | +| bit_resnet50 | 76.81 | 32 | 8 | 130.60 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | +| bit_resnet50x3 | 80.63 | 32 | 8 | 533.09 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | +| bit_resnet101 | 77.93| 16 | 8 | 128.15 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | +| repvgg_a0 | 72.19 | 32 | 8 | 27.63 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| repvgg_a1 | 74.19 | 32 | 8 | 27.45 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| repvgg_a2 | 76.63 | 32 | 8 | 39.79 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| repvgg_b0 | 74.99 | 32 | 8 | 33.05 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| repvgg_b1 | 78.81 | 32 | 8 | 68.88 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| repvgg_b2 | 79.29 | 32 | 8 | 106.90 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| repvgg_b3 | 80.46 | 32 | 8 | 137.24 | O0| [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| repvgg_b1g2 | 78.03 | 32 | 8 | 59.71 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| repvgg_b1g4 | 77.64 | 32 | 8 | 65.83 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| repvgg_b2g4 | 78.80 | 32 | 8 | 89.57 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| repmlp_t224 | 76.71 | 128 | 8 | 973.88 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repmlp) | +| convnext_tiny | 81.91 | 128 | 8 | 343.21 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | +| convnext_small | 83.40 | 128 | 8 | 405.96 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | +| convnext_base | 83.32 | 128 | 8 | 531.10 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | +| vit_b_32_224 | 75.86 | 256 | 8 | 623.09 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | +| vit_l_16_224 | 76.34| 48 | 8 | 613.98 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | +| vit_l_32_224 | 73.71 | 128 | 8 | 527.58 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | +| swintransformer_tiny | 80.82 | 256 | 8 | 1765.65 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/swintransformer) | +| pvt_tiny | 74.81 | 128 | 8 | 310.74 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | +| pvt_small | 79.66 | 128 | 8 | 431.15 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | +| pvt_medium | 81.82 | 128 | 8 | 613.08 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | +| pvt_large | 81.75 | 128 | 8 | 860.41 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | +| pvt_v2_b0 | 71.50 | 128 | 8 | 338.78 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | +| pvt_v2_b1 | 78.91 | 128 | 8 | 337.94 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | +| pvt_v2_b2 | 81.99 | 128 | 8 | 503.79 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | +| pvt_v2_b3 | 82.84 | 128 | 8 | 738.90 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | +| pvt_v2_b4 | 83.14 | 128 | 8 | 1030.06 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | +| pit_ti | 72.96 | 128 | 8 | 339.44 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | +| pit_xs | 78.41 | 128 | 8 | 338.70 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | +| pit_s | 80.56 | 128 | 8 | 336.08 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | +| pit_b | 81.87 | 128 | 8 | 350.33 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | +| coat_lite_tiny | 77.35 | 64 | 8 | 258.07 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | +| coat_lite_mini | 78.51 | 64 | 8 | 265.44 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | +| coat_tiny | 79.67 | 64 | 8 | 580.54 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | +| convit_tiny | 73.66 | 256 | 8 | 388.80 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | +| convit_tiny_plus | 77.00 | 256 | 8 | 393.60 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | +| convit_small | 81.63 | 192 | 8 | 588.73 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | +| convit_small_plus | 81.80 | 192 | 8 | 665.74 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | +| convit_base | 82.10 | 128 | 8 | 701.84 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | +| convit_base_plus | 81.96 | 128 | 8 | 983.21 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | +| crossvit_9 | 73.56 | 256 | 8 | 685.25 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | +| crossvit_15 | 81.08 | 256 | 8 | 1086.00 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | +| crossvit_18 | 81.93 | 256 | 8 | 1137.60 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | +| mobilevit_xx_small | 68.90 | uploading | uploading |uploading | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | +| mobilevit_x_small | 74.98 | uploading | uploading | uploading | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | +| mobilevit_small | 78.48 | uploading | uploading | uploading | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | +| visformer_tiny | 78.28 | 128 | 8 | 393.29 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | +| visformer_tiny_v2 | 78.82 | 256 | 8 | 627.20 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | +| visformer_small | 81.76 | 64 | 8 | 155.88 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | +| visformer_small_v2 | 82.17 | 64 | 8 | 158.27 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | +| edgenext_xx_small | 71.02 | 256 | 8 | 1207.78 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | +| edgenext_x_small | 75.14 | 256 | 8 | 1961.42 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | +| edgenext_small | 79.15 | 256 | 8 | 882.00 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | +| edgenext_base | 82.24 | 256 | 8 | 1151.98 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | +| poolformer_s12 | 77.33 | 128 | 8 | 316.77 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/poolformer) | +| xcit_tiny_12_p16 | 77.67 | 128 | 8 | 352.30 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/xcit) | +| volo_d1 | 81.82 | 128 | 8 | 575.54 | O3 | uploading | +| cait_s24 | 82.25 | 64 | 8 | 435.54 | O2 | uploading | + + +| 领域 | 子领域 | 网络 | Ascend | GPU | CPU | |:------ |:------| :----------- |:------: |:------: |:-----: | -| Audio | Speaker Recognition | [ecapa_tdnn](https://gitee.com/mindspore/models/tree/master/official/audio/EcapaTDNN) |✅| | | -| Audio | Speech Synthesis | [lpcnet](https://gitee.com/mindspore/models/tree/master/official/audio/LPCNet) |✅| ✅ | | -| Audio | Speech Synthesis | [melgan](https://gitee.com/mindspore/models/tree/master/official/audio/MELGAN) |✅| ✅ | | -| Audio | Speech Synthesis | [tacotron2](https://gitee.com/mindspore/models/tree/master/official/audio/Tacotron2) |✅| | | -| Graph Neural Network | Text Classification | [bgcf](https://gitee.com/mindspore/models/tree/master/research/gnn/bgcf) |✅| ✅ | | -| Graph Neural Network | Text Classification | [gat](https://gitee.com/mindspore/models/tree/master/research/gnn/gat) |✅| ✅ | | -| Graph Neural Network | Text Classification | [gcn](https://gitee.com/mindspore/models/tree/master/official/gnn/GCN) |✅| ✅ | | -| Recommendation | Recommender System | [naml](https://gitee.com/mindspore/models/tree/master/research/recommend/naml) |✅| ✅ | | -| Recommendation | Recommender System | [ncf](https://gitee.com/mindspore/models/tree/master/research/recommend/ncf) |✅| ✅ | | -| Recommendation | Recommender System | [tbnet](https://gitee.com/mindspore/models/tree/master/official/recommend/Tbnet) |✅| ✅ | | -| Image | Image Classification | [alexnet](https://gitee.com/mindspore/models/tree/master/research/cv/Alexnet) |✅| ✅ | | -| Image | Image Denoise | [brdnet](https://gitee.com/mindspore/models/tree/master/research/cv/brdnet) |✅| | | -| Image | Object Detection | [centerface](https://gitee.com/mindspore/models/tree/master/research/cv/centerface) |✅| ✅ | ✅ | -| Image | Image Classification | [cnn_direction_model](https://gitee.com/mindspore/models/tree/master/research/cv/cnn_direction_model) |✅| ✅ | | -| Image | Scene Text Recognition | [cnnctc](https://gitee.com/mindspore/models/tree/master/research/cv/cnnctc) |✅| ✅ | ✅ | -| Image | Scene Text Recognition | [crnn](https://gitee.com/mindspore/models/tree/master/official/cv/CRNN) |✅| ✅ | ✅ | -| Image | Scene Text Recognition | [crnn_seq2seq_ocr](https://gitee.com/mindspore/models/tree/master/research/cv/crnn_seq2seq_ocr) |✅| | | -| Image | Image Classification | [cspdarknet53](https://gitee.com/mindspore/models/tree/master/research/cv/cspdarknet53) |✅| | | -| Image | Object Detection | [ctpn](https://gitee.com/mindspore/models/tree/master/official/cv/CTPN) |✅| ✅ | | -| Image | Object Detection | [darknet53](https://gitee.com/mindspore/models/tree/master/research/cv/darknet53) | | ✅ | | -| Image | Text Detection | [dbnet](https://gitee.com/mindspore/models/tree/master/official/cv/DBNet) |✅| ✅ | ✅ | -| Image | Semantic Segmentation | [deeplabv3](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabV3P) |✅| ✅ | ✅ | -| Image | Text Detection | [deeptext](https://gitee.com/mindspore/models/tree/master/official/cv/DeepText) |✅| ✅ | | -| Image | Image Classification | [densenet100](https://gitee.com/mindspore/models/tree/master/research/cv/densenet) |✅| ✅ | | -| Image | Image Classification | [densenet121](https://gitee.com/mindspore/models/tree/master/research/cv/densenet) |✅| ✅ | | -| Image | Depth Estimation | [depthnet](https://gitee.com/mindspore/models/tree/master/official/cv/DepthNet) |✅| | | -| Image | Image Denoise | [dncnn](https://gitee.com/mindspore/models/tree/master/research/cv/dncnn) | | ✅ | | -| Image | Image Classification | [dpn](https://gitee.com/mindspore/models/tree/master/research/cv/dpn) |✅| ✅ | | -| Image | Scene Text Detection | [east](https://gitee.com/mindspore/models/tree/master/research/cv/east) |✅| ✅ | | -| Image | Image Classification | [efficientnet](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet) | | ✅ | ✅ | -| Image | Image Classification | [erfnet](https://gitee.com/mindspore/models/tree/master/research/cv/erfnet) |✅| ✅ | | -| Image | Scene Text Recognition | [essay-recogination](https://gitee.com/mindspore/models/tree/master/research/cv/essay-recogination) | | ✅ | | -| Image | Object Detection | [FasterRCNN_Inception_Resnetv2](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| Image | Object Detection | [FasterRCNN_ResNetV1.5_50](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| Image | Object Detection | [FasterRCNN_ResNetV1_101](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| Image | Object Detection | [FasterRCNN_ResNetV1_152](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| Image | Object Detection | [FasterRCNN_ResNetV1_50](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| Image | Semantic Segmentation | [fastscnn](https://gitee.com/mindspore/models/tree/master/research/cv/fastscnn) |✅| | | -| Image | Semantic Segmentation | [FCN8s](https://gitee.com/mindspore/models/tree/master/research/cv/FCN8s) |✅| ✅ | | -| Image | Image Classification | [googlenet](https://gitee.com/mindspore/models/tree/master/research/cv/googlenet) |✅| ✅ | | -| Image | Image Classification | [inceptionv3](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv3) |✅| ✅ | ✅ | -| Image | Image Classification | [inceptionv4](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv4) |✅| ✅ | ✅ | -| Image | Image Denoise | [LearningToSeeInTheDark](https://gitee.com/mindspore/models/tree/master/research/cv/LearningToSeeInTheDark) |✅| | | -| Image | Image Classification | [lenet](https://gitee.com/mindspore/models/tree/master/research/cv/lenet) |✅| ✅ | ✅ | -| Image | Object Detection | [maskrcnn_resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/MaskRCNN/maskrcnn_resnet50) |✅| ✅ | | -| Image | Object Detection | [maskrcnn_mobilenetv1](https://gitee.com/mindspore/models/tree/master/official/cv/MaskRCNN/maskrcnn_mobilenetv1) |✅| ✅ | ✅ | -| Image | Crowd Counting | [MCNN](https://gitee.com/mindspore/models/tree/master/research/cv/MCNN) |✅| ✅ | | -| Image | Image Classification | [mobilenetv1](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv1) |✅| ✅ | | -| Image | Image Classification | [mobilenetv2](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv2) |✅| ✅ | ✅ | -| Image | Image Classification | [mobilenetv3](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv3) |✅| ✅ | ✅ | -| Image | Image Classification | [nasnet](https://gitee.com/mindspore/models/tree/master/research/cv/nasnet) |✅| ✅ | | -| Image | Image Quality Assessment | [nima](https://gitee.com/mindspore/models/tree/master/research/cv/nima) |✅| ✅ | | -| Image | Point Cloud Model | [octsqueeze](https://gitee.com/mindspore/models/tree/master/official/cv/OctSqueeze) |✅| ✅ | | -| Image | Keypoint Detection | [openpose](https://gitee.com/mindspore/models/tree/master/official/cv/OpenPose) |✅| | | -| Image | Defect Detection | [patchcore](https://gitee.com/mindspore/models/tree/master/official/cv/PatchCore) |✅| ✅ | | -| Image | Camera Relocalization | [posenet](https://gitee.com/mindspore/models/tree/master/research/cv/PoseNet) |✅| ✅ | | -| Image | Video Predictive Learning | [predrnn++](https://gitee.com/mindspore/models/tree/master/research/cv/predrnn++) |✅| | | -| Image | Scene Text Detection | [psenet](https://gitee.com/mindspore/models/tree/master/research/cv/psenet) |✅| ✅ | | -| Image | Pose Estimation | [pvnet](https://gitee.com/mindspore/models/tree/master/official/cv/PVNet) |✅| | | -| Image | Optical Flow Estimation | [pwcnet](https://gitee.com/mindspore/models/tree/master/official/cv/PWCNet) |✅| ✅ | | -| Image | Image Super Resolution | [RDN](https://gitee.com/mindspore/models/tree/master/research/cv/RDN) |✅| ✅ | | -| Image | Image Classification | [resnet101](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| Image | Image Classification | [resnet152](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| Image | Image Classification | [resnet18](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| Image | Image Classification | [resnet34](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| Image | Image Classification | [resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| Image | Image Classification | [resnet50_thor](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | | -| Image | Image Classification | [resnext101](https://gitee.com/mindspore/models/tree/master/official/cv/ResNeXt) |✅| ✅ | | -| Image | Image Classification | [resnext50](https://gitee.com/mindspore/models/tree/master/official/cv/ResNeXt) |✅| ✅ | | -| Image | Object Detection | [retinaface_resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/RetinaFace_ResNet50) | | ✅ | | -| Image | Object Detection | [retinanet](https://gitee.com/mindspore/models/tree/master/official/cv/RetinaNet) |✅| ✅ | | -| Image | Image Classification | [se_resnext50](https://gitee.com/mindspore/models/tree/master/research/cv/SE_ResNeXt50) |✅| | | -| Image | Image Matting | [semantic_human_matting](https://gitee.com/mindspore/models/tree/master/official/cv/SemanticHumanMatting) |✅| | | -| Image | Image Classification | [se-resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| Image | Image Classification | [shufflenetv1](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv1) |✅| ✅ | ✅ | -| Image | Image Classification | [shufflenetv2](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv2) |✅| ✅ | ✅ | -| Image | Image Classification | [simclr](https://gitee.com/mindspore/models/tree/master/research/cv/simclr) |✅| ✅ | | -| Image | Keypoint Detection | [simple_pose](https://gitee.com/mindspore/models/tree/master/research/cv/simple_pose) |✅| ✅ | | -| Image | Object Detection | [sphereface](https://gitee.com/mindspore/models/tree/master/research/cv/sphereface) |✅| ✅ | | -| Image | Image Classification | [squeezenet](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | -| Image | Image Classification | [SqueezeNet_Residual](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | -| Image | Image Super Resolution | [srcnn](https://gitee.com/mindspore/models/tree/master/research/cv/srcnn) |✅| ✅ | | -| Image | Object Detection | [ssd_mobilenet-v1-fpn](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | -| Image | Object Detection | [ssd-mobilenet-v2](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | -| Image | Object Detection | [ssd-resnet50-fpn](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | -| Image | Object Detection | [ssd-vgg16](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | -| Image | Defect Detection | [ssim-ae](https://gitee.com/mindspore/models/tree/master/official/cv/SSIM-AE) |✅| | | -| Image | Image Classification | [tinydarknet](https://gitee.com/mindspore/models/tree/master/research/cv/tinydarknet) |✅| ✅ | ✅ | -| Image | Semantic Segmentation | [UNet_nested](https://gitee.com/mindspore/models/tree/master/official/cv/Unet) |✅| ✅ | | -| Image | Semantic Segmentation | [unet2d](https://gitee.com/mindspore/models/tree/master/official/cv/Unet) |✅| ✅ | | -| Image | Semantic Segmentation | [unet3d](https://gitee.com/mindspore/models/tree/master/official/cv/Unet3d) |✅| ✅ | | -| Image | Image Classification | [vgg16](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/vgg16) |✅| ✅ | ✅ | -| Image | Image Classification | [vit](https://gitee.com/mindspore/models/tree/master/official/cv/VIT) |✅| ✅ | | -| Image | Scene Text Recognition | [warpctc](https://gitee.com/mindspore/models/tree/master/research/cv/warpctc) |✅| ✅ | | -| Image | Image Classification | [xception](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/xception) |✅| ✅ | | -| Image | Object Detection | [yolov3_darknet53](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv3) |✅| ✅ | | -| Image | Object Detection | [yolov3_resnet18](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_resnet18) |✅| | | -| Image | Object Detection | [yolov4](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv4) |✅| | | -| Image | Object Detection | [yolov5s](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv5) |✅| ✅ | | -| Recommendation | Click-Through Rate Prediction | [deep_and_cross](https://gitee.com/mindspore/models/tree/master/research/recommend/deep_and_cross) | | ✅ | | -| Recommendation | Click-Through Rate Prediction | [deepfm](https://gitee.com/mindspore/models/tree/master/official/recommend/DeepFM) |✅| ✅ | | -| Recommendation | Click-Through Rate Prediction | [fibinet](https://gitee.com/mindspore/models/tree/master/research/recommend/fibinet) | | ✅ | | -| Recommendation | Click-Through Rate Prediction | [wide_and_deep](https://gitee.com/mindspore/models/tree/master/official/recommend/Wide_and_Deep) |✅| ✅ | | -| Recommendation | Click-Through Rate Prediction | [wide_and_deep_multitable](https://gitee.com/mindspore/models/tree/master/official/recommend/Wide_and_Deep_Multitable) |✅| ✅ | | -| Text | Natural Language Understanding | [bert_base](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | -| Text | Natural Language Understanding | [bert_bilstm_crf](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | -| Text | Natural Language Understanding | [bert_finetuning](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | -| Text | Natural Language Understanding | [bert_large](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| | | -| Text | Natural Language Understanding | [bert_nezha](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | -| Text | Natural Language Understanding | [cpm](https://gitee.com/mindspore/models/tree/master/research/nlp/cpm) |✅| ✅ | | -| Text | Dialogue | [dgu](https://gitee.com/mindspore/models/tree/master/research/nlp/dgu) |✅| ✅ | | -| Text | Dialogue | [duconv](https://gitee.com/mindspore/models/tree/master/research/nlp/duconv) |✅| ✅ | | -| Text | Emotion Classification | [emotect](https://gitee.com/mindspore/models/tree/master/research/nlp/emotect) |✅| ✅ | | -| Text | Natural Language Understanding | [ernie](https://gitee.com/mindspore/models/tree/master/research/nlp/ernie) |✅| ✅ | | -| Text | Natural Language Understanding | [fasttext](https://gitee.com/mindspore/models/tree/master/research/nlp/fasttext) |✅| ✅ | | -| Text | Natural Language Understanding | [gnmt_v2](https://gitee.com/mindspore/models/tree/master/research/nlp/gnmt_v2) |✅| ✅ | | -| Text | Natural Language Understanding | [gpt3](https://gitee.com/mindspore/models/tree/master/official/nlp/GPT) |✅| | | -| Text | Natural Language Understanding | [gru](https://gitee.com/mindspore/models/tree/master/official/nlp/GRU) |✅| ✅ | | -| Text | Emotion Classification | [lstm](https://gitee.com/mindspore/models/tree/master/official/nlp/LSTM) |✅| ✅ | | -| Text | Natural Language Understanding | [mass](https://gitee.com/mindspore/models/tree/master/research/nlp/mass) |✅| ✅ | | -| Text | Pre Training | [pangu_alpha](https://gitee.com/mindspore/models/tree/master/official/nlp/Pangu_alpha) |✅| ✅ | | -| Text | Natural Language Understanding | [textcnn](https://gitee.com/mindspore/models/tree/master/research/nlp/textcnn) |✅| ✅ | | -| Text | Natural Language Understanding | [tinybert](https://gitee.com/mindspore/models/tree/master/research/nlp/tinybert) |✅| ✅ | | -| Text | Natural Language Understanding | [transformer](https://gitee.com/mindspore/models/tree/master/official/nlp/Transformer) |✅| ✅ | | -| Video | Object Tracking | [ADNet](https://gitee.com/mindspore/models/tree/master/research/cv/ADNet) |✅| | | -| Video | Video Classification | [c3d](https://gitee.com/mindspore/models/tree/master/official/cv/C3D) |✅| ✅ | | -| Video | Object Tracking | [Deepsort](https://gitee.com/mindspore/models/tree/master/research/cv/Deepsort) |✅| ✅ | | - -### Research - -| Domain | Sub Domain | Network | Ascend | GPU | CPU | +| 语音 | 声纹识别 | [ecapa_tdnn](https://gitee.com/mindspore/models/tree/master/official/audio/EcapaTDNN) |✅| | | +| 语音 | 语音合成 | [lpcnet](https://gitee.com/mindspore/models/tree/master/official/audio/LPCNet) |✅| ✅ | | +| 语音 | 语音合成 | [melgan](https://gitee.com/mindspore/models/tree/master/official/audio/MELGAN) |✅| ✅ | | +| 语音 | 语音合成 | [tacotron2](https://gitee.com/mindspore/models/tree/master/official/audio/Tacotron2) |✅| | | + +| 图神经网络 | 文本分类 | [gcn](https://gitee.com/mindspore/models/tree/master/official/gnn/GCN) |✅| ✅ | | +| 推荐 | 推荐系统 | [naml](https://gitee.com/mindspore/models/tree/master/research/recommend/naml) |✅| ✅ | | +| 推荐 | 推荐系统 | [ncf](https://gitee.com/mindspore/models/tree/master/research/recommend/ncf) |✅| ✅ | | +| 推荐 | 推荐系统 | [tbnet](https://gitee.com/mindspore/models/tree/master/official/recommend/Tbnet) |✅| ✅ | | +| 图像 | 图像去噪 | [brdnet](https://gitee.com/mindspore/models/tree/master/research/cv/brdnet) |✅| | | +| 图像 | 目标检测 | [centerface](https://gitee.com/mindspore/models/tree/master/research/cv/centerface) |✅| ✅ | ✅ | +| 图像 | 文本识别 | [cnnctc](https://gitee.com/mindspore/models/tree/master/research/cv/cnnctc) |✅| ✅ | ✅ | +| 图像 | 文本识别 | [crnn](https://gitee.com/mindspore/models/tree/master/official/cv/CRNN) |✅| ✅ | ✅ | +| 图像 | 文本识别 | [crnn_seq2seq_ocr](https://gitee.com/mindspore/models/tree/master/research/cv/crnn_seq2seq_ocr) |✅| | | +| 图像 | 目标检测 | [ctpn](https://gitee.com/mindspore/models/tree/master/official/cv/CTPN) |✅| ✅ | | +| 图像 | 目标检测 | [darknet53](https://gitee.com/mindspore/models/tree/master/research/cv/darknet53) | | ✅ | | +| 图像 | 文本检测 | [dbnet](https://gitee.com/mindspore/models/tree/master/official/cv/DBNet) |✅| ✅ | ✅ | +| 图像 | 语义分割 | [deeplabv3](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabV3P) |✅| ✅ | ✅ | +| 图像 | 文本检测 | [deeptext](https://gitee.com/mindspore/models/tree/master/official/cv/DeepText) |✅| ✅ | | +| 图像 | 深度估计 | [depthnet](https://gitee.com/mindspore/models/tree/master/official/cv/DepthNet) |✅| | | +| 图像 | 图像去噪 | [dncnn](https://gitee.com/mindspore/models/tree/master/research/cv/dncnn) | | ✅ | | +| 图像 | 文本检测 | [east](https://gitee.com/mindspore/models/tree/master/research/cv/east) |✅| ✅ | | +| 图像 | 文本识别 | [essay-recogination](https://gitee.com/mindspore/models/tree/master/research/cv/essay-recogination) | | ✅ | | +| 图像 | 目标检测 | [FasterRCNN_Inception_Resnetv2](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | +| 图像 | 目标检测 | [FasterRCNN_ResNetV1.5_50](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | +| 图像 | 目标检测 | [FasterRCNN_ResNetV1_101](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | +| 图像 | 目标检测 | [FasterRCNN_ResNetV1_152](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | +| 图像 | 目标检测 | [FasterRCNN_ResNetV1_50](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | +| 图像 | 语义分割 | [fastscnn](https://gitee.com/mindspore/models/tree/master/research/cv/fastscnn) |✅| | | +| 图像 | 语义分割 | [FCN8s](https://gitee.com/mindspore/models/tree/master/research/cv/FCN8s) |✅| ✅ | | +| 图像 | 图像分类 | [inceptionv3](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv3) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [inceptionv4](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv4) |✅| ✅ | ✅ | +| 图像 | 图像去噪 | [LearningToSeeInTheDark](https://gitee.com/mindspore/models/tree/master/research/cv/LearningToSeeInTheDark) |✅| | | +| 图像 | 图像分类 | [lenet](https://gitee.com/mindspore/models/tree/master/research/cv/lenet) |✅| ✅ | ✅ | +| 图像 | 目标检测 | [maskrcnn_resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/MaskRCNN/maskrcnn_resnet50) |✅| ✅ | | +| 图像 | 目标检测 | [maskrcnn_mobilenetv1](https://gitee.com/mindspore/models/tree/master/official/cv/MaskRCNN/maskrcnn_mobilenetv1) |✅| ✅ | ✅ | +| 图像 | 人群计数 | [MCNN](https://gitee.com/mindspore/models/tree/master/research/cv/MCNN) |✅| ✅ | | +| 图像 | 图像分类 | [mobilenetv1](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv1) |✅| ✅ | | +| 图像 | 图像分类 | [mobilenetv2](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv2) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [mobilenetv3](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv3) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [nasnet](https://gitee.com/mindspore/models/tree/master/research/cv/nasnet) |✅| ✅ | | +| 图像 | 图像质量评估 | [nima](https://gitee.com/mindspore/models/tree/master/research/cv/nima) |✅| ✅ | | +| 图像 | 点云模型 | [octsqueeze](https://gitee.com/mindspore/models/tree/master/official/cv/OctSqueeze) |✅| ✅ | | +| 图像 | 关键点检测 | [openpose](https://gitee.com/mindspore/models/tree/master/official/cv/OpenPose) |✅| | | +| 图像 | 缺陷检测 | [patchcore](https://gitee.com/mindspore/models/tree/master/official/cv/PatchCore) |✅| ✅ | | +| 图像 | 相机重定位 | [posenet](https://gitee.com/mindspore/models/tree/master/research/cv/PoseNet) |✅| ✅ | | +| 图像 | 视频预测学习 | [predrnn++](https://gitee.com/mindspore/models/tree/master/research/cv/predrnn++) |✅| | | +| 图像 | 文本检测 | [psenet](https://gitee.com/mindspore/models/tree/master/research/cv/psenet) |✅| ✅ | | +| 图像 | 姿态估计 | [pvnet](https://gitee.com/mindspore/models/tree/master/official/cv/PVNet) |✅| | | +| 图像 | 光流估计 | [pwcnet](https://gitee.com/mindspore/models/tree/master/official/cv/PWCNet) |✅| ✅ | | +| 图像 | 图像超分 | [RDN](https://gitee.com/mindspore/models/tree/master/research/cv/RDN) |✅| ✅ | | +| 图像 | 图像分类 | [resnet101](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [resnet152](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [resnet18](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [resnet34](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [resnet50_thor](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | | +| 图像 | 图像分类 | [resnext101](https://gitee.com/mindspore/models/tree/master/official/cv/ResNeXt) |✅| ✅ | | +| 图像 | 图像分类 | [resnext50](https://gitee.com/mindspore/models/tree/master/official/cv/ResNeXt) |✅| ✅ | | +| 图像 | 目标检测 | [retinaface_resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/RetinaFace_ResNet50) | | ✅ | | +| 图像 | 目标检测 | [retinanet](https://gitee.com/mindspore/models/tree/master/official/cv/RetinaNet) |✅| ✅ | | +| 图像 | 图像分类 | [se_resnext50](https://gitee.com/mindspore/models/tree/master/research/cv/SE_ResNeXt50) |✅| | | +| 图像 | 图像抠图 | [semantic_human_matting](https://gitee.com/mindspore/models/tree/master/official/cv/SemanticHumanMatting) |✅| | | +| 图像 | 图像分类 | [se-resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [shufflenetv1](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv1) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [shufflenetv2](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv2) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [simclr](https://gitee.com/mindspore/models/tree/master/research/cv/simclr) |✅| ✅ | | +| 图像 | 关键点检测 | [simple_pose](https://gitee.com/mindspore/models/tree/master/research/cv/simple_pose) |✅| ✅ | | +| 图像 | 目标检测 | [sphereface](https://gitee.com/mindspore/models/tree/master/research/cv/sphereface) |✅| ✅ | | +| 图像 | 图像分类 | [squeezenet](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | +| 图像 | 图像分类 | [SqueezeNet_Residual](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | +| 图像 | 图像超分 | [srcnn](https://gitee.com/mindspore/models/tree/master/research/cv/srcnn) |✅| ✅ | | +| 图像 | 目标检测 | [ssd_mobilenet-v1-fpn](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | +| 图像 | 目标检测 | [ssd_mobilenet-v2](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | +| 图像 | 目标检测 | [ssd-resnet50-fpn](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | +| 图像 | 目标检测 | [ssd-vgg16](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | +| 图像 | 缺陷检测 | [ssim-ae](https://gitee.com/mindspore/models/tree/master/official/cv/SSIM-AE) |✅| | | +| 图像 | 图像分类 | [tinydarknet](https://gitee.com/mindspore/models/tree/master/research/cv/tinydarknet) |✅| ✅ | ✅ | +| 图像 | 语义分割 | [UNet_nested](https://gitee.com/mindspore/models/tree/master/official/cv/Unet) |✅| ✅ | | +| 图像 | 语义分割 | [unet2d](https://gitee.com/mindspore/models/tree/master/official/cv/Unet) |✅| ✅ | | +| 图像 | 语义分割 | [unet3d](https://gitee.com/mindspore/models/tree/master/official/cv/Unet3d) |✅| ✅ | | +| 图像 | 图像分类 | [vgg16](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/vgg16) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [vit](https://gitee.com/mindspore/models/tree/master/official/cv/VIT) |✅| ✅ | | +| 图像 | 文本识别 | [warpctc](https://gitee.com/mindspore/models/tree/master/research/cv/warpctc) |✅| ✅ | | +| 图像 | 图像分类 | [xception](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/xception) |✅| ✅ | | +| 图像 | 目标检测 | [yolov3_darknet53](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv3) |✅| ✅ | | +| 图像 | 目标检测 | [yolov3_resnet18](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_resnet18) |✅| | | +| 图像 | 目标检测 | [yolov4](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv4) |✅| | | +| 图像 | 目标检测 | [yolov5s](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv5) |✅| ✅ | | +| 推荐 | 点击率预测 | [deep_and_cross](https://gitee.com/mindspore/models/tree/master/research/recommend/deep_and_cross) | | ✅ | | +| 推荐 | 点击率预测 | [deepfm](https://gitee.com/mindspore/models/tree/master/official/recommend/DeepFM) |✅| ✅ | | +| 推荐 | 点击率预测 | [fibinet](https://gitee.com/mindspore/models/tree/master/research/recommend/fibinet) | | ✅ | | +| 推荐 | 点击率预测 | [wide_and_deep](https://gitee.com/mindspore/models/tree/master/official/recommend/Wide_and_Deep) |✅| ✅ | | +| 推荐 | 点击率预测 | [wide_and_deep_multitable](https://gitee.com/mindspore/models/tree/master/official/recommend/Wide_and_Deep_Multitable) |✅| ✅ | | +| 文本 | 自然语言理解 | [bert_base](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | +| 文本 | 自然语言理解 | [bert_bilstm_crf](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | +| 文本 | 自然语言理解 | [bert_finetuning](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | +| 文本 | 自然语言理解 | [bert_large](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| | | +| 文本 | 自然语言理解 | [bert_nezha](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | +| 文本 | 自然语言理解 | [cpm](https://gitee.com/mindspore/models/tree/master/research/nlp/cpm) |✅| ✅ | | +| 文本 | 对话 | [dgu](https://gitee.com/mindspore/models/tree/master/research/nlp/dgu) |✅| ✅ | | +| 文本 | 对话 | [duconv](https://gitee.com/mindspore/models/tree/master/research/nlp/duconv) |✅| ✅ | | +| 文本 | 情绪分类 | [emotect](https://gitee.com/mindspore/models/tree/master/research/nlp/emotect) |✅| ✅ | | +| 文本 | 自然语言理解 | [ernie](https://gitee.com/mindspore/models/tree/master/research/nlp/ernie) |✅| ✅ | | +| 文本 | 自然语言理解 | [fasttext](https://gitee.com/mindspore/models/tree/master/research/nlp/fasttext) |✅| ✅ | | +| 文本 | 自然语言理解 | [gnmt_v2](https://gitee.com/mindspore/models/tree/master/research/nlp/gnmt_v2) |✅| ✅ | | +| 文本 | 自然语言理解 | [gpt3](https://gitee.com/mindspore/models/tree/master/official/nlp/GPT) |✅| | | +| 文本 | 自然语言理解 | [gru](https://gitee.com/mindspore/models/tree/master/official/nlp/GRU) |✅| ✅ | | +| 文本 | 情绪分类 | [lstm](https://gitee.com/mindspore/models/tree/master/official/nlp/LSTM) |✅| ✅ | | +| 文本 | 自然语言理解 | [mass](https://gitee.com/mindspore/models/tree/master/research/nlp/mass) |✅| ✅ | | +| 文本 | 预训练 | [pangu_alpha](https://gitee.com/mindspore/models/tree/master/official/nlp/Pangu_alpha) |✅| ✅ | | +| 文本 | 自然语言理解 | [textcnn](https://gitee.com/mindspore/models/tree/master/research/nlp/textcnn) |✅| ✅ | | +| 文本 | 自然语言理解 | [tinybert](https://gitee.com/mindspore/models/tree/master/research/nlp/tinybert) |✅| ✅ | | +| 文本 | 自然语言理解 | [transformer](https://gitee.com/mindspore/models/tree/master/official/nlp/Transformer) |✅| ✅ | | +| 视频 | 目标追踪 | [ADNet](https://gitee.com/mindspore/models/tree/master/research/cv/ADNet) |✅| | | +| 视频 | 视频分类 | [c3d](https://gitee.com/mindspore/models/tree/master/official/cv/C3D) |✅| ✅ | | +| 视频 | 目标追踪 | [Deepsort](https://gitee.com/mindspore/models/tree/master/research/cv/Deepsort) |✅| ✅ | | + +### 研究网络 + +| 领域 | 子领域 | 网络 | Ascend | GPU | CPU | |:------ |:------| :----------- |:------: |:------: |:-----: | -| 3D | 3D Reconstruction | [cmr](https://gitee.com/mindspore/models/tree/master/research/cv/cmr) | | ✅ | | -| 3D | 3D Reconstruction | [DecoMR](https://gitee.com/mindspore/models/tree/master/research/cv/DecoMR) | | ✅ | | -| 3D | 3D Reconstruction | [DeepLM](https://gitee.com/mindspore/models/tree/master/research/3d/DeepLM) | | ✅ | | -| 3D | 3D Reconstruction | [eppmvsnet](https://gitee.com/mindspore/models/tree/master/research/cv/eppmvsnet) | | ✅ | | -| 3D | 3D Object Detection | [pointpillars](https://gitee.com/mindspore/models/tree/master/research/cv/pointpillars) |✅| ✅ | | -| Audio | Speech Recognition | [ctcmodel](https://gitee.com/mindspore/models/tree/master/research/audio/ctcmodel) |✅| | | -| Audio | Speech Recognition | [deepspeech2](https://gitee.com/mindspore/models/tree/master/official/audio/DeepSpeech2) | | ✅ | | -| Audio | Keyword Spotting | [dscnn](https://gitee.com/mindspore/models/tree/master/research/audio/dscnn) |✅| ✅ | | -| Audio | Speech Synthesis | [FastSpeech](https://gitee.com/mindspore/models/tree/master/research/audio/FastSpeech) | | ✅ | | -| Audio | Audio Tagging | [fcn-4](https://gitee.com/mindspore/models/tree/master/research/audio/fcn-4) |✅| ✅ | | -| Audio | Speech Recognition | [jasper](https://gitee.com/mindspore/models/tree/master/research/audio/jasper) |✅| ✅ | | -| Audio | Speech Synthesis | [wavenet](https://gitee.com/mindspore/models/tree/master/research/audio/wavenet) |✅| ✅ | | -| Graph Neural Network | Graph Classification | [dgcn](https://gitee.com/mindspore/models/tree/master/research/gnn/dgcn) |✅| | | -| Graph Neural Network | Text Classification | [hypertext](https://gitee.com/mindspore/models/tree/master/research/nlp/hypertext) |✅| ✅ | | -| Graph Neural Network | Graph Classification | [sdne](https://gitee.com/mindspore/models/tree/master/research/gnn/sdne) |✅| | | -| Graph Neural Network | Social and Information Networks | [sgcn](https://gitee.com/mindspore/models/tree/master/research/gnn/sgcn) |✅| ✅ | | -| Graph Neural Network | Text Classification | [textrcnn](https://gitee.com/mindspore/models/tree/master/research/nlp/textrcnn) |✅| ✅ | | -| High Performance Computing | High Performance Computing | [deepbsde](https://gitee.com/mindspore/models/tree/master/research/hpc/deepbsde) | | ✅ | | -| High Performance Computing | High Performance Computing | [molecular_dynamics](https://gitee.com/mindspore/models/tree/master/research/hpc/molecular_dynamics) |✅| | | -| High Performance Computing | High Performance Computing | [ocean_model](https://gitee.com/mindspore/models/tree/master/research/hpc/ocean_model) | | ✅ | | -| High Performance Computing | High Performance Computing | [pafnucy](https://gitee.com/mindspore/models/tree/master/research/hpc/pafnucy) |✅| ✅ | | -| High Performance Computing | High Performance Computing | [pfnn](https://gitee.com/mindspore/models/tree/master/research/hpc/pfnn) | | ✅ | | -| High Performance Computing | High Performance Computing | [pinns](https://gitee.com/mindspore/models/tree/master/research/hpc/pinns) | | ✅ | | -| Image | Image Classification | [3D_DenseNet](https://gitee.com/mindspore/models/tree/master/research/cv/3D_DenseNet) |✅| ✅ | | -| Image | Semantic Segmentation | [3dcnn](https://gitee.com/mindspore/models/tree/master/research/cv/3dcnn) |✅| ✅ | | -| Image | Semantic Segmentation | [adelaide_ea](https://gitee.com/mindspore/models/tree/master/research/cv/adelaide_ea) |✅| | | -| Image | Scene Text Detection | [advanced_east](https://gitee.com/mindspore/models/tree/master/research/cv/advanced_east) |✅| ✅ | | -| Image | Style Transfer | [aecrnet](https://gitee.com/mindspore/models/tree/master/research/cv/aecrnet) |✅| ✅ | | -| Image | Re-Identification | [AlignedReID](https://gitee.com/mindspore/models/tree/master/research/cv/AlignedReID) | | ✅ | | -| Image | Re-Identification | [AlignedReID++](https://gitee.com/mindspore/models/tree/master/research/cv/AlignedReID++) |✅| ✅ | | -| Image | Pose Estimation | [AlphaPose](https://gitee.com/mindspore/models/tree/master/research/cv/AlphaPose) |✅| | | -| Image | Style Transfer | [APDrawingGAN](https://gitee.com/mindspore/models/tree/master/research/cv/APDrawingGAN) |✅| ✅ | | -| Image | Style Transfer | [ArbitraryStyleTransfer](https://gitee.com/mindspore/models/tree/master/research/cv/ArbitraryStyleTransfer) |✅| ✅ | | -| Image | Object Detection | [arcface](https://gitee.com/mindspore/models/tree/master/official/cv/Arcface) |✅| ✅ | | -| Image | Keypoint Detection | [ArtTrack](https://gitee.com/mindspore/models/tree/master/research/cv/ArtTrack) | | ✅ | | -| Image | Style Transfer | [AttGAN](https://gitee.com/mindspore/models/tree/master/research/cv/AttGAN) |✅| ✅ | | -| Image | Image Classification | [augvit](https://gitee.com/mindspore/models/tree/master/research/cv/augvit) | | ✅ | | -| Image | Image Classification | [autoaugment](https://gitee.com/mindspore/models/tree/master/research/cv/autoaugment) |✅| ✅ | | -| Image | Semantic Segmentation | [Auto-DeepLab](https://gitee.com/mindspore/models/tree/master/research/cv/Auto-DeepLab) |✅| | | -| Image | Neural Architecture Search | [AutoSlim](https://gitee.com/mindspore/models/tree/master/research/cv/AutoSlim) |✅| ✅ | | -| Image | Image Classification | [AVA_cifar](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_cifar) |✅| ✅ | | -| Image | Image Classification | [AVA_hpa](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_hpa) |✅| ✅ | | -| Image | Image Classification | [cait](https://gitee.com/mindspore/models/tree/master/research/cv/cait) |✅| ✅ | | -| Image | Object Detection | [CascadeRCNN](https://gitee.com/mindspore/models/tree/master/research/cv/CascadeRCNN) |✅| ✅ | | -| Image | Image Classification | [CBAM](https://gitee.com/mindspore/models/tree/master/research/cv/CBAM) |✅| | | -| Image | Image Classification | [cct](https://gitee.com/mindspore/models/tree/master/research/cv/cct) |✅| ✅ | | -| Image | Keypoint Detection | [centernet](https://gitee.com/mindspore/models/tree/master/research/cv/centernet) |✅| | ✅ | -| Image | Keypoint Detection | [centernet_det](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_det) |✅| | | -| Image | Keypoint Detection | [centernet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet101) |✅| ✅ | | -| Image | Keypoint Detection | [centernet_resnet50_v1](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet50_v1) |✅| | | -| Image | Image Generation | [CGAN](https://gitee.com/mindspore/models/tree/master/research/cv/CGAN) |✅| ✅ | | -| Image | Image Classification | [convnext](https://gitee.com/mindspore/models/tree/master/research/cv/convnext) |✅| ✅ | | -| Image | Image Super Resolution | [csd](https://gitee.com/mindspore/models/tree/master/research/cv/csd) |✅| ✅ | | -| Image | Image Generation | [CTSDG](https://gitee.com/mindspore/models/tree/master/research/cv/CTSDG) | | ✅ | | -| Image | Style Transfer | [CycleGAN](https://gitee.com/mindspore/models/tree/master/official/cv/CycleGAN) |✅| ✅ | | -| Image | Image Super Resolution | [DBPN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) |✅| | | -| Image | Image Super Resolution | [DBPN_GAN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) |✅| | | -| Image | Image Generation | [dcgan](https://gitee.com/mindspore/models/tree/master/research/cv/dcgan) |✅| ✅ | | -| Image | Re-Identification | [DDAG](https://gitee.com/mindspore/models/tree/master/research/cv/DDAG) |✅| ✅ | | -| Image | Semantic Segmentation | [DDM](https://gitee.com/mindspore/models/tree/master/research/cv/DDM) |✅| | | -| Image | Semantic Segmentation | [DDRNet](https://gitee.com/mindspore/models/tree/master/research/cv/DDRNet) |✅| ✅ | | -| Image | Object Detection | [DeepID](https://gitee.com/mindspore/models/tree/master/research/cv/DeepID) |✅| ✅ | | -| Image | Semantic Segmentation | [deeplabv3plus](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabV3P) |✅| ✅ | | -| Image | Image Retrieval | [delf](https://gitee.com/mindspore/models/tree/master/research/cv/delf) |✅| | | -| Image | Zero-Shot Learning | [dem](https://gitee.com/mindspore/models/tree/master/research/cv/dem) |✅| ✅ | | -| Image | Object Detection | [detr](https://gitee.com/mindspore/models/tree/master/research/cv/detr) |✅| ✅ | | -| Image | Semantic Segmentation | [dgcnet_res101](https://gitee.com/mindspore/models/tree/master/research/cv/dgcnet_res101) | | ✅ | | -| Image | Instance Segmentation | [dlinknet](https://gitee.com/mindspore/models/tree/master/research/cv/dlinknet) |✅| | | -| Image | Image Denoise | [DnCNN](https://gitee.com/mindspore/models/tree/master/research/cv/DnCNN) |✅| | | -| Image | Image Classification | [dnet_nas](https://gitee.com/mindspore/models/tree/master/research/cv/dnet_nas) |✅| | | -| Image | Image Classification | [DRNet](https://gitee.com/mindspore/models/tree/master/research/cv/DRNet) |✅| ✅ | | -| Image | Image Super Resolution | [EDSR](https://gitee.com/mindspore/models/tree/master/official/cv/EDSR) |✅| | | -| Image | Object Detection | [EfficientDet_d0](https://gitee.com/mindspore/models/tree/master/research/cv/EfficientDet_d0) |✅| | | -| Image | Image Classification | [efficientnet-b0](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b0) |✅| | | -| Image | Image Classification | [efficientnet-b1](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnet-b1) |✅| | | -| Image | Image Classification | [efficientnet-b2](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnet-b2) |✅| ✅ | | -| Image | Image Classification | [efficientnet-b3](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnet-b3) |✅| ✅ | | -| Image | Image Classification | [efficientnetv2](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnetv2) |✅| | | -| Image | Salient Object Detection | [EGnet](https://gitee.com/mindspore/models/tree/master/research/cv/EGnet) |✅| ✅ | | -| Image | Semantic Segmentation | [E-NET](https://gitee.com/mindspore/models/tree/master/research/cv/E-NET) |✅| ✅ | | -| Image | Image Super Resolution | [esr_ea](https://gitee.com/mindspore/models/tree/master/research/cv/esr_ea) |✅| ✅ | | -| Image | Image Super Resolution | [ESRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/ESRGAN) |✅| ✅ | | -| Image | Image Classification | [FaceAttribute](https://gitee.com/mindspore/models/tree/master/research/cv/FaceAttribute) |✅| ✅ | | -| Image | Object Detection | [faceboxes](https://gitee.com/mindspore/models/tree/master/research/cv/faceboxes) |✅| | | -| Image | Object Detection | [FaceDetection](https://gitee.com/mindspore/models/tree/master/research/cv/FaceDetection) |✅| ✅ | | -| Image | Face Recognition | [FaceNet](https://gitee.com/mindspore/models/tree/master/research/cv/FaceNet) |✅| ✅ | | -| Image | Image Classification | [FaceQualityAssessment](https://gitee.com/mindspore/models/tree/master/research/cv/FaceQualityAssessment) |✅| ✅ | ✅ | -| Image | Object Detection | [FaceRecognition](https://gitee.com/mindspore/models/tree/master/official/cv/FaceRecognition) |✅| ✅ | | -| Image | Object Detection | [FaceRecognitionForTracking](https://gitee.com/mindspore/models/tree/master/research/cv/FaceRecognitionForTracking) |✅| | ✅ | -| Image | Object Detection | [faster_rcnn_dcn](https://gitee.com/mindspore/models/tree/master/research/cv/faster_rcnn_dcn) |✅| ✅ | | -| Image | Image Matting | [FCANet](https://gitee.com/mindspore/models/tree/master/research/cv/FCANet) |✅| | | -| Image | Image Classification | [FDA-BNN](https://gitee.com/mindspore/models/tree/master/research/cv/FDA-BNN) |✅| ✅ | | -| Image | Image Classification | [fishnet99](https://gitee.com/mindspore/models/tree/master/research/cv/fishnet99) |✅| ✅ | | -| Image | Optical Flow Estimation | [flownet2](https://gitee.com/mindspore/models/tree/master/research/cv/flownet2) |✅| | | -| Image | Image Generation | [gan](https://gitee.com/mindspore/models/tree/master/research/cv/gan) |✅| ✅ | | -| Image | Image Classification | [GENet_Res50](https://gitee.com/mindspore/models/tree/master/research/cv/GENet_Res50) |✅| | | -| Image | Image Classification | [ghostnet](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet) |✅| | | -| Image | Image Classification | [ghostnet_d](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet_d) |✅| ✅ | | -| Image | Image Classification | [glore_res200](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) |✅| ✅ | | -| Image | Image Classification | [glore_res50](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) |✅| ✅ | | -| Image | Image Classification | [hardnet](https://gitee.com/mindspore/models/tree/master/research/cv/hardnet) |✅| ✅ | | -| Image | Edge Detection | [hed](https://gitee.com/mindspore/models/tree/master/research/cv/hed) |✅| ✅ | | -| Image | Image Generation | [HiFaceGAN](https://gitee.com/mindspore/models/tree/master/research/cv/HiFaceGAN) | | ✅ | | -| Image | Image Classification | [HourNAS](https://gitee.com/mindspore/models/tree/master/research/cv/HourNAS) | | ✅ | | -| Image | Image Classification | [HRNetW48_cls](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_cls) |✅| ✅ | | -| Image | Semantic Segmentation | [HRNetW48_seg](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_seg) |✅| | | -| Image | Image Classification | [ibnnet](https://gitee.com/mindspore/models/tree/master/research/cv/ibnnet) |✅| ✅ | | -| Image | Semantic Segmentation | [ICNet](https://gitee.com/mindspore/models/tree/master/research/cv/ICNet) |✅| | | -| Image | Image Classification | [inception_resnet_v2](https://gitee.com/mindspore/models/tree/master/research/cv/inception_resnet_v2) |✅| ✅ | | -| Image | Image Classification | [Inceptionv2](https://gitee.com/mindspore/models/tree/master/research/cv/Inception-v2) |✅| ✅ | | -| Image | Image Matting | [IndexNet](https://gitee.com/mindspore/models/tree/master/research/cv/IndexNet) | | ✅ | | -| Image | Image Generation | [IPT](https://gitee.com/mindspore/models/tree/master/research/cv/IPT) |✅| | | -| Image | Image Super Resolution | [IRN](https://gitee.com/mindspore/models/tree/master/research/cv/IRN) |✅| ✅ | | -| Image | Image Classification | [ISyNet](https://gitee.com/mindspore/models/tree/master/research/cv/ISyNet) |✅| ✅ | | -| Image | Image Classification | [ivpf](https://gitee.com/mindspore/models/tree/master/research/cv/ivpf) | | ✅ | | -| Image | Image Denoise | [LearningToSeeInTheDark](https://gitee.com/mindspore/models/tree/master/research/cv/LearningToSeeInTheDark) |✅| | | -| Image | Meta Learning | [LEO](https://gitee.com/mindspore/models/tree/master/research/cv/LEO) |✅| ✅ | | -| Image | Object Detection | [LightCNN](https://gitee.com/mindspore/models/tree/master/research/cv/LightCNN) |✅| ✅ | ✅ | -| Image | Image Super Resolution | [lite-hrnet](https://gitee.com/mindspore/models/tree/master/research/cv/lite-hrnet) | | ✅ | | -| Image | Image Classification | [lresnet100e_ir](https://gitee.com/mindspore/models/tree/master/research/cv/lresnet100e_ir) | | ✅ | | -| Image | Object Detection | [m2det](https://gitee.com/mindspore/models/tree/master/research/cv/m2det) | | ✅ | | -| Image | Autoencoder | [mae](https://gitee.com/mindspore/models/tree/master/official/cv/MAE) |✅| ✅ | | -| Image | Meta Learning | [MAML](https://gitee.com/mindspore/models/tree/master/research/cv/MAML) |✅| ✅ | | -| Image | Scene Text Recognition | [ManiDP](https://gitee.com/mindspore/models/tree/master/research/cv/ManiDP) | | ✅ | | -| Image | Face Recognition | [MaskedFaceRecognition](https://gitee.com/mindspore/models/tree/master/research/cv/MaskedFaceRecognition) |✅| | | -| Image | Meta Learning | [meta-baseline](https://gitee.com/mindspore/models/tree/master/research/cv/meta-baseline) |✅| ✅ | | -| Image | Re-Identification | [MGN](https://gitee.com/mindspore/models/tree/master/research/cv/MGN) |✅| ✅ | | -| Image | Depth Estimation | [midas](https://gitee.com/mindspore/models/tree/master/research/cv/midas) |✅| ✅ | | -| Image | Image Denoise | [MIMO-UNet](https://gitee.com/mindspore/models/tree/master/research/cv/MIMO-UNet) | | ✅ | | -| Image | Image Classification | [mnasnet](https://gitee.com/mindspore/models/tree/master/research/cv/mnasnet) |✅| ✅ | | -| Image | Image Classification | [mobilenetv3_large](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetv3_large) |✅| | ✅ | -| Image | Image Classification | [mobilenetV3_small_x1_0](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetV3_small_x1_0) |✅| ✅ | ✅ | -| Image | Image Classification | [MultiTaskNet](https://gitee.com/mindspore/models/tree/master/research/cv/PAMTRI/MultiTaskNet) |✅| ✅ | | -| Image | Re-Identification | [MVD](https://gitee.com/mindspore/models/tree/master/research/cv/MVD) |✅| ✅ | | -| Image | Object Detection | [nas-fpn](https://gitee.com/mindspore/models/tree/master/research/cv/nas-fpn) |✅| | | -| Image | Image Denoise | [Neighbor2Neighbor](https://gitee.com/mindspore/models/tree/master/research/cv/Neighbor2Neighbor) |✅| ✅ | | -| Image | Image Classification | [NFNet](https://gitee.com/mindspore/models/tree/master/research/cv/NFNet) |✅| ✅ | | -| Image | Image Quality Assessment | [nima_vgg16](https://gitee.com/mindspore/models/tree/master/research/cv/nima_vgg16) | | ✅ | | -| Image | Semantic Segmentation | [nnUNet](https://gitee.com/mindspore/models/tree/master/research/cv/nnUNet) |✅| ✅ | | -| Image | Image Classification | [ntsnet](https://gitee.com/mindspore/models/tree/master/research/cv/ntsnet) |✅| ✅ | | -| Image | Semantic Segmentation | [OCRNet](https://gitee.com/mindspore/models/tree/master/official/cv/OCRNet) |✅| ✅ | | -| Image | Re-Identification | [osnet](https://gitee.com/mindspore/models/tree/master/research/cv/osnet) |✅| ✅ | | -| Image | Salient Object Detection | [PAGENet](https://gitee.com/mindspore/models/tree/master/research/cv/PAGENet) |✅| ✅ | | -| Image | Image Retrieval | [pcb](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | -| Image | Image Retrieval | [pcb](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | -| Image | Image Retrieval | [pcb_rpp](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | -| Image | Image Classification | [PDarts](https://gitee.com/mindspore/models/tree/master/research/cv/PDarts) |✅| ✅ | | -| Image | Image Generation | [PGAN](https://gitee.com/mindspore/models/tree/master/research/cv/PGAN) |✅| ✅ | | -| Image | Image Generation | [Pix2Pix](https://gitee.com/mindspore/models/tree/master/research/cv/Pix2Pix) |✅| ✅ | | -| Image | Image Super Resolution | [Pix2PixHD](https://gitee.com/mindspore/models/tree/master/official/cv/Pix2PixHD) |✅| | | -| Image | Image Classification | [pnasnet](https://gitee.com/mindspore/models/tree/master/research/cv/pnasnet) |✅| ✅ | | -| Image | Point Cloud Model | [pointnet](https://gitee.com/mindspore/models/tree/master/official/cv/PointNet) |✅| ✅ | | -| Image | Point Cloud Model | [pointnet2](https://gitee.com/mindspore/models/tree/master/official/cv/PointNet2) |✅| ✅ | | -| Image | Image Classification | [PoseEstNet](https://gitee.com/mindspore/models/tree/master/research/cv/PAMTRI/PoseEstNet) |✅| ✅ | | -| Image | Image Classification | [ProtoNet](https://gitee.com/mindspore/models/tree/master/research/cv/ProtoNet) |✅| ✅ | | -| Image | Image Classification | [proxylessnas](https://gitee.com/mindspore/models/tree/master/research/cv/proxylessnas) |✅| ✅ | | -| Image | Semantic Segmentation | [PSPNet](https://gitee.com/mindspore/models/tree/master/research/cv/PSPNet) |✅| | | -| Image | Salient Object Detection | [ras](https://gitee.com/mindspore/models/tree/master/research/cv/ras) |✅| ✅ | | -| Image | Image Super Resolution | [RCAN](https://gitee.com/mindspore/models/tree/master/research/cv/RCAN) |✅| | | -| Image | Object Detection | [rcnn](https://gitee.com/mindspore/models/tree/master/research/cv/rcnn) |✅| ✅ | | -| Image | Image Super Resolution | [REDNet30](https://gitee.com/mindspore/models/tree/master/research/cv/REDNet30) |✅| ✅ | | -| Image | Object Detection | [RefineDet](https://gitee.com/mindspore/models/tree/master/research/cv/RefineDet) |✅| ✅ | | -| Image | Semantic Segmentation | [RefineNet](https://gitee.com/mindspore/models/tree/master/research/cv/RefineNet) |✅| ✅ | | -| Image | Re-Identification | [ReIDStrongBaseline](https://gitee.com/mindspore/models/tree/master/research/cv/ReIDStrongBaseline) |✅| ✅ | | -| Image | Image Classification | [relationnet](https://gitee.com/mindspore/models/tree/master/research/cv/relationnet) |✅| ✅ | | -| Image | Image Classification | [renas](https://gitee.com/mindspore/models/tree/master/research/cv/renas) |✅| ✅ | ✅ | -| Image | Semantic Segmentation | [repvgg](https://gitee.com/mindspore/models/tree/master/research/cv/repvgg) |✅| ✅ | | -| Image | Semantic Segmentation | [res2net_deeplabv3](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_deeplabv3) |✅| | ✅ | -| Image | Object Detection | [res2net_faster_rcnn](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_faster_rcnn) |✅| ✅ | | -| Image | Object Detection | [res2net_yolov3](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_yolov3) |✅| ✅ | | -| Image | Image Classification | [res2net101](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| Image | Image Classification | [res2net152](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| Image | Image Classification | [res2net50](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| Image | Image Classification | [ResNeSt50](https://gitee.com/mindspore/models/tree/master/research/cv/ResNeSt50) |✅| ✅ | | -| Image | Image Classification | [resnet50_adv_pruning](https://gitee.com/mindspore/models/tree/master/research/cv/resnet50_adv_pruning) |✅| ✅ | | -| Image | Image Classification | [resnet50_bam](https://gitee.com/mindspore/models/tree/master/research/cv/resnet50_bam) |✅| ✅ | | -| Image | Image Classification | [ResNet50-Quadruplet](https://gitee.com/mindspore/models/tree/master/research/cv/metric_learn) |✅| ✅ | | -| Image | Image Classification | [ResNet50-Triplet](https://gitee.com/mindspore/models/tree/master/research/cv/metric_learn) |✅| ✅ | | -| Image | Image Classification | [ResnetV2_101](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | -| Image | Image Classification | [ResnetV2_152](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | -| Image | Image Classification | [ResnetV2_50](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | -| Image | Image Classification | [resnetv2_50_frn](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2_50_frn) |✅| ✅ | | -| Image | Image Classification | [resnext152_64x4d](https://gitee.com/mindspore/models/tree/master/research/cv/resnext152_64x4d) |✅| ✅ | | -| Image | Object Detection | [retinaface_mobilenet0.25](https://gitee.com/mindspore/models/tree/master/research/cv/retinaface) |✅| ✅ | | -| Image | Object Detection | [retinanet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet101) |✅| ✅ | | -| Image | Object Detection | [retinanet_resnet152](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet152) |✅| ✅ | | -| Image | Object Detection | [rfcn](https://gitee.com/mindspore/models/tree/master/research/cv/rfcn) | | ✅ | | -| Image | Image Classification | [SE_ResNeXt50](https://gitee.com/mindspore/models/tree/master/research/cv/SE_ResNeXt50) |✅| | | -| Image | Image Classification | [senet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net) |✅| ✅ | ✅ | -| Image | Image Classification | [senet_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net) |✅| ✅ | ✅ | -| Image | Image Classification | [se-res2net50](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| Image | Image Classification | [S-GhostNet](https://gitee.com/mindspore/models/tree/master/research/cv/S-GhostNet) |✅| | | -| Image | Pose Estimation | [simple_baselines](https://gitee.com/mindspore/models/tree/master/research/cv/simple_baselines) |✅| ✅ | | -| Image | Image Generation | [SinGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SinGAN) |✅| | | -| Image | Image Classification | [single_path_nas](https://gitee.com/mindspore/models/tree/master/research/cv/single_path_nas) |✅| ✅ | | -| Image | Image Classification | [sknet](https://gitee.com/mindspore/models/tree/master/research/cv/sknet) |✅| ✅ | ✅ | -| Image | Image Classification | [snn_mlp](https://gitee.com/mindspore/models/tree/master/research/cv/snn_mlp) | | ✅ | | -| Image | Object Detection | [Spnas](https://gitee.com/mindspore/models/tree/master/research/cv/Spnas) |✅| | | -| Image | Image Classification | [SPPNet](https://gitee.com/mindspore/models/tree/master/research/cv/SPPNet) |✅| ✅ | | -| Image | Image Classification | [squeezenet](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | -| Image | Image Super Resolution | [sr_ea](https://gitee.com/mindspore/models/tree/master/research/cv/sr_ea) |✅| | | -| Image | Image Super Resolution | [SRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SRGAN) |✅| ✅ | | -| Image | Image Classification | [ssc_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/ssc_resnet50) |✅| ✅ | | -| Image | Object Detection | [ssd_ghostnet](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_ghostnet) |✅| ✅ | ✅ | -| Image | Object Detection | [ssd_inception_v2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_inception_v2) | | ✅ | ✅ | -| Image | Object Detection | [ssd_inceptionv2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_inceptionv2) |✅| | | -| Image | Object Detection | [ssd_mobilenetV2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2) |✅| ✅ | ✅ | -| Image | Object Detection | [ssd_mobilenetV2_FPNlite](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2_FPNlite) |✅| ✅ | ✅ | -| Image | Object Detection | [ssd_resnet_34](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet_34) | | ✅ | | -| Image | Object Detection | [ssd_resnet34](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet34) |✅| | ✅ | -| Image | Object Detection | [ssd_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet50) |✅| | | -| Image | Pose Estimation | [StackedHourglass](https://gitee.com/mindspore/models/tree/master/research/cv/StackedHourglass) |✅| | | -| Image | Image Generation | [StarGAN](https://gitee.com/mindspore/models/tree/master/research/cv/StarGAN) |✅| ✅ | | -| Image | Image Generation | [STGAN](https://gitee.com/mindspore/models/tree/master/research/cv/STGAN) |✅| ✅ | | -| Image | Traffic Prediction | [stgcn](https://gitee.com/mindspore/models/tree/master/research/cv/stgcn) |✅| ✅ | | -| Image | Image Classification | [stpm](https://gitee.com/mindspore/models/tree/master/official/cv/STPM) |✅| ✅ | | -| Image | Image Classification | [swin_transformer](https://gitee.com/mindspore/models/tree/master/official/cv/SwinTransformer) |✅| ✅ | | -| Image | Temporal Localization | [tall](https://gitee.com/mindspore/models/tree/master/research/cv/tall) |✅| | | -| Image | Image Classification | [TCN](https://gitee.com/mindspore/models/tree/master/research/cv/TCN) |✅| ✅ | | -| Image | Scene Text Detection | [textfusenet](https://gitee.com/mindspore/models/tree/master/research/cv/textfusenet) |✅| | | -| Image | Traffic Prediction | [tgcn](https://gitee.com/mindspore/models/tree/master/research/cv/tgcn) |✅| ✅ | | -| Image | Image Classification | [tinynet](https://gitee.com/mindspore/models/tree/master/research/cv/tinynet) | | ✅ | | -| Image | Image Classification | [TNT](https://gitee.com/mindspore/models/tree/master/research/cv/TNT) |✅| ✅ | | -| Image | Object Detection | [u2net](https://gitee.com/mindspore/models/tree/master/research/cv/u2net) |✅| ✅ | | -| Image | Image Generation | [U-GAT-IT](https://gitee.com/mindspore/models/tree/master/research/cv/U-GAT-IT) |✅| ✅ | | -| Image | Semantic Segmentation | [UNet3+](https://gitee.com/mindspore/models/tree/master/research/cv/UNet3+) |✅| ✅ | | -| Image | Re-Identification | [VehicleNet](https://gitee.com/mindspore/models/tree/master/research/cv/VehicleNet) |✅| | | -| Image | Image Classification | [vgg19](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/vgg19) |✅| ✅ | | -| Image | Image Classification | [ViG](https://gitee.com/mindspore/models/tree/master/research/cv/ViG) |✅| ✅ | | -| Image | Image Classification | [vit_cifar](https://gitee.com/mindspore/models/tree/master/research/cv/vit_base) |✅| ✅ | | -| Image | Semantic Segmentation | [vnet](https://gitee.com/mindspore/models/tree/master/research/cv/vnet) |✅| ✅ | | -| Image | Image Classification | [wave_mlp](https://gitee.com/mindspore/models/tree/master/research/cv/wave_mlp) |✅| ✅ | | -| Image | Image Super Resolution | [wdsr](https://gitee.com/mindspore/models/tree/master/research/cv/wdsr) |✅| ✅ | | -| Image | Image Generation | [wgan](https://gitee.com/mindspore/models/tree/master/official/cv/WGAN) |✅| | | -| Image | Image Classification | [wideresnet](https://gitee.com/mindspore/models/tree/master/research/cv/wideresnet) |✅| ✅ | | -| Image | Instance Segmentation | [Yolact++](https://gitee.com/mindspore/models/tree/master/research/cv/Yolact++) |✅| | | -| Image | Object Detection | [yolov3_tiny](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_tiny) |✅| ✅ | | -| Image | Object Detection | [yolox](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOX) |✅| | | -| Multi Modal | Multi Modal | [opt](https://gitee.com/mindspore/models/tree/master/research/mm/opt) |✅| ✅ | | -| Multi Modal | Multi Modal | [TokenFusion](https://gitee.com/mindspore/models/tree/master/research/cv/TokenFusion) |✅| ✅ | | -| Multi Modal | Multi Modal | [wukong](https://gitee.com/mindspore/models/tree/master/research/mm/wukong) |✅| | | -| Recommendation | Click-Through Rate Prediction | [autodis](https://gitee.com/mindspore/models/tree/master/research/recommend/autodis) |✅| ✅ | | -| Recommendation | Click-Through Rate Prediction | [DIEN](https://gitee.com/mindspore/models/tree/master/research/recommend/DIEN) |✅| ✅ | | -| Recommendation | Click-Through Rate Prediction | [dlrm](https://gitee.com/mindspore/models/tree/master/research/recommend/dlrm) |✅| ✅ | | -| Recommendation | Click-Through Rate Prediction | [EDCN](https://gitee.com/mindspore/models/tree/master/research/recommend/EDCN) |✅| ✅ | | -| Recommendation | Click-Through Rate Prediction | [Fat-DeepFFM](https://gitee.com/mindspore/models/tree/master/research/recommend/Fat-DeepFFM) |✅| ✅ | | -| Recommendation | Click-Through Rate Prediction | [mmoe](https://gitee.com/mindspore/models/tree/master/research/recommend/mmoe) |✅| ✅ | | -| Text | Natural Language Understanding | [albert](https://gitee.com/mindspore/models/tree/master/research/nlp/albert) |✅| ✅ | | -| Text | Emotion Classification | [atae_lstm](https://gitee.com/mindspore/models/tree/master/research/nlp/atae_lstm) |✅| ✅ | | -| Text | Dialogue | [dam](https://gitee.com/mindspore/models/tree/master/research/nlp/dam) |✅| | | -| Text | Language Model | [gpt2](https://gitee.com/mindspore/models/tree/master/research/nlp/gpt2) |✅| | | -| Text | Knowledge Graph Embedding | [hake](https://gitee.com/mindspore/models/tree/master/research/nlp/hake) | | ✅ | | -| Text | Natural Language Understanding | [ktnet](https://gitee.com/mindspore/models/tree/master/research/nlp/ktnet) |✅| ✅ | | -| Text | Named Entity Recognition | [lstm_crf](https://gitee.com/mindspore/models/tree/master/research/nlp/lstm_crf) |✅| | | -| Text | Natural Language Understanding | [luke](https://gitee.com/mindspore/models/tree/master/research/nlp/luke) |✅| ✅ | | -| Text | Knowledge Graph Embedding | [rotate](https://gitee.com/mindspore/models/tree/master/research/nlp/rotate) |✅| ✅ | | -| Text | Emotion Classification | [senta](https://gitee.com/mindspore/models/tree/master/research/nlp/senta) |✅| ✅ | | -| Text | Machine Translation | [seq2seq](https://gitee.com/mindspore/models/tree/master/research/nlp/seq2seq) |✅| | | -| Text | Word Embedding | [skipgram](https://gitee.com/mindspore/models/tree/master/research/nlp/skipgram) |✅| ✅ | | -| Text | Machine Translation | [speech_transformer](https://gitee.com/mindspore/models/tree/master/research/nlp/speech_transformer) |✅| | | -| Text | Pre Training | [ternarybert](https://gitee.com/mindspore/models/tree/master/research/nlp/ternarybert) |✅| ✅ | | -| Text | Natural Language Understanding | [tprr](https://gitee.com/mindspore/models/tree/master/research/nlp/tprr) |✅| | | -| Text | Natural Language Understanding | [transformer_xl](https://gitee.com/mindspore/models/tree/master/research/nlp/transformer_xl) |✅| ✅ | | -| Text | Knowledge Graph Embedding | [transX](https://gitee.com/mindspore/models/tree/master/research/nlp/transX) | | ✅ | | -| Video | Video Classification | [AttentionCluster](https://gitee.com/mindspore/models/tree/master/research/cv/AttentionCluster) |✅| ✅ | | -| Video | Others | [DYR](https://gitee.com/mindspore/models/tree/master/research/nlp/DYR) |✅| | | -| Video | Video Classification | [ecolite](https://gitee.com/mindspore/models/tree/master/research/cv/ecolite) |✅| | | -| Video | Object Tracking | [fairmot](https://gitee.com/mindspore/models/tree/master/research/cv/fairmot) |✅| ✅ | | -| Video | Video Classification | [I3D](https://gitee.com/mindspore/models/tree/master/research/cv/I3D) |✅| | | -| Video | Object Tracking | [JDE](https://gitee.com/mindspore/models/tree/master/research/cv/JDE) | | ✅ | | -| Video | video Segment | [OSVOS](https://gitee.com/mindspore/models/tree/master/research/cv/OSVOS) | | ✅ | | -| Video | Video Classification | [r2plus1d](https://gitee.com/mindspore/models/tree/master/research/cv/r2plus1d) |✅| ✅ | | -| Video | video Super Resolution | [rbpn](https://gitee.com/mindspore/models/tree/master/research/cv/rbpn) |✅| | | -| Video | Video Classification | [resnet3d](https://gitee.com/mindspore/models/tree/master/research/cv/resnet3d) |✅| | | -| Video | Object Tracking | [SiamFC](https://gitee.com/mindspore/models/tree/master/research/cv/SiamFC) |✅| | | -| Video | Object Tracking | [siamRPN](https://gitee.com/mindspore/models/tree/master/research/cv/siamRPN) |✅| ✅ | | -| Video | Video Classification | [slowfast](https://gitee.com/mindspore/models/tree/master/research/cv/slowfast) |✅| ✅ | | -| Video | Video Classification | [stnet](https://gitee.com/mindspore/models/tree/master/research/cv/stnet) |✅| | | -| Video | Object Tracking | [tracktor](https://gitee.com/mindspore/models/tree/master/research/cv/tracktor) | | ✅ | | -| Video | Object Tracking | [tracktor++](https://gitee.com/mindspore/models/tree/master/research/cv/tracktor++) |✅| ✅ | | -| Video | Video Classification | [trn](https://gitee.com/mindspore/models/tree/master/research/cv/trn) | | ✅ | | -| Video | Video Classification | [tsm](https://gitee.com/mindspore/models/tree/master/research/cv/tsm) |✅| ✅ | | -| Video | Video Classification | [tsn](https://gitee.com/mindspore/models/tree/master/research/cv/tsn) |✅| ✅ | | - -- [Community](https://gitee.com/mindspore/models/tree/master/community) - -## Announcements - -### 2021.9.15 Set up repository `models` - -`models` comes from the directory `model_zoo` of repository [mindspore](https://gitee.com/mindspore/mindspore). This new repository doesn't contain any history of commits about the directory `model_zoo` in `mindspore`, you could refer to the repository `mindspore` for the past commits. - -## Related Website - -Here is the ModelZoo for MindSpore which support different devices including Ascend, GPU, CPU and mobile. - -If you are looking for exclusive models only for Ascend using different ML platform, you could refer to [Ascend ModelZoo](https://hiascend.com/software/modelzoo) and corresponding [gitee repository](https://gitee.com/ascend/modelzoo) - -If you are looking for some pretrained checkpoint of mindspore, you could refer to [MindSpore Hub](https://www.mindspore.cn/resources/hub/en) or [Download Website](https://download.mindspore.cn/model_zoo/). - -## Disclaimers - -Mindspore only provides scripts that downloads and preprocesses public datasets. We do not own these datasets and are not responsible for their quality or maintenance. Please make sure you have permission to use the dataset under the dataset’s license. The models trained on these dataset are for non-commercial research and educational purpose only. - -To dataset owners: we will remove or update all public content upon request if you don’t want your dataset included on Mindspore, or wish to update it in any way. Please contact us through a Github/Gitee issue. Your understanding and contribution to this community is greatly appreciated. - -MindSpore is Apache 2.0 licensed. Please see the LICENSE file. - -## License - -[Apache License 2.0](https://gitee.com/mindspore/mindspore/blob/master/LICENSE) +| 3D | 三维重建 | [cmr](https://gitee.com/mindspore/models/tree/master/research/cv/cmr) | | ✅ | | +| 3D | 三维重建 | [DecoMR](https://gitee.com/mindspore/models/tree/master/research/cv/DecoMR) | | ✅ | | +| 3D | 三维重建 | [DeepLM](https://gitee.com/mindspore/models/tree/master/research/3d/DeepLM) | | ✅ | | +| 3D | 三维重建 | [eppmvsnet](https://gitee.com/mindspore/models/tree/master/research/cv/eppmvsnet) | | ✅ | | +| 3D | 三维物体检测 | [pointpillars](https://gitee.com/mindspore/models/tree/master/research/cv/pointpillars) |✅| ✅ | | +| 语音 | 语音识别 | [ctcmodel](https://gitee.com/mindspore/models/tree/master/research/audio/ctcmodel) |✅| | | +| 语音 | 语音识别 | [deepspeech2](https://gitee.com/mindspore/models/tree/master/official/audio/DeepSpeech2) | | ✅ | | +| 语音 | 语音唤醒 | [dscnn](https://gitee.com/mindspore/models/tree/master/research/audio/dscnn) |✅| ✅ | | +| 语音 | 语音合成 | [FastSpeech](https://gitee.com/mindspore/models/tree/master/research/audio/FastSpeech) | | ✅ | | +| 语音 | 语音标注 | [fcn-4](https://gitee.com/mindspore/models/tree/master/research/audio/fcn-4) |✅| ✅ | | +| 语音 | 语音识别 | [jasper](https://gitee.com/mindspore/models/tree/master/research/audio/jasper) |✅| ✅ | | +| 语音 | 语音合成 | [wavenet](https://gitee.com/mindspore/models/tree/master/research/audio/wavenet) |✅| ✅ | | +| 图神经网络 | 图分类 | [dgcn](https://gitee.com/mindspore/models/tree/master/research/gnn/dgcn) |✅| | | +| 图神经网络 | 文本分类 | [hypertext](https://gitee.com/mindspore/models/tree/master/research/nlp/hypertext) |✅| ✅ | | +| 图神经网络 | 图分类 | [sdne](https://gitee.com/mindspore/models/tree/master/research/gnn/sdne) |✅| | | +| 图神经网络 | 社会和信息网络 | [sgcn](https://gitee.com/mindspore/models/tree/master/research/gnn/sgcn) |✅| ✅ | | +| 图神经网络 | 文本分类 | [textrcnn](https://gitee.com/mindspore/models/tree/master/research/nlp/textrcnn) |✅| ✅ | | +| 高性能计算 | 高性能计算 | [deepbsde](https://gitee.com/mindspore/models/tree/master/research/hpc/deepbsde) | | ✅ | | +| 高性能计算 | 高性能计算 | [molecular_dynamics](https://gitee.com/mindspore/models/tree/master/research/hpc/molecular_dynamics) |✅| | | +| 高性能计算 | 高性能计算 | [ocean_model](https://gitee.com/mindspore/models/tree/master/research/hpc/ocean_model) | | ✅ | | +| 高性能计算 | 高性能计算 | [pafnucy](https://gitee.com/mindspore/models/tree/master/research/hpc/pafnucy) |✅| ✅ | | +| 高性能计算 | 高性能计算 | [pfnn](https://gitee.com/mindspore/models/tree/master/research/hpc/pfnn) | | ✅ | | +| 高性能计算 | 高性能计算 | [pinns](https://gitee.com/mindspore/models/tree/master/research/hpc/pinns) | | ✅ | | +| 图像 | 图像分类 | [3D_DenseNet](https://gitee.com/mindspore/models/tree/master/research/cv/3D_DenseNet) |✅| ✅ | | +| 图像 | 语义分割 | [3dcnn](https://gitee.com/mindspore/models/tree/master/research/cv/3dcnn) |✅| ✅ | | +| 图像 | 语义分割 | [adelaide_ea](https://gitee.com/mindspore/models/tree/master/research/cv/adelaide_ea) |✅| | | +| 图像 | 文本检测 | [advanced_east](https://gitee.com/mindspore/models/tree/master/research/cv/advanced_east) |✅| ✅ | | +| 图像 | 风格转移 | [aecrnet](https://gitee.com/mindspore/models/tree/master/research/cv/aecrnet) |✅| ✅ | | +| 图像 | 重新识别 | [AlignedReID](https://gitee.com/mindspore/models/tree/master/research/cv/AlignedReID) | | ✅ | | +| 图像 | 重新识别 | [AlignedReID++](https://gitee.com/mindspore/models/tree/master/research/cv/AlignedReID++) |✅| ✅ | | +| 图像 | 姿态估计 | [AlphaPose](https://gitee.com/mindspore/models/tree/master/research/cv/AlphaPose) |✅| | | +| 图像 | 风格转移 | [APDrawingGAN](https://gitee.com/mindspore/models/tree/master/research/cv/APDrawingGAN) |✅| ✅ | | +| 图像 | 风格转移 | [ArbitraryStyleTransfer](https://gitee.com/mindspore/models/tree/master/research/cv/ArbitraryStyleTransfer) |✅| ✅ | | +| 图像 | 目标检测 | [arcface](https://gitee.com/mindspore/models/tree/master/official/cv/Arcface) |✅| ✅ | | +| 图像 | 关键点检测 | [ArtTrack](https://gitee.com/mindspore/models/tree/master/research/cv/ArtTrack) | | ✅ | | +| 图像 | 风格转移 | [AttGAN](https://gitee.com/mindspore/models/tree/master/research/cv/AttGAN) |✅| ✅ | | +| 图像 | 图像分类 | [augvit](https://gitee.com/mindspore/models/tree/master/research/cv/augvit) | | ✅ | | +| 图像 | 图像分类 | [autoaugment](https://gitee.com/mindspore/models/tree/master/research/cv/autoaugment) |✅| ✅ | | +| 图像 | 语义分割 | [Auto-DeepLab](https://gitee.com/mindspore/models/tree/master/research/cv/Auto-DeepLab) |✅| | | +| 图像 | 神经架构搜索 | [AutoSlim](https://gitee.com/mindspore/models/tree/master/research/cv/AutoSlim) |✅| ✅ | | +| 图像 | 图像分类 | [AVA_cifar](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_cifar) |✅| ✅ | | +| 图像 | 图像分类 | [AVA_hpa](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_hpa) |✅| ✅ | | +| 图像 | 图像分类 | [cait](https://gitee.com/mindspore/models/tree/master/research/cv/cait) |✅| ✅ | | +| 图像 | 目标检测 | [CascadeRCNN](https://gitee.com/mindspore/models/tree/master/research/cv/CascadeRCNN) |✅| ✅ | | +| 图像 | 图像分类 | [CBAM](https://gitee.com/mindspore/models/tree/master/research/cv/CBAM) |✅| | | +| 图像 | 图像分类 | [cct](https://gitee.com/mindspore/models/tree/master/research/cv/cct) |✅| ✅ | | +| 图像 | 关键点检测 | [centernet](https://gitee.com/mindspore/models/tree/master/research/cv/centernet) |✅| | ✅ | +| 图像 | 关键点检测 | [centernet_det](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_det) |✅| | | +| 图像 | 关键点检测 | [centernet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet101) |✅| ✅ | | +| 图像 | 关键点检测 | [centernet_resnet50_v1](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet50_v1) |✅| | | +| 图像 | 图像生成 | [CGAN](https://gitee.com/mindspore/models/tree/master/research/cv/CGAN) |✅| ✅ | | +| 图像 | 图像分类 | [convnext](https://gitee.com/mindspore/models/tree/master/research/cv/convnext) |✅| ✅ | | +| 图像 | 图像超分 | [csd](https://gitee.com/mindspore/models/tree/master/research/cv/csd) |✅| ✅ | | +| 图像 | 图像生成 | [CTSDG](https://gitee.com/mindspore/models/tree/master/research/cv/CTSDG) | | ✅ | | +| 图像 | 风格转移 | [CycleGAN](https://gitee.com/mindspore/models/tree/master/official/cv/CycleGAN) |✅| ✅ | | +| 图像 | 图像超分 | [DBPN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) |✅| | | +| 图像 | 图像超分 | [DBPN_GAN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) |✅| | | +| 图像 | 图像生成 | [dcgan](https://gitee.com/mindspore/models/tree/master/research/cv/dcgan) |✅| ✅ | | +| 图像 | 重新识别 | [DDAG](https://gitee.com/mindspore/models/tree/master/research/cv/DDAG) |✅| ✅ | | +| 图像 | 语义分割 | [DDM](https://gitee.com/mindspore/models/tree/master/research/cv/DDM) |✅| | | +| 图像 | 语义分割 | [DDRNet](https://gitee.com/mindspore/models/tree/master/research/cv/DDRNet) |✅| ✅ | | +| 图像 | 目标检测 | [DeepID](https://gitee.com/mindspore/models/tree/master/research/cv/DeepID) |✅| ✅ | | +| 图像 | 语义分割 | [deeplabv3plus](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabV3P) |✅| ✅ | | +| 图像 | 图像检索 | [delf](https://gitee.com/mindspore/models/tree/master/research/cv/delf) |✅| | | +| 图像 | 零样本学习 | [dem](https://gitee.com/mindspore/models/tree/master/research/cv/dem) |✅| ✅ | | +| 图像 | 目标检测 | [detr](https://gitee.com/mindspore/models/tree/master/research/cv/detr) |✅| ✅ | | +| 图像 | 语义分割 | [dgcnet_res101](https://gitee.com/mindspore/models/tree/master/research/cv/dgcnet_res101) | | ✅ | | +| 图像 | 实例分割 | [dlinknet](https://gitee.com/mindspore/models/tree/master/research/cv/dlinknet) |✅| | | +| 图像 | 图像去噪 | [DnCNN](https://gitee.com/mindspore/models/tree/master/research/cv/DnCNN) |✅| | | +| 图像 | 图像分类 | [dnet_nas](https://gitee.com/mindspore/models/tree/master/research/cv/dnet_nas) |✅| | | +| 图像 | 图像分类 | [DRNet](https://gitee.com/mindspore/models/tree/master/research/cv/DRNet) |✅| ✅ | | +| 图像 | 图像超分 | [EDSR](https://gitee.com/mindspore/models/tree/master/official/cv/EDSR) |✅| | | +| 图像 | 目标检测 | [EfficientDet_d0](https://gitee.com/mindspore/models/tree/master/research/cv/EfficientDet_d0) |✅| | | +| 图像 | 图像分类 | [efficientnet-b0](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b0) |✅| | | +| 图像 | 图像分类 | [efficientnet-b1](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnet-b1) |✅| | | +| 图像 | 图像分类 | [efficientnet-b2](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnet-b2) |✅| ✅ | | +| 图像 | 图像分类 | [efficientnet-b3](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnet-b3) |✅| ✅ | | +| 图像 | 图像分类 | [efficientnetv2](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnetv2) |✅| | | +| 图像 | 显著性检测 | [EGnet](https://gitee.com/mindspore/models/tree/master/research/cv/EGnet) |✅| ✅ | | +| 图像 | 语义分割 | [E-NET](https://gitee.com/mindspore/models/tree/master/research/cv/E-NET) |✅| ✅ | | +| 图像 | 图像超分 | [esr_ea](https://gitee.com/mindspore/models/tree/master/research/cv/esr_ea) |✅| ✅ | | +| 图像 | 图像超分 | [ESRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/ESRGAN) |✅| ✅ | | +| 图像 | 图像分类 | [FaceAttribute](https://gitee.com/mindspore/models/tree/master/research/cv/FaceAttribute) |✅| ✅ | | +| 图像 | 目标检测 | [faceboxes](https://gitee.com/mindspore/models/tree/master/research/cv/faceboxes) |✅| | | +| 图像 | 目标检测 | [FaceDetection](https://gitee.com/mindspore/models/tree/master/research/cv/FaceDetection) |✅| ✅ | | +| 图像 | 人脸识别 | [FaceNet](https://gitee.com/mindspore/models/tree/master/research/cv/FaceNet) |✅| ✅ | | +| 图像 | 图像分类 | [FaceQualityAssessment](https://gitee.com/mindspore/models/tree/master/research/cv/FaceQualityAssessment) |✅| ✅ | ✅ | +| 图像 | 目标检测 | [FaceRecognition](https://gitee.com/mindspore/models/tree/master/official/cv/FaceRecognition) |✅| ✅ | | +| 图像 | 目标检测 | [FaceRecognitionForTracking](https://gitee.com/mindspore/models/tree/master/research/cv/FaceRecognitionForTracking) |✅| | ✅ | +| 图像 | 目标检测 | [faster_rcnn_dcn](https://gitee.com/mindspore/models/tree/master/research/cv/faster_rcnn_dcn) |✅| ✅ | | +| 图像 | 图像抠图 | [FCANet](https://gitee.com/mindspore/models/tree/master/research/cv/FCANet) |✅| | | +| 图像 | 图像分类 | [FDA-BNN](https://gitee.com/mindspore/models/tree/master/research/cv/FDA-BNN) |✅| ✅ | | +| 图像 | 图像分类 | [fishnet99](https://gitee.com/mindspore/models/tree/master/research/cv/fishnet99) |✅| ✅ | | +| 图像 | 光流估计 | [flownet2](https://gitee.com/mindspore/models/tree/master/research/cv/flownet2) |✅| | | +| 图像 | 图像生成 | [gan](https://gitee.com/mindspore/models/tree/master/research/cv/gan) |✅| ✅ | | +| 图像 | 图像分类 | [GENet_Res50](https://gitee.com/mindspore/models/tree/master/research/cv/GENet_Res50) |✅| | | +| 图像 | 图像分类 | [ghostnet](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet) |✅| | | +| 图像 | 图像分类 | [ghostnet_d](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet_d) |✅| ✅ | | +| 图像 | 图像分类 | [glore_res200](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) |✅| ✅ | | +| 图像 | 图像分类 | [glore_res50](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) |✅| ✅ | | +| 图像 | 图像分类 | [hardnet](https://gitee.com/mindspore/models/tree/master/research/cv/hardnet) |✅| ✅ | | +| 图像 | 边缘检测 | [hed](https://gitee.com/mindspore/models/tree/master/research/cv/hed) |✅| ✅ | | +| 图像 | 图像生成 | [HiFaceGAN](https://gitee.com/mindspore/models/tree/master/research/cv/HiFaceGAN) | | ✅ | | +| 图像 | 图像分类 | [HourNAS](https://gitee.com/mindspore/models/tree/master/research/cv/HourNAS) | | ✅ | | +| 图像 | 图像分类 | [HRNetW48_cls](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_cls) |✅| ✅ | | +| 图像 | 语义分割 | [HRNetW48_seg](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_seg) |✅| | | +| 图像 | 图像分类 | [ibnnet](https://gitee.com/mindspore/models/tree/master/research/cv/ibnnet) |✅| ✅ | | +| 图像 | 语义分割 | [ICNet](https://gitee.com/mindspore/models/tree/master/research/cv/ICNet) |✅| | | +| 图像 | 图像分类 | [inception_resnet_v2](https://gitee.com/mindspore/models/tree/master/research/cv/inception_resnet_v2) |✅| ✅ | | +| 图像 | 图像分类 | [Inceptionv2](https://gitee.com/mindspore/models/tree/master/research/cv/Inception-v2) |✅| ✅ | | +| 图像 | 图像抠图 | [IndexNet](https://gitee.com/mindspore/models/tree/master/research/cv/IndexNet) | | ✅ | | +| 图像 | 图像生成 | [IPT](https://gitee.com/mindspore/models/tree/master/research/cv/IPT) |✅| | | +| 图像 | 图像超分 | [IRN](https://gitee.com/mindspore/models/tree/master/research/cv/IRN) |✅| ✅ | | +| 图像 | 图像分类 | [ISyNet](https://gitee.com/mindspore/models/tree/master/research/cv/ISyNet) |✅| ✅ | | +| 图像 | 图像分类 | [ivpf](https://gitee.com/mindspore/models/tree/master/research/cv/ivpf) | | ✅ | | +| 图像 | 图像去噪 | [LearningToSeeInTheDark](https://gitee.com/mindspore/models/tree/master/research/cv/LearningToSeeInTheDark) |✅| | | +| 图像 | 元学习 | [LEO](https://gitee.com/mindspore/models/tree/master/research/cv/LEO) |✅| ✅ | | +| 图像 | 目标检测 | [LightCNN](https://gitee.com/mindspore/models/tree/master/research/cv/LightCNN) |✅| ✅ | ✅ | +| 图像 | 图像超分 | [lite-hrnet](https://gitee.com/mindspore/models/tree/master/research/cv/lite-hrnet) | | ✅ | | +| 图像 | 图像分类 | [lresnet100e_ir](https://gitee.com/mindspore/models/tree/master/research/cv/lresnet100e_ir) | | ✅ | | +| 图像 | 目标检测 | [m2det](https://gitee.com/mindspore/models/tree/master/research/cv/m2det) | | ✅ | | +| 图像 | 自编码 | [mae](https://gitee.com/mindspore/models/tree/master/official/cv/MAE) |✅| ✅ | | +| 图像 | 元学习 | [MAML](https://gitee.com/mindspore/models/tree/master/research/cv/MAML) |✅| ✅ | | +| 图像 | 文本识别 | [ManiDP](https://gitee.com/mindspore/models/tree/master/research/cv/ManiDP) | | ✅ | | +| 图像 | 人脸识别 | [MaskedFaceRecognition](https://gitee.com/mindspore/models/tree/master/research/cv/MaskedFaceRecognition) |✅| | | +| 图像 | 元学习 | [meta-baseline](https://gitee.com/mindspore/models/tree/master/research/cv/meta-baseline) |✅| ✅ | | +| 图像 | 重新识别 | [MGN](https://gitee.com/mindspore/models/tree/master/research/cv/MGN) |✅| ✅ | | +| 图像 | 深度估计 | [midas](https://gitee.com/mindspore/models/tree/master/research/cv/midas) |✅| ✅ | | +| 图像 | 图像去噪 | [MIMO-UNet](https://gitee.com/mindspore/models/tree/master/research/cv/MIMO-UNet) | | ✅ | | +| 图像 | 图像分类 | [mnasnet](https://gitee.com/mindspore/models/tree/master/research/cv/mnasnet) |✅| ✅ | | +| 图像 | 图像分类 | [mobilenetv3_large](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetv3_large) |✅| | ✅ | +| 图像 | 图像分类 | [mobilenetV3_small_x1_0](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetV3_small_x1_0) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [MultiTaskNet](https://gitee.com/mindspore/models/tree/master/research/cv/PAMTRI/MultiTaskNet) |✅| ✅ | | +| 图像 | 重新识别 | [MVD](https://gitee.com/mindspore/models/tree/master/research/cv/MVD) |✅| ✅ | | +| 图像 | 目标检测 | [nas-fpn](https://gitee.com/mindspore/models/tree/master/research/cv/nas-fpn) |✅| | | +| 图像 | 图像去噪 | [Neighbor2Neighbor](https://gitee.com/mindspore/models/tree/master/research/cv/Neighbor2Neighbor) |✅| ✅ | | +| 图像 | 图像分类 | [NFNet](https://gitee.com/mindspore/models/tree/master/research/cv/NFNet) |✅| ✅ | | +| 图像 | 图像质量评估 | [nima_vgg16](https://gitee.com/mindspore/models/tree/master/research/cv/nima_vgg16) | | ✅ | | +| 图像 | 语义分割 | [nnUNet](https://gitee.com/mindspore/models/tree/master/research/cv/nnUNet) |✅| ✅ | | +| 图像 | 图像分类 | [ntsnet](https://gitee.com/mindspore/models/tree/master/research/cv/ntsnet) |✅| ✅ | | +| 图像 | 语义分割 | [OCRNet](https://gitee.com/mindspore/models/tree/master/official/cv/OCRNet) |✅| ✅ | | +| 图像 | 重新识别 | [osnet](https://gitee.com/mindspore/models/tree/master/research/cv/osnet) |✅| ✅ | | +| 图像 | 显著性检测 | [PAGENet](https://gitee.com/mindspore/models/tree/master/research/cv/PAGENet) |✅| ✅ | | +| 图像 | 图像检索 | [pcb](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | +| 图像 | 图像检索 | [pcb](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | +| 图像 | 图像检索 | [pcb_rpp](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | +| 图像 | 图像分类 | [PDarts](https://gitee.com/mindspore/models/tree/master/research/cv/PDarts) |✅| ✅ | | +| 图像 | 图像生成 | [PGAN](https://gitee.com/mindspore/models/tree/master/research/cv/PGAN) |✅| ✅ | | +| 图像 | 图像生成 | [Pix2Pix](https://gitee.com/mindspore/models/tree/master/research/cv/Pix2Pix) |✅| ✅ | | +| 图像 | 图像超分 | [Pix2PixHD](https://gitee.com/mindspore/models/tree/master/official/cv/Pix2PixHD) |✅| | | +| 图像 | 图像分类 | [pnasnet](https://gitee.com/mindspore/models/tree/master/research/cv/pnasnet) |✅| ✅ | | +| 图像 | 点云模型 | [pointnet](https://gitee.com/mindspore/models/tree/master/official/cv/PointNet) |✅| ✅ | | +| 图像 | 点云模型 | [pointnet2](https://gitee.com/mindspore/models/tree/master/official/cv/PointNet2) |✅| ✅ | | +| 图像 | 图像分类 | [PoseEstNet](https://gitee.com/mindspore/models/tree/master/research/cv/PAMTRI/PoseEstNet) |✅| ✅ | | +| 图像 | 图像分类 | [ProtoNet](https://gitee.com/mindspore/models/tree/master/research/cv/ProtoNet) |✅| ✅ | | +| 图像 | 图像分类 | [proxylessnas](https://gitee.com/mindspore/models/tree/master/research/cv/proxylessnas) |✅| ✅ | | +| 图像 | 语义分割 | [PSPNet](https://gitee.com/mindspore/models/tree/master/research/cv/PSPNet) |✅| | | +| 图像 | 显著性检测 | [ras](https://gitee.com/mindspore/models/tree/master/research/cv/ras) |✅| ✅ | | +| 图像 | 图像超分 | [RCAN](https://gitee.com/mindspore/models/tree/master/research/cv/RCAN) |✅| | | +| 图像 | 目标检测 | [rcnn](https://gitee.com/mindspore/models/tree/master/research/cv/rcnn) |✅| ✅ | | +| 图像 | 图像超分 | [REDNet30](https://gitee.com/mindspore/models/tree/master/research/cv/REDNet30) |✅| ✅ | | +| 图像 | 目标检测 | [RefineDet](https://gitee.com/mindspore/models/tree/master/research/cv/RefineDet) |✅| ✅ | | +| 图像 | 语义分割 | [RefineNet](https://gitee.com/mindspore/models/tree/master/research/cv/RefineNet) |✅| ✅ | | +| 图像 | 重新识别 | [ReIDStrongBaseline](https://gitee.com/mindspore/models/tree/master/research/cv/ReIDStrongBaseline) |✅| ✅ | | +| 图像 | 图像分类 | [relationnet](https://gitee.com/mindspore/models/tree/master/research/cv/relationnet) |✅| ✅ | | +| 图像 | 图像分类 | [renas](https://gitee.com/mindspore/models/tree/master/research/cv/renas) |✅| ✅ | ✅ | +| 图像 | 语义分割 | [repvgg](https://gitee.com/mindspore/models/tree/master/research/cv/repvgg) |✅| ✅ | | +| 图像 | 语义分割 | [res2net_deeplabv3](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_deeplabv3) |✅| | ✅ | +| 图像 | 目标检测 | [res2net_faster_rcnn](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_faster_rcnn) |✅| ✅ | | +| 图像 | 目标检测 | [res2net_yolov3](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_yolov3) |✅| ✅ | | +| 图像 | 图像分类 | [res2net101](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | +| 图像 | 图像分类 | [res2net152](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | +| 图像 | 图像分类 | [res2net50](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | +| 图像 | 图像分类 | [ResNeSt50](https://gitee.com/mindspore/models/tree/master/research/cv/ResNeSt50) |✅| ✅ | | +| 图像 | 图像分类 | [resnet50_adv_pruning](https://gitee.com/mindspore/models/tree/master/research/cv/resnet50_adv_pruning) |✅| ✅ | | +| 图像 | 图像分类 | [resnet50_bam](https://gitee.com/mindspore/models/tree/master/research/cv/resnet50_bam) |✅| ✅ | | +| 图像 | 图像分类 | [ResNet50-Quadruplet](https://gitee.com/mindspore/models/tree/master/research/cv/metric_learn) |✅| ✅ | | +| 图像 | 图像分类 | [ResNet50-Triplet](https://gitee.com/mindspore/models/tree/master/research/cv/metric_learn) |✅| ✅ | | +| 图像 | 图像分类 | [ResnetV2_101](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | +| 图像 | 图像分类 | [ResnetV2_152](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | +| 图像 | 图像分类 | [ResnetV2_50](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | +| 图像 | 图像分类 | [resnetv2_50_frn](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2_50_frn) |✅| ✅ | | +| 图像 | 图像分类 | [resnext152_64x4d](https://gitee.com/mindspore/models/tree/master/research/cv/resnext152_64x4d) |✅| ✅ | | +| 图像 | 目标检测 | [retinaface_mobilenet0.25](https://gitee.com/mindspore/models/tree/master/research/cv/retinaface) |✅| ✅ | | +| 图像 | 目标检测 | [retinanet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet101) |✅| ✅ | | +| 图像 | 目标检测 | [retinanet_resnet152](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet152) |✅| ✅ | | +| 图像 | 目标检测 | [rfcn](https://gitee.com/mindspore/models/tree/master/research/cv/rfcn) | | ✅ | | +| 图像 | 图像分类 | [SE_ResNeXt50](https://gitee.com/mindspore/models/tree/master/research/cv/SE_ResNeXt50) |✅| | | +| 图像 | 图像分类 | [senet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [senet_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [se-res2net50](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | +| 图像 | 图像分类 | [S-GhostNet](https://gitee.com/mindspore/models/tree/master/research/cv/S-GhostNet) |✅| | | +| 图像 | 姿态估计 | [simple_baselines](https://gitee.com/mindspore/models/tree/master/research/cv/simple_baselines) |✅| ✅ | | +| 图像 | 图像生成 | [SinGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SinGAN) |✅| | | +| 图像 | 图像分类 | [single_path_nas](https://gitee.com/mindspore/models/tree/master/research/cv/single_path_nas) |✅| ✅ | | +| 图像 | 图像分类 | [sknet](https://gitee.com/mindspore/models/tree/master/research/cv/sknet) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [snn_mlp](https://gitee.com/mindspore/models/tree/master/research/cv/snn_mlp) | | ✅ | | +| 图像 | 目标检测 | [Spnas](https://gitee.com/mindspore/models/tree/master/research/cv/Spnas) |✅| | | +| 图像 | 图像分类 | [SPPNet](https://gitee.com/mindspore/models/tree/master/research/cv/SPPNet) |✅| ✅ | | +| 图像 | 图像分类 | [squeezenet](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | +| 图像 | 图像超分 | [sr_ea](https://gitee.com/mindspore/models/tree/master/research/cv/sr_ea) |✅| | | +| 图像 | 图像超分 | [SRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SRGAN) |✅| ✅ | | +| 图像 | 图像分类 | [ssc_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/ssc_resnet50) |✅| ✅ | | +| 图像 | 目标检测 | [ssd_ghostnet](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_ghostnet) |✅| ✅ | ✅ | +| 图像 | 目标检测 | [ssd_inception_v2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_inception_v2) | | ✅ | ✅ | +| 图像 | 目标检测 | [ssd_inceptionv2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_inceptionv2) |✅| | | +| 图像 | 目标检测 | [ssd_mobilenetV2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2) |✅| ✅ | ✅ | +| 图像 | 目标检测 | [ssd_mobilenetV2_FPNlite](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2_FPNlite) |✅| ✅ | ✅ | +| 图像 | 目标检测 | [ssd_resnet_34](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet_34) | | ✅ | | +| 图像 | 目标检测 | [ssd_resnet34](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet34) |✅| | ✅ | +| 图像 | 目标检测 | [ssd_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet50) |✅| | | +| 图像 | 姿态估计 | [StackedHourglass](https://gitee.com/mindspore/models/tree/master/research/cv/StackedHourglass) |✅| | | +| 图像 | 图像生成 | [StarGAN](https://gitee.com/mindspore/models/tree/master/research/cv/StarGAN) |✅| ✅ | | +| 图像 | 图像生成 | [STGAN](https://gitee.com/mindspore/models/tree/master/research/cv/STGAN) |✅| ✅ | | +| 图像 | 交通预测 | [stgcn](https://gitee.com/mindspore/models/tree/master/research/cv/stgcn) |✅| ✅ | | +| 图像 | 图像分类 | [stpm](https://gitee.com/mindspore/models/tree/master/official/cv/STPM) |✅| ✅ | | +| 图像 | 图像分类 | [swin_transformer](https://gitee.com/mindspore/models/tree/master/official/cv/SwinTransformer) |✅| ✅ | | +| 图像 | 时间定位 | [tall](https://gitee.com/mindspore/models/tree/master/research/cv/tall) |✅| | | +| 图像 | 图像分类 | [TCN](https://gitee.com/mindspore/models/tree/master/research/cv/TCN) |✅| ✅ | | +| 图像 | 文本检测 | [textfusenet](https://gitee.com/mindspore/models/tree/master/research/cv/textfusenet) |✅| | | +| 图像 | 交通预测 | [tgcn](https://gitee.com/mindspore/models/tree/master/research/cv/tgcn) |✅| ✅ | | +| 图像 | 图像分类 | [tinynet](https://gitee.com/mindspore/models/tree/master/research/cv/tinynet) | | ✅ | | +| 图像 | 图像分类 | [TNT](https://gitee.com/mindspore/models/tree/master/research/cv/TNT) |✅| ✅ | | +| 图像 | 目标检测 | [u2net](https://gitee.com/mindspore/models/tree/master/research/cv/u2net) |✅| ✅ | | +| 图像 | 图像生成 | [U-GAT-IT](https://gitee.com/mindspore/models/tree/master/research/cv/U-GAT-IT) |✅| ✅ | | +| 图像 | 语义分割 | [UNet3+](https://gitee.com/mindspore/models/tree/master/research/cv/UNet3+) |✅| ✅ | | +| 图像 | 重新识别 | [VehicleNet](https://gitee.com/mindspore/models/tree/master/research/cv/VehicleNet) |✅| | | +| 图像 | 图像分类 | [vgg19](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/vgg19) |✅| ✅ | | +| 图像 | 图像分类 | [ViG](https://gitee.com/mindspore/models/tree/master/research/cv/ViG) |✅| ✅ | | +| 图像 | 图像分类 | [vit_cifar](https://gitee.com/mindspore/models/tree/master/research/cv/vit_base) |✅| ✅ | | +| 图像 | 语义分割 | [vnet](https://gitee.com/mindspore/models/tree/master/research/cv/vnet) |✅| ✅ | | +| 图像 | 图像分类 | [wave_mlp](https://gitee.com/mindspore/models/tree/master/research/cv/wave_mlp) |✅| ✅ | | +| 图像 | 图像超分 | [wdsr](https://gitee.com/mindspore/models/tree/master/research/cv/wdsr) |✅| ✅ | | +| 图像 | 图像生成 | [wgan](https://gitee.com/mindspore/models/tree/master/official/cv/WGAN) |✅| | | +| 图像 | 图像分类 | [wideresnet](https://gitee.com/mindspore/models/tree/master/research/cv/wideresnet) |✅| ✅ | | +| 图像 | 实例分割 | [Yolact++](https://gitee.com/mindspore/models/tree/master/research/cv/Yolact++) |✅| | | +| 图像 | 目标检测 | [yolov3_tiny](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_tiny) |✅| ✅ | | +| 图像 | 目标检测 | [yolox](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOX) |✅| | | +| 多模态 | 多模态 | [opt](https://gitee.com/mindspore/models/tree/master/research/mm/opt) |✅| ✅ | | +| 多模态 | 多模态 | [TokenFusion](https://gitee.com/mindspore/models/tree/master/research/cv/TokenFusion) |✅| ✅ | | +| 多模态 | 多模态 | [wukong](https://gitee.com/mindspore/models/tree/master/research/mm/wukong) |✅| | | +| 推荐 | 点击率预测 | [autodis](https://gitee.com/mindspore/models/tree/master/research/recommend/autodis) |✅| ✅ | | +| 推荐 | 点击率预测 | [DIEN](https://gitee.com/mindspore/models/tree/master/research/recommend/DIEN) |✅| ✅ | | +| 推荐 | 点击率预测 | [dlrm](https://gitee.com/mindspore/models/tree/master/research/recommend/dlrm) |✅| ✅ | | +| 推荐 | 点击率预测 | [EDCN](https://gitee.com/mindspore/models/tree/master/research/recommend/EDCN) |✅| ✅ | | +| 推荐 | 点击率预测 | [Fat-DeepFFM](https://gitee.com/mindspore/models/tree/master/research/recommend/Fat-DeepFFM) |✅| ✅ | | +| 推荐 | 点击率预测 | [mmoe](https://gitee.com/mindspore/models/tree/master/research/recommend/mmoe) |✅| ✅ | | +| 文本 | 自然语言理解 | [albert](https://gitee.com/mindspore/models/tree/master/research/nlp/albert) |✅| ✅ | | +| 文本 | 情绪分类 | [atae_lstm](https://gitee.com/mindspore/models/tree/master/research/nlp/atae_lstm) |✅| ✅ | | +| 文本 | 对话 | [dam](https://gitee.com/mindspore/models/tree/master/research/nlp/dam) |✅| | | +| 文本 | 语言模型 | [gpt2](https://gitee.com/mindspore/models/tree/master/research/nlp/gpt2) |✅| | | +| 文本 | 知识图嵌入 | [hake](https://gitee.com/mindspore/models/tree/master/research/nlp/hake) | | ✅ | | +| 文本 | 自然语言理解 | [ktnet](https://gitee.com/mindspore/models/tree/master/research/nlp/ktnet) |✅| ✅ | | +| 文本 | 命名实体识别 | [lstm_crf](https://gitee.com/mindspore/models/tree/master/research/nlp/lstm_crf) |✅| | | +| 文本 | 自然语言理解 | [luke](https://gitee.com/mindspore/models/tree/master/research/nlp/luke) |✅| ✅ | | +| 文本 | 知识图嵌入 | [rotate](https://gitee.com/mindspore/models/tree/master/research/nlp/rotate) |✅| ✅ | | +| 文本 | 情绪分类 | [senta](https://gitee.com/mindspore/models/tree/master/research/nlp/senta) |✅| ✅ | | +| 文本 | 机器翻译 | [seq2seq](https://gitee.com/mindspore/models/tree/master/research/nlp/seq2seq) |✅| | | +| 文本 | 词嵌入 | [skipgram](https://gitee.com/mindspore/models/tree/master/research/nlp/skipgram) |✅| ✅ | | +| 文本 | 机器翻译 | [speech_transformer](https://gitee.com/mindspore/models/tree/master/research/nlp/speech_transformer) |✅| | | +| 文本 | 预训练 | [ternarybert](https://gitee.com/mindspore/models/tree/master/research/nlp/ternarybert) |✅| ✅ | | +| 文本 | 自然语言理解 | [tprr](https://gitee.com/mindspore/models/tree/master/research/nlp/tprr) |✅| | | +| 文本 | 自然语言理解 | [transformer_xl](https://gitee.com/mindspore/models/tree/master/research/nlp/transformer_xl) |✅| ✅ | | +| 文本 | 知识图嵌入 | [transX](https://gitee.com/mindspore/models/tree/master/research/nlp/transX) | | ✅ | | +| 视频 | 视频分类 | [AttentionCluster](https://gitee.com/mindspore/models/tree/master/research/cv/AttentionCluster) |✅| ✅ | | +| 视频 | 其他 | [DYR](https://gitee.com/mindspore/models/tree/master/research/nlp/DYR) |✅| | | +| 视频 | 视频分类 | [ecolite](https://gitee.com/mindspore/models/tree/master/research/cv/ecolite) |✅| | | +| 视频 | 目标追踪 | [fairmot](https://gitee.com/mindspore/models/tree/master/research/cv/fairmot) |✅| ✅ | | +| 视频 | 视频分类 | [I3D](https://gitee.com/mindspore/models/tree/master/research/cv/I3D) |✅| | | +| 视频 | 目标追踪 | [JDE](https://gitee.com/mindspore/models/tree/master/research/cv/JDE) | | ✅ | | +| 视频 | 视频分割 | [OSVOS](https://gitee.com/mindspore/models/tree/master/research/cv/OSVOS) | | ✅ | | +| 视频 | 视频分类 | [r2plus1d](https://gitee.com/mindspore/models/tree/master/research/cv/r2plus1d) |✅| ✅ | | +| 视频 | 视频超分 | [rbpn](https://gitee.com/mindspore/models/tree/master/research/cv/rbpn) |✅| | | +| 视频 | 视频分类 | [resnet3d](https://gitee.com/mindspore/models/tree/master/research/cv/resnet3d) |✅| | | +| 视频 | 目标追踪 | [SiamFC](https://gitee.com/mindspore/models/tree/master/research/cv/SiamFC) |✅| | | +| 视频 | 目标追踪 | [siamRPN](https://gitee.com/mindspore/models/tree/master/research/cv/siamRPN) |✅| ✅ | | +| 视频 | 视频分类 | [slowfast](https://gitee.com/mindspore/models/tree/master/research/cv/slowfast) |✅| ✅ | | +| 视频 | 视频分类 | [stnet](https://gitee.com/mindspore/models/tree/master/research/cv/stnet) |✅| | | +| 视频 | 目标追踪 | [tracktor](https://gitee.com/mindspore/models/tree/master/research/cv/tracktor) | | ✅ | | +| 视频 | 目标追踪 | [tracktor++](https://gitee.com/mindspore/models/tree/master/research/cv/tracktor++) |✅| ✅ | | +| 视频 | 视频分类 | [trn](https://gitee.com/mindspore/models/tree/master/research/cv/trn) | | ✅ | | +| 视频 | 视频分类 | [tsm](https://gitee.com/mindspore/models/tree/master/research/cv/tsm) |✅| ✅ | | +| 视频 | 视频分类 | [tsn](https://gitee.com/mindspore/models/tree/master/research/cv/tsn) |✅| ✅ | | + +Process finished with exit code 0 + +- [社区](https://gitee.com/mindspore/models/tree/master/community) + +## 公告 + +### 2021.9.15 `models`独立建仓 + +`models`仓库由原[mindspore仓库](https://gitee.com/mindspore/mindspore)的model_zoo目录独立分离而来，新仓库不继承历史commit记录，如果需要查找历史提2021.9.15之前的提交，请到mindspore仓库进行查询。 + +## 关联站点 + +这里是MindSpore框架提供的可以运行于包括Ascend/GPU/CPU/移动设备等多种设备的模型库。 + +相应的专属于Ascend平台的多框架模型可以参考[昇腾ModelZoo](https://hiascend.com/software/modelzoo)以及对应的[代码仓](https://gitee.com/ascend/modelzoo)。 + +MindSpore相关的预训练模型可以在[MindSpore hub](https://www.mindspore.cn/resources/hub)或[下载中心](https://download.mindspore.cn/model_zoo/). + +## 免责声明 + +MindSpore仅提供下载和预处理公共数据集的脚本。我们不拥有这些数据集，也不对它们的质量负责或维护。请确保您具有在数据集许可下使用该数据集的权限。在这些数据集上训练的模型仅用于非商业研究和教学目的。 + +致数据集拥有者：如果您不希望将数据集包含在MindSpore中，或者希望以任何方式对其进行更新，我们将根据要求删除或更新所有公共内容。请通过GitHub或Gitee与我们联系。非常感谢您对这个社区的理解和贡献。 + +MindSpore已获得Apache 2.0许可，请参见LICENSE文件。 + +## 许可证 + +[Apache 2.0许可证](https://gitee.com/mindspore/mindspore/blob/master/LICENSE) ## FAQ -For more information about `MindSpore` framework, please refer to [FAQ](https://www.mindspore.cn/docs/en/master/faq/installation.html) +想要获取更多关于`MindSpore`框架使用本身的FAQ问题的，可以参考[官网FAQ](https://www.mindspore.cn/docs/zh-CN/master/faq/installation.html) -- **Q: How to resolve the lack of memory while using the model directly under "models" with errors such as *Failed to alloc memory pool memory*?** +- **Q: 直接使用models下的模型出现内存不足错误，例如*Failed to alloc memory pool memory*, 该怎么处理?** - **A**: The typical reason for insufficient memory when directly using models under "models" is due to differences in operating mode (`PYNATIVE_MODE`), operating environment configuration, and license control (AI-TOKEN). - - `PYNATIVE_MODE` usually uses more memory than `GRAPH_MODE` , especially in the training graph that needs back propagation calculation, there are two ways to try to solve this problem. - Method 1: You can try to use some smaller batch size; - Method 2: Add context.set_context(mempool_block_size="XXGB"), where the current maximum effective value of "XX" can be set to "31". - If method 1 and method 2 are used in combination, the effect will be better. - - The operating environment will also cause similar problems due to the different configurations of NPU cores, memory, etc.; - - Different gears of License control (AI-TOKEN ) will cause different memory overhead during execution. You can also try to use some smaller batch sizes. + **A**: 直接使用models下的模型出现内存不足的典型原因是由于运行模式（`PYNATIVE_MODE`)、运行环境配置、License控制（AI-TOKEN）的不同造成的： + - `PYNATIVE_MODE`通常比`GRAPH_MODE`使用更多内存，尤其是在需要进行反向传播计算的训练图中，当前有2种方法可以尝试解决该问题。 + 方法1：你可以尝试使用一些更小的batch size； + 方法2：添加context.set_context(mempool_block_size="XXGB")，其中，“XX”当前最大有效值可设置为“31”。 + 如果将方法1与方法2结合使用，效果会更好。 + - 运行环境由于NPU的核数、内存等配置不同也会产生类似问题。 + - License控制（AI-TOKEN）的不同档位会造成执行过程中内存开销不同，也可以尝试使用一些更小的batch size。 -- **Q: How to resolve the error about the interface are not supported in some network operations, such as `cann not import`?** +- **Q: 一些网络运行中报错接口不存在，例如cannot import，该怎么处理?** - **A**: Please check the version of MindSpore and the branch you fetch the modelzoo scripts. Some model scripits in latest branch will use new interface in the latest version of MindSpore. + **A**: 优先检查一下获取网络脚本的分支，与所使用的MindSpore版本是否一致，部分新分支中的模型脚本会使用一些新版本MindSpore才支持的接口，从而在使用老版本MindSpore时会发生报错. -- **Q: What is Some *RANK_TBAL_FILE* which mentioned in many models?** +- **Q: 一些模型描述中提到的*RANK_TABLE_FILE*文件，是什么？** - **A**: *RANK_TABLE_FILE* is the config file of cluster on Ascend while running distributed training. For more information, you could refer to the generator [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) and [Parallel Distributed Training Example](https://mindspore.cn/docs/programming_guide/en/r1.5/distributed_training_ascend.html#configuring-distributed-environment-variables) + **A**: *RANK_TABLE_FILE*是一个Ascend环境上用于指定分布式集群信息的文件，更多信息可以参考生成工具[hccl_toos](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)和[分布式并行训练教程](https://mindspore.cn/docs/programming_guide/zh-CN/r1.5/distributed_training_ascend.html#id4) -- **Q: How to run the scripts on Windows system?** +- **Q: 在windows环境上要怎么运行网络脚本？** - **A**: Most the start-up scripts are written in `bash`, but we usually can't run bash directly on Windows. You can try start python directly without bash scripts. If you really need the start-up bash scripts, we suggest you the following method to get a bash environment on Windows: - 1. Use a virtual system or docker container with linux system. Then run the scripts in the virtual system or container. - 2. Use WSL, you could turn on the `Windows Subsystem for Linux` on Windows to obtain an linux system which could run the bash scripts. - 3. Use some bash tools on Windows, such as [cygwin](http://www.cygwin.com) and [git bash](https://gitforwindows.org). + **A**: 多数模型都是使用bash作为启动脚本，在Windows环境上无法直接使用bash命令，你可以考虑直接运行python命令而不是bash启动脚本 ，如果你确实想需要使用bash脚本，你可以考虑使用以下几种方法来运行模型： + 1. 使用虚拟环境，可以构造一个linux的虚拟机或docker容器，然后在虚拟环境中运行脚本 + 2. 使用WSL，可以开启Windows的linux子系统来在Windows系统中运行linux，然后再WSL中运行脚本。 + 3. 使用Windows Bash，需要获取一个可以直接在Windows上运行bash的环境，常见的选择是[cygwin](http://www.cygwin.com)或[git bash](https://gitforwindows.org) + 4. 跳过bash脚本，直接调用python程序。 -- **Q: How to resolve the compile error point to gflags when infer on ascend310 with errors such as *undefined reference to 'google::FlagRegisterer::FlagRegisterer'*?** +- **Q: 网络在310推理时出现编译失败，报错信息指向gflags，例如*undefined reference to 'google::FlagRegisterer::FlagRegisterer'*，该怎么处理?** - **A**: Please check the version of GCC and gflags. You can refer to [GCC](https://www.mindspore.cn/install) and [gflags](https://github.com/gflags/gflags/archive/v2.2.2.tar.gz) to install GCC and gflags. You need to ensure that the components used are ABI compatible, for more information, please refer to [_GLIBCXX_USE_CXX11_ABI](https://gcc.gnu.org/onlinedocs/libstdc++/manual/using_dual_abi.html). + **A**: 优先检查一下环境GCC版本和gflags版本是否匹配，可以参考[官方链接](https://www.mindspore.cn/install)安装对应的GCC版本，[gflags](https://github.com/gflags/gflags/archive/v2.2.2.tar.gz)安装gflags。你需要保证所使用的组件之间是ABI兼容的，更多信息可以参考[_GLIBCXX_USE_CXX11_ABI](https://gcc.gnu.org/onlinedocs/libstdc++/manual/using_dual_abi.html) -- **Q: How to solve the error when loading dataset in mindrecord format on Mac system, such as *Invalid file, failed to open files for reading mindrecord files.*?** +- **Q: 在Mac系统上加载mindrecord格式的数据集出错,例如*Invalid file, failed to open files for reading mindrecord files.*，该怎么处理?** - **A**: Please check the system limit with *ulimit -a*, if the number of *file descriptors* is 256 (default), you need to use *ulimit -n 1024* to set it to 1024 (or larger). Then check whether the file is damaged or modified. + **A**: 优先使用*ulimit -a*检查系统限制，如果*file descriptors*数量为256（默认值），需要使用*ulimit -n 1024*将其设置为1024（或者更大的值）。之后再检查文件是否损坏或者被修改。 -- **Q: What should I do if I can't reach the accuracy while training with several servers instead of a single server?** +- **Q: 我在多台服务器构成的大集群上进行训练，但是得到的精度比预期要低，该怎么办？** - **A**: Most of the models has only been trained on single server with at most 8 pcs. Because the `batch_size` used in MindSpore only represent the batch size of single GPU/NPU, the `global_batch_size` will increase while training with multi-server. Different `gloabl_batch_size` requires different hyper parameter including learning_rate, etc. So you have to optimize these hyperparameters will training with multi-servers. + **A**: 当前模型库中的大部分模型只在单机内进行过验证，最大使用8卡进行训练。由于MindSpore训练时指定的`batch_size`是单卡的，所以当单机8卡升级到多机时，会导致全局的`global_batch_size`变大，这就导致需要针对当前多机场景的`global_batch_size`进行重新调参优化。 diff --git a/README_CN.md b/README_CN.md index f8fb7d449..08b4f1942 100644 --- a/README_CN.md +++ b/README_CN.md @@ -10,7 +10,7 @@ MindSpore models仓中提供了不同任务领域，经典的SOTA模型实现和 |------------------------| ------------------------------------------------------------ | | [official](official) | • 官方维护，随MindSpore版本迭代更新，保证版本出口网络的精度效果
• 推荐写法，使用最新的MindSpore接口和推荐使用的特性，在保证代码可读性的基础上，有更快的性能表现
• 有详细的网络信息和说明文档，包含但不限于模型说明，数据集使用，规格支持，精度性能数据，网络checkpoint文件，MindIR文件等 | | [research](research) | • 历史支持，测试验收通过的模型，在README里标明支持的MindSpore版本
• 按需维护，内容不会随版本迭代更新，只会适配对应的接口变更，由MindSpore开发人员进行维护支持，按需进行维护升级
• 提供较为详细的网络信息和说明文档，包含但不限于模型说明，数据集使用，规格支持，精度数据，网络checkpoint文件，MindIR文件等 | -| [community](community) | • 生态开发者贡献模型，按需进行维护升级，在README里说明支持的MindSpore版本
• 不强制提供模型文件 | +| [community](community) | • 生态开发者贡献模型 | - 使用最新MindSpore API的SOTA模型 @@ -18,429 +18,99 @@ MindSpore models仓中提供了不同任务领域，经典的SOTA模型实现和 - 官方维护和支持 -## 目录 - -### 官方网络 - -| 领域 | 子领域 | 网络 | Ascend | GPU | CPU | -|:------ |:------| :----------- |:------: |:------: |:-----: | -| 语音 | 声纹识别 | [ecapa_tdnn](https://gitee.com/mindspore/models/tree/master/official/audio/EcapaTDNN) |✅| | | -| 语音 | 语音合成 | [lpcnet](https://gitee.com/mindspore/models/tree/master/official/audio/LPCNet) |✅| ✅ | | -| 语音 | 语音合成 | [melgan](https://gitee.com/mindspore/models/tree/master/official/audio/MELGAN) |✅| ✅ | | -| 语音 | 语音合成 | [tacotron2](https://gitee.com/mindspore/models/tree/master/official/audio/Tacotron2) |✅| | | -| 图神经网络 | 文本分类 | [bgcf](https://gitee.com/mindspore/models/tree/master/research/gnn/bgcf) |✅| ✅ | | -| 图神经网络 | 文本分类 | [gat](https://gitee.com/mindspore/models/tree/master/research/gnn/gat) |✅| ✅ | | -| 图神经网络 | 文本分类 | [gcn](https://gitee.com/mindspore/models/tree/master/official/gnn/GCN) |✅| ✅ | | -| 推荐 | 推荐系统 | [naml](https://gitee.com/mindspore/models/tree/master/research/recommend/naml) |✅| ✅ | | -| 推荐 | 推荐系统 | [ncf](https://gitee.com/mindspore/models/tree/master/research/recommend/ncf) |✅| ✅ | | -| 推荐 | 推荐系统 | [tbnet](https://gitee.com/mindspore/models/tree/master/official/recommend/Tbnet) |✅| ✅ | | -| 图像 | 图像分类 | [alexnet](https://gitee.com/mindspore/models/tree/master/research/cv/Alexnet) |✅| ✅ | | -| 图像 | 图像去噪 | [brdnet](https://gitee.com/mindspore/models/tree/master/research/cv/brdnet) |✅| | | -| 图像 | 目标检测 | [centerface](https://gitee.com/mindspore/models/tree/master/research/cv/centerface) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [cnn_direction_model](https://gitee.com/mindspore/models/tree/master/research/cv/cnn_direction_model) |✅| ✅ | | -| 图像 | 文本识别 | [cnnctc](https://gitee.com/mindspore/models/tree/master/research/cv/cnnctc) |✅| ✅ | ✅ | -| 图像 | 文本识别 | [crnn](https://gitee.com/mindspore/models/tree/master/official/cv/CRNN) |✅| ✅ | ✅ | -| 图像 | 文本识别 | [crnn_seq2seq_ocr](https://gitee.com/mindspore/models/tree/master/research/cv/crnn_seq2seq_ocr) |✅| | | -| 图像 | 图像分类 | [cspdarknet53](https://gitee.com/mindspore/models/tree/master/research/cv/cspdarknet53) |✅| | | -| 图像 | 目标检测 | [ctpn](https://gitee.com/mindspore/models/tree/master/official/cv/CTPN) |✅| ✅ | | -| 图像 | 目标检测 | [darknet53](https://gitee.com/mindspore/models/tree/master/research/cv/darknet53) | | ✅ | | -| 图像 | 文本检测 | [dbnet](https://gitee.com/mindspore/models/tree/master/official/cv/DBNet) |✅| ✅ | ✅ | -| 图像 | 语义分割 | [deeplabv3](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabV3P) |✅| ✅ | ✅ | -| 图像 | 文本检测 | [deeptext](https://gitee.com/mindspore/models/tree/master/official/cv/DeepText) |✅| ✅ | | -| 图像 | 图像分类 | [densenet100](https://gitee.com/mindspore/models/tree/master/research/cv/densenet) |✅| ✅ | | -| 图像 | 图像分类 | [densenet121](https://gitee.com/mindspore/models/tree/master/research/cv/densenet) |✅| ✅ | | -| 图像 | 深度估计 | [depthnet](https://gitee.com/mindspore/models/tree/master/official/cv/DepthNet) |✅| | | -| 图像 | 图像去噪 | [dncnn](https://gitee.com/mindspore/models/tree/master/research/cv/dncnn) | | ✅ | | -| 图像 | 图像分类 | [dpn](https://gitee.com/mindspore/models/tree/master/research/cv/dpn) |✅| ✅ | | -| 图像 | 文本检测 | [east](https://gitee.com/mindspore/models/tree/master/research/cv/east) |✅| ✅ | | -| 图像 | 图像分类 | [efficientnet](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet) | | ✅ | ✅ | -| 图像 | 图像分类 | [erfnet](https://gitee.com/mindspore/models/tree/master/research/cv/erfnet) |✅| ✅ | | -| 图像 | 文本识别 | [essay-recogination](https://gitee.com/mindspore/models/tree/master/research/cv/essay-recogination) | | ✅ | | -| 图像 | 目标检测 | [FasterRCNN_Inception_Resnetv2](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| 图像 | 目标检测 | [FasterRCNN_ResNetV1.5_50](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| 图像 | 目标检测 | [FasterRCNN_ResNetV1_101](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| 图像 | 目标检测 | [FasterRCNN_ResNetV1_152](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| 图像 | 目标检测 | [FasterRCNN_ResNetV1_50](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| 图像 | 语义分割 | [fastscnn](https://gitee.com/mindspore/models/tree/master/research/cv/fastscnn) |✅| | | -| 图像 | 语义分割 | [FCN8s](https://gitee.com/mindspore/models/tree/master/research/cv/FCN8s) |✅| ✅ | | -| 图像 | 图像分类 | [googlenet](https://gitee.com/mindspore/models/tree/master/research/cv/googlenet) |✅| ✅ | | -| 图像 | 图像分类 | [inceptionv3](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv3) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [inceptionv4](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv4) |✅| ✅ | ✅ | -| 图像 | 图像去噪 | [LearningToSeeInTheDark](https://gitee.com/mindspore/models/tree/master/research/cv/LearningToSeeInTheDark) |✅| | | -| 图像 | 图像分类 | [lenet](https://gitee.com/mindspore/models/tree/master/research/cv/lenet) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [maskrcnn_resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/MaskRCNN/maskrcnn_resnet50) |✅| ✅ | | -| 图像 | 目标检测 | [maskrcnn_mobilenetv1](https://gitee.com/mindspore/models/tree/master/official/cv/MaskRCNN/maskrcnn_mobilenetv1) |✅| ✅ | ✅ | -| 图像 | 人群计数 | [MCNN](https://gitee.com/mindspore/models/tree/master/research/cv/MCNN) |✅| ✅ | | -| 图像 | 图像分类 | [mobilenetv1](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv1) |✅| ✅ | | -| 图像 | 图像分类 | [mobilenetv2](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv2) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [mobilenetv3](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv3) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [nasnet](https://gitee.com/mindspore/models/tree/master/research/cv/nasnet) |✅| ✅ | | -| 图像 | 图像质量评估 | [nima](https://gitee.com/mindspore/models/tree/master/research/cv/nima) |✅| ✅ | | -| 图像 | 点云模型 | [octsqueeze](https://gitee.com/mindspore/models/tree/master/official/cv/OctSqueeze) |✅| ✅ | | -| 图像 | 关键点检测 | [openpose](https://gitee.com/mindspore/models/tree/master/official/cv/OpenPose) |✅| | | -| 图像 | 缺陷检测 | [patchcore](https://gitee.com/mindspore/models/tree/master/official/cv/PatchCore) |✅| ✅ | | -| 图像 | 相机重定位 | [posenet](https://gitee.com/mindspore/models/tree/master/research/cv/PoseNet) |✅| ✅ | | -| 图像 | 视频预测学习 | [predrnn++](https://gitee.com/mindspore/models/tree/master/research/cv/predrnn++) |✅| | | -| 图像 | 文本检测 | [psenet](https://gitee.com/mindspore/models/tree/master/research/cv/psenet) |✅| ✅ | | -| 图像 | 姿态估计 | [pvnet](https://gitee.com/mindspore/models/tree/master/official/cv/PVNet) |✅| | | -| 图像 | 光流估计 | [pwcnet](https://gitee.com/mindspore/models/tree/master/official/cv/PWCNet) |✅| ✅ | | -| 图像 | 图像超分 | [RDN](https://gitee.com/mindspore/models/tree/master/research/cv/RDN) |✅| ✅ | | -| 图像 | 图像分类 | [resnet101](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [resnet152](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [resnet18](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [resnet34](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [resnet50_thor](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | | -| 图像 | 图像分类 | [resnext101](https://gitee.com/mindspore/models/tree/master/official/cv/ResNeXt) |✅| ✅ | | -| 图像 | 图像分类 | [resnext50](https://gitee.com/mindspore/models/tree/master/official/cv/ResNeXt) |✅| ✅ | | -| 图像 | 目标检测 | [retinaface_resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/RetinaFace_ResNet50) | | ✅ | | -| 图像 | 目标检测 | [retinanet](https://gitee.com/mindspore/models/tree/master/official/cv/RetinaNet) |✅| ✅ | | -| 图像 | 图像分类 | [se_resnext50](https://gitee.com/mindspore/models/tree/master/research/cv/SE_ResNeXt50) |✅| | | -| 图像 | 图像抠图 | [semantic_human_matting](https://gitee.com/mindspore/models/tree/master/official/cv/SemanticHumanMatting) |✅| | | -| 图像 | 图像分类 | [se-resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [shufflenetv1](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv1) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [shufflenetv2](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv2) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [simclr](https://gitee.com/mindspore/models/tree/master/research/cv/simclr) |✅| ✅ | | -| 图像 | 关键点检测 | [simple_pose](https://gitee.com/mindspore/models/tree/master/research/cv/simple_pose) |✅| ✅ | | -| 图像 | 目标检测 | [sphereface](https://gitee.com/mindspore/models/tree/master/research/cv/sphereface) |✅| ✅ | | -| 图像 | 图像分类 | [squeezenet](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | -| 图像 | 图像分类 | [SqueezeNet_Residual](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | -| 图像 | 图像超分 | [srcnn](https://gitee.com/mindspore/models/tree/master/research/cv/srcnn) |✅| ✅ | | -| 图像 | 目标检测 | [ssd_mobilenet-v1-fpn](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd_mobilenet-v2](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd-resnet50-fpn](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd-vgg16](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | -| 图像 | 缺陷检测 | [ssim-ae](https://gitee.com/mindspore/models/tree/master/official/cv/SSIM-AE) |✅| | | -| 图像 | 图像分类 | [tinydarknet](https://gitee.com/mindspore/models/tree/master/research/cv/tinydarknet) |✅| ✅ | ✅ | -| 图像 | 语义分割 | [UNet_nested](https://gitee.com/mindspore/models/tree/master/official/cv/Unet) |✅| ✅ | | -| 图像 | 语义分割 | [unet2d](https://gitee.com/mindspore/models/tree/master/official/cv/Unet) |✅| ✅ | | -| 图像 | 语义分割 | [unet3d](https://gitee.com/mindspore/models/tree/master/official/cv/Unet3d) |✅| ✅ | | -| 图像 | 图像分类 | [vgg16](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/vgg16) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [vit](https://gitee.com/mindspore/models/tree/master/official/cv/VIT) |✅| ✅ | | -| 图像 | 文本识别 | [warpctc](https://gitee.com/mindspore/models/tree/master/research/cv/warpctc) |✅| ✅ | | -| 图像 | 图像分类 | [xception](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/xception) |✅| ✅ | | -| 图像 | 目标检测 | [yolov3_darknet53](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv3) |✅| ✅ | | -| 图像 | 目标检测 | [yolov3_resnet18](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_resnet18) |✅| | | -| 图像 | 目标检测 | [yolov4](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv4) |✅| | | -| 图像 | 目标检测 | [yolov5s](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv5) |✅| ✅ | | -| 推荐 | 点击率预测 | [deep_and_cross](https://gitee.com/mindspore/models/tree/master/research/recommend/deep_and_cross) | | ✅ | | -| 推荐 | 点击率预测 | [deepfm](https://gitee.com/mindspore/models/tree/master/official/recommend/DeepFM) |✅| ✅ | | -| 推荐 | 点击率预测 | [fibinet](https://gitee.com/mindspore/models/tree/master/research/recommend/fibinet) | | ✅ | | -| 推荐 | 点击率预测 | [wide_and_deep](https://gitee.com/mindspore/models/tree/master/official/recommend/Wide_and_Deep) |✅| ✅ | | -| 推荐 | 点击率预测 | [wide_and_deep_multitable](https://gitee.com/mindspore/models/tree/master/official/recommend/Wide_and_Deep_Multitable) |✅| ✅ | | -| 文本 | 自然语言理解 | [bert_base](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | -| 文本 | 自然语言理解 | [bert_bilstm_crf](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | -| 文本 | 自然语言理解 | [bert_finetuning](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | -| 文本 | 自然语言理解 | [bert_large](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| | | -| 文本 | 自然语言理解 | [bert_nezha](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | -| 文本 | 自然语言理解 | [cpm](https://gitee.com/mindspore/models/tree/master/research/nlp/cpm) |✅| ✅ | | -| 文本 | 对话 | [dgu](https://gitee.com/mindspore/models/tree/master/research/nlp/dgu) |✅| ✅ | | -| 文本 | 对话 | [duconv](https://gitee.com/mindspore/models/tree/master/research/nlp/duconv) |✅| ✅ | | -| 文本 | 情绪分类 | [emotect](https://gitee.com/mindspore/models/tree/master/research/nlp/emotect) |✅| ✅ | | -| 文本 | 自然语言理解 | [ernie](https://gitee.com/mindspore/models/tree/master/research/nlp/ernie) |✅| ✅ | | -| 文本 | 自然语言理解 | [fasttext](https://gitee.com/mindspore/models/tree/master/research/nlp/fasttext) |✅| ✅ | | -| 文本 | 自然语言理解 | [gnmt_v2](https://gitee.com/mindspore/models/tree/master/research/nlp/gnmt_v2) |✅| ✅ | | -| 文本 | 自然语言理解 | [gpt3](https://gitee.com/mindspore/models/tree/master/official/nlp/GPT) |✅| | | -| 文本 | 自然语言理解 | [gru](https://gitee.com/mindspore/models/tree/master/official/nlp/GRU) |✅| ✅ | | -| 文本 | 情绪分类 | [lstm](https://gitee.com/mindspore/models/tree/master/official/nlp/LSTM) |✅| ✅ | | -| 文本 | 自然语言理解 | [mass](https://gitee.com/mindspore/models/tree/master/research/nlp/mass) |✅| ✅ | | -| 文本 | 预训练 | [pangu_alpha](https://gitee.com/mindspore/models/tree/master/official/nlp/Pangu_alpha) |✅| ✅ | | -| 文本 | 自然语言理解 | [textcnn](https://gitee.com/mindspore/models/tree/master/research/nlp/textcnn) |✅| ✅ | | -| 文本 | 自然语言理解 | [tinybert](https://gitee.com/mindspore/models/tree/master/research/nlp/tinybert) |✅| ✅ | | -| 文本 | 自然语言理解 | [transformer](https://gitee.com/mindspore/models/tree/master/official/nlp/Transformer) |✅| ✅ | | -| 视频 | 目标追踪 | [ADNet](https://gitee.com/mindspore/models/tree/master/research/cv/ADNet) |✅| | | -| 视频 | 视频分类 | [c3d](https://gitee.com/mindspore/models/tree/master/official/cv/C3D) |✅| ✅ | | -| 视频 | 目标追踪 | [Deepsort](https://gitee.com/mindspore/models/tree/master/research/cv/Deepsort) |✅| ✅ | | - -### 研究网络 - -| 领域 | 子领域 | 网络 | Ascend | GPU | CPU | -|:------ |:------| :----------- |:------: |:------: |:-----: | -| 3D | 三维重建 | [cmr](https://gitee.com/mindspore/models/tree/master/research/cv/cmr) | | ✅ | | -| 3D | 三维重建 | [DecoMR](https://gitee.com/mindspore/models/tree/master/research/cv/DecoMR) | | ✅ | | -| 3D | 三维重建 | [DeepLM](https://gitee.com/mindspore/models/tree/master/research/3d/DeepLM) | | ✅ | | -| 3D | 三维重建 | [eppmvsnet](https://gitee.com/mindspore/models/tree/master/research/cv/eppmvsnet) | | ✅ | | -| 3D | 三维物体检测 | [pointpillars](https://gitee.com/mindspore/models/tree/master/research/cv/pointpillars) |✅| ✅ | | -| 语音 | 语音识别 | [ctcmodel](https://gitee.com/mindspore/models/tree/master/research/audio/ctcmodel) |✅| | | -| 语音 | 语音识别 | [deepspeech2](https://gitee.com/mindspore/models/tree/master/official/audio/DeepSpeech2) | | ✅ | | -| 语音 | 语音唤醒 | [dscnn](https://gitee.com/mindspore/models/tree/master/research/audio/dscnn) |✅| ✅ | | -| 语音 | 语音合成 | [FastSpeech](https://gitee.com/mindspore/models/tree/master/research/audio/FastSpeech) | | ✅ | | -| 语音 | 语音标注 | [fcn-4](https://gitee.com/mindspore/models/tree/master/research/audio/fcn-4) |✅| ✅ | | -| 语音 | 语音识别 | [jasper](https://gitee.com/mindspore/models/tree/master/research/audio/jasper) |✅| ✅ | | -| 语音 | 语音合成 | [wavenet](https://gitee.com/mindspore/models/tree/master/research/audio/wavenet) |✅| ✅ | | -| 图神经网络 | 图分类 | [dgcn](https://gitee.com/mindspore/models/tree/master/research/gnn/dgcn) |✅| | | -| 图神经网络 | 文本分类 | [hypertext](https://gitee.com/mindspore/models/tree/master/research/nlp/hypertext) |✅| ✅ | | -| 图神经网络 | 图分类 | [sdne](https://gitee.com/mindspore/models/tree/master/research/gnn/sdne) |✅| | | -| 图神经网络 | 社会和信息网络 | [sgcn](https://gitee.com/mindspore/models/tree/master/research/gnn/sgcn) |✅| ✅ | | -| 图神经网络 | 文本分类 | [textrcnn](https://gitee.com/mindspore/models/tree/master/research/nlp/textrcnn) |✅| ✅ | | -| 高性能计算 | 高性能计算 | [deepbsde](https://gitee.com/mindspore/models/tree/master/research/hpc/deepbsde) | | ✅ | | -| 高性能计算 | 高性能计算 | [molecular_dynamics](https://gitee.com/mindspore/models/tree/master/research/hpc/molecular_dynamics) |✅| | | -| 高性能计算 | 高性能计算 | [ocean_model](https://gitee.com/mindspore/models/tree/master/research/hpc/ocean_model) | | ✅ | | -| 高性能计算 | 高性能计算 | [pafnucy](https://gitee.com/mindspore/models/tree/master/research/hpc/pafnucy) |✅| ✅ | | -| 高性能计算 | 高性能计算 | [pfnn](https://gitee.com/mindspore/models/tree/master/research/hpc/pfnn) | | ✅ | | -| 高性能计算 | 高性能计算 | [pinns](https://gitee.com/mindspore/models/tree/master/research/hpc/pinns) | | ✅ | | -| 图像 | 图像分类 | [3D_DenseNet](https://gitee.com/mindspore/models/tree/master/research/cv/3D_DenseNet) |✅| ✅ | | -| 图像 | 语义分割 | [3dcnn](https://gitee.com/mindspore/models/tree/master/research/cv/3dcnn) |✅| ✅ | | -| 图像 | 语义分割 | [adelaide_ea](https://gitee.com/mindspore/models/tree/master/research/cv/adelaide_ea) |✅| | | -| 图像 | 文本检测 | [advanced_east](https://gitee.com/mindspore/models/tree/master/research/cv/advanced_east) |✅| ✅ | | -| 图像 | 风格转移 | [aecrnet](https://gitee.com/mindspore/models/tree/master/research/cv/aecrnet) |✅| ✅ | | -| 图像 | 重新识别 | [AlignedReID](https://gitee.com/mindspore/models/tree/master/research/cv/AlignedReID) | | ✅ | | -| 图像 | 重新识别 | [AlignedReID++](https://gitee.com/mindspore/models/tree/master/research/cv/AlignedReID++) |✅| ✅ | | -| 图像 | 姿态估计 | [AlphaPose](https://gitee.com/mindspore/models/tree/master/research/cv/AlphaPose) |✅| | | -| 图像 | 风格转移 | [APDrawingGAN](https://gitee.com/mindspore/models/tree/master/research/cv/APDrawingGAN) |✅| ✅ | | -| 图像 | 风格转移 | [ArbitraryStyleTransfer](https://gitee.com/mindspore/models/tree/master/research/cv/ArbitraryStyleTransfer) |✅| ✅ | | -| 图像 | 目标检测 | [arcface](https://gitee.com/mindspore/models/tree/master/official/cv/Arcface) |✅| ✅ | | -| 图像 | 关键点检测 | [ArtTrack](https://gitee.com/mindspore/models/tree/master/research/cv/ArtTrack) | | ✅ | | -| 图像 | 风格转移 | [AttGAN](https://gitee.com/mindspore/models/tree/master/research/cv/AttGAN) |✅| ✅ | | -| 图像 | 图像分类 | [augvit](https://gitee.com/mindspore/models/tree/master/research/cv/augvit) | | ✅ | | -| 图像 | 图像分类 | [autoaugment](https://gitee.com/mindspore/models/tree/master/research/cv/autoaugment) |✅| ✅ | | -| 图像 | 语义分割 | [Auto-DeepLab](https://gitee.com/mindspore/models/tree/master/research/cv/Auto-DeepLab) |✅| | | -| 图像 | 神经架构搜索 | [AutoSlim](https://gitee.com/mindspore/models/tree/master/research/cv/AutoSlim) |✅| ✅ | | -| 图像 | 图像分类 | [AVA_cifar](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_cifar) |✅| ✅ | | -| 图像 | 图像分类 | [AVA_hpa](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_hpa) |✅| ✅ | | -| 图像 | 图像分类 | [cait](https://gitee.com/mindspore/models/tree/master/research/cv/cait) |✅| ✅ | | -| 图像 | 目标检测 | [CascadeRCNN](https://gitee.com/mindspore/models/tree/master/research/cv/CascadeRCNN) |✅| ✅ | | -| 图像 | 图像分类 | [CBAM](https://gitee.com/mindspore/models/tree/master/research/cv/CBAM) |✅| | | -| 图像 | 图像分类 | [cct](https://gitee.com/mindspore/models/tree/master/research/cv/cct) |✅| ✅ | | -| 图像 | 关键点检测 | [centernet](https://gitee.com/mindspore/models/tree/master/research/cv/centernet) |✅| | ✅ | -| 图像 | 关键点检测 | [centernet_det](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_det) |✅| | | -| 图像 | 关键点检测 | [centernet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet101) |✅| ✅ | | -| 图像 | 关键点检测 | [centernet_resnet50_v1](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet50_v1) |✅| | | -| 图像 | 图像生成 | [CGAN](https://gitee.com/mindspore/models/tree/master/research/cv/CGAN) |✅| ✅ | | -| 图像 | 图像分类 | [convnext](https://gitee.com/mindspore/models/tree/master/research/cv/convnext) |✅| ✅ | | -| 图像 | 图像超分 | [csd](https://gitee.com/mindspore/models/tree/master/research/cv/csd) |✅| ✅ | | -| 图像 | 图像生成 | [CTSDG](https://gitee.com/mindspore/models/tree/master/research/cv/CTSDG) | | ✅ | | -| 图像 | 风格转移 | [CycleGAN](https://gitee.com/mindspore/models/tree/master/official/cv/CycleGAN) |✅| ✅ | | -| 图像 | 图像超分 | [DBPN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) |✅| | | -| 图像 | 图像超分 | [DBPN_GAN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) |✅| | | -| 图像 | 图像生成 | [dcgan](https://gitee.com/mindspore/models/tree/master/research/cv/dcgan) |✅| ✅ | | -| 图像 | 重新识别 | [DDAG](https://gitee.com/mindspore/models/tree/master/research/cv/DDAG) |✅| ✅ | | -| 图像 | 语义分割 | [DDM](https://gitee.com/mindspore/models/tree/master/research/cv/DDM) |✅| | | -| 图像 | 语义分割 | [DDRNet](https://gitee.com/mindspore/models/tree/master/research/cv/DDRNet) |✅| ✅ | | -| 图像 | 目标检测 | [DeepID](https://gitee.com/mindspore/models/tree/master/research/cv/DeepID) |✅| ✅ | | -| 图像 | 语义分割 | [deeplabv3plus](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabV3P) |✅| ✅ | | -| 图像 | 图像检索 | [delf](https://gitee.com/mindspore/models/tree/master/research/cv/delf) |✅| | | -| 图像 | 零样本学习 | [dem](https://gitee.com/mindspore/models/tree/master/research/cv/dem) |✅| ✅ | | -| 图像 | 目标检测 | [detr](https://gitee.com/mindspore/models/tree/master/research/cv/detr) |✅| ✅ | | -| 图像 | 语义分割 | [dgcnet_res101](https://gitee.com/mindspore/models/tree/master/research/cv/dgcnet_res101) | | ✅ | | -| 图像 | 实例分割 | [dlinknet](https://gitee.com/mindspore/models/tree/master/research/cv/dlinknet) |✅| | | -| 图像 | 图像去噪 | [DnCNN](https://gitee.com/mindspore/models/tree/master/research/cv/DnCNN) |✅| | | -| 图像 | 图像分类 | [dnet_nas](https://gitee.com/mindspore/models/tree/master/research/cv/dnet_nas) |✅| | | -| 图像 | 图像分类 | [DRNet](https://gitee.com/mindspore/models/tree/master/research/cv/DRNet) |✅| ✅ | | -| 图像 | 图像超分 | [EDSR](https://gitee.com/mindspore/models/tree/master/official/cv/EDSR) |✅| | | -| 图像 | 目标检测 | [EfficientDet_d0](https://gitee.com/mindspore/models/tree/master/research/cv/EfficientDet_d0) |✅| | | -| 图像 | 图像分类 | [efficientnet-b0](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b0) |✅| | | -| 图像 | 图像分类 | [efficientnet-b1](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnet-b1) |✅| | | -| 图像 | 图像分类 | [efficientnet-b2](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnet-b2) |✅| ✅ | | -| 图像 | 图像分类 | [efficientnet-b3](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnet-b3) |✅| ✅ | | -| 图像 | 图像分类 | [efficientnetv2](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnetv2) |✅| | | -| 图像 | 显著性检测 | [EGnet](https://gitee.com/mindspore/models/tree/master/research/cv/EGnet) |✅| ✅ | | -| 图像 | 语义分割 | [E-NET](https://gitee.com/mindspore/models/tree/master/research/cv/E-NET) |✅| ✅ | | -| 图像 | 图像超分 | [esr_ea](https://gitee.com/mindspore/models/tree/master/research/cv/esr_ea) |✅| ✅ | | -| 图像 | 图像超分 | [ESRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/ESRGAN) |✅| ✅ | | -| 图像 | 图像分类 | [FaceAttribute](https://gitee.com/mindspore/models/tree/master/research/cv/FaceAttribute) |✅| ✅ | | -| 图像 | 目标检测 | [faceboxes](https://gitee.com/mindspore/models/tree/master/research/cv/faceboxes) |✅| | | -| 图像 | 目标检测 | [FaceDetection](https://gitee.com/mindspore/models/tree/master/research/cv/FaceDetection) |✅| ✅ | | -| 图像 | 人脸识别 | [FaceNet](https://gitee.com/mindspore/models/tree/master/research/cv/FaceNet) |✅| ✅ | | -| 图像 | 图像分类 | [FaceQualityAssessment](https://gitee.com/mindspore/models/tree/master/research/cv/FaceQualityAssessment) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [FaceRecognition](https://gitee.com/mindspore/models/tree/master/official/cv/FaceRecognition) |✅| ✅ | | -| 图像 | 目标检测 | [FaceRecognitionForTracking](https://gitee.com/mindspore/models/tree/master/research/cv/FaceRecognitionForTracking) |✅| | ✅ | -| 图像 | 目标检测 | [faster_rcnn_dcn](https://gitee.com/mindspore/models/tree/master/research/cv/faster_rcnn_dcn) |✅| ✅ | | -| 图像 | 图像抠图 | [FCANet](https://gitee.com/mindspore/models/tree/master/research/cv/FCANet) |✅| | | -| 图像 | 图像分类 | [FDA-BNN](https://gitee.com/mindspore/models/tree/master/research/cv/FDA-BNN) |✅| ✅ | | -| 图像 | 图像分类 | [fishnet99](https://gitee.com/mindspore/models/tree/master/research/cv/fishnet99) |✅| ✅ | | -| 图像 | 光流估计 | [flownet2](https://gitee.com/mindspore/models/tree/master/research/cv/flownet2) |✅| | | -| 图像 | 图像生成 | [gan](https://gitee.com/mindspore/models/tree/master/research/cv/gan) |✅| ✅ | | -| 图像 | 图像分类 | [GENet_Res50](https://gitee.com/mindspore/models/tree/master/research/cv/GENet_Res50) |✅| | | -| 图像 | 图像分类 | [ghostnet](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet) |✅| | | -| 图像 | 图像分类 | [ghostnet_d](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet_d) |✅| ✅ | | -| 图像 | 图像分类 | [glore_res200](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) |✅| ✅ | | -| 图像 | 图像分类 | [glore_res50](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) |✅| ✅ | | -| 图像 | 图像分类 | [hardnet](https://gitee.com/mindspore/models/tree/master/research/cv/hardnet) |✅| ✅ | | -| 图像 | 边缘检测 | [hed](https://gitee.com/mindspore/models/tree/master/research/cv/hed) |✅| ✅ | | -| 图像 | 图像生成 | [HiFaceGAN](https://gitee.com/mindspore/models/tree/master/research/cv/HiFaceGAN) | | ✅ | | -| 图像 | 图像分类 | [HourNAS](https://gitee.com/mindspore/models/tree/master/research/cv/HourNAS) | | ✅ | | -| 图像 | 图像分类 | [HRNetW48_cls](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_cls) |✅| ✅ | | -| 图像 | 语义分割 | [HRNetW48_seg](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_seg) |✅| | | -| 图像 | 图像分类 | [ibnnet](https://gitee.com/mindspore/models/tree/master/research/cv/ibnnet) |✅| ✅ | | -| 图像 | 语义分割 | [ICNet](https://gitee.com/mindspore/models/tree/master/research/cv/ICNet) |✅| | | -| 图像 | 图像分类 | [inception_resnet_v2](https://gitee.com/mindspore/models/tree/master/research/cv/inception_resnet_v2) |✅| ✅ | | -| 图像 | 图像分类 | [Inceptionv2](https://gitee.com/mindspore/models/tree/master/research/cv/Inception-v2) |✅| ✅ | | -| 图像 | 图像抠图 | [IndexNet](https://gitee.com/mindspore/models/tree/master/research/cv/IndexNet) | | ✅ | | -| 图像 | 图像生成 | [IPT](https://gitee.com/mindspore/models/tree/master/research/cv/IPT) |✅| | | -| 图像 | 图像超分 | [IRN](https://gitee.com/mindspore/models/tree/master/research/cv/IRN) |✅| ✅ | | -| 图像 | 图像分类 | [ISyNet](https://gitee.com/mindspore/models/tree/master/research/cv/ISyNet) |✅| ✅ | | -| 图像 | 图像分类 | [ivpf](https://gitee.com/mindspore/models/tree/master/research/cv/ivpf) | | ✅ | | -| 图像 | 图像去噪 | [LearningToSeeInTheDark](https://gitee.com/mindspore/models/tree/master/research/cv/LearningToSeeInTheDark) |✅| | | -| 图像 | 元学习 | [LEO](https://gitee.com/mindspore/models/tree/master/research/cv/LEO) |✅| ✅ | | -| 图像 | 目标检测 | [LightCNN](https://gitee.com/mindspore/models/tree/master/research/cv/LightCNN) |✅| ✅ | ✅ | -| 图像 | 图像超分 | [lite-hrnet](https://gitee.com/mindspore/models/tree/master/research/cv/lite-hrnet) | | ✅ | | -| 图像 | 图像分类 | [lresnet100e_ir](https://gitee.com/mindspore/models/tree/master/research/cv/lresnet100e_ir) | | ✅ | | -| 图像 | 目标检测 | [m2det](https://gitee.com/mindspore/models/tree/master/research/cv/m2det) | | ✅ | | -| 图像 | 自编码 | [mae](https://gitee.com/mindspore/models/tree/master/official/cv/MAE) |✅| ✅ | | -| 图像 | 元学习 | [MAML](https://gitee.com/mindspore/models/tree/master/research/cv/MAML) |✅| ✅ | | -| 图像 | 文本识别 | [ManiDP](https://gitee.com/mindspore/models/tree/master/research/cv/ManiDP) | | ✅ | | -| 图像 | 人脸识别 | [MaskedFaceRecognition](https://gitee.com/mindspore/models/tree/master/research/cv/MaskedFaceRecognition) |✅| | | -| 图像 | 元学习 | [meta-baseline](https://gitee.com/mindspore/models/tree/master/research/cv/meta-baseline) |✅| ✅ | | -| 图像 | 重新识别 | [MGN](https://gitee.com/mindspore/models/tree/master/research/cv/MGN) |✅| ✅ | | -| 图像 | 深度估计 | [midas](https://gitee.com/mindspore/models/tree/master/research/cv/midas) |✅| ✅ | | -| 图像 | 图像去噪 | [MIMO-UNet](https://gitee.com/mindspore/models/tree/master/research/cv/MIMO-UNet) | | ✅ | | -| 图像 | 图像分类 | [mnasnet](https://gitee.com/mindspore/models/tree/master/research/cv/mnasnet) |✅| ✅ | | -| 图像 | 图像分类 | [mobilenetv3_large](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetv3_large) |✅| | ✅ | -| 图像 | 图像分类 | [mobilenetV3_small_x1_0](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetV3_small_x1_0) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [MultiTaskNet](https://gitee.com/mindspore/models/tree/master/research/cv/PAMTRI/MultiTaskNet) |✅| ✅ | | -| 图像 | 重新识别 | [MVD](https://gitee.com/mindspore/models/tree/master/research/cv/MVD) |✅| ✅ | | -| 图像 | 目标检测 | [nas-fpn](https://gitee.com/mindspore/models/tree/master/research/cv/nas-fpn) |✅| | | -| 图像 | 图像去噪 | [Neighbor2Neighbor](https://gitee.com/mindspore/models/tree/master/research/cv/Neighbor2Neighbor) |✅| ✅ | | -| 图像 | 图像分类 | [NFNet](https://gitee.com/mindspore/models/tree/master/research/cv/NFNet) |✅| ✅ | | -| 图像 | 图像质量评估 | [nima_vgg16](https://gitee.com/mindspore/models/tree/master/research/cv/nima_vgg16) | | ✅ | | -| 图像 | 语义分割 | [nnUNet](https://gitee.com/mindspore/models/tree/master/research/cv/nnUNet) |✅| ✅ | | -| 图像 | 图像分类 | [ntsnet](https://gitee.com/mindspore/models/tree/master/research/cv/ntsnet) |✅| ✅ | | -| 图像 | 语义分割 | [OCRNet](https://gitee.com/mindspore/models/tree/master/official/cv/OCRNet) |✅| ✅ | | -| 图像 | 重新识别 | [osnet](https://gitee.com/mindspore/models/tree/master/research/cv/osnet) |✅| ✅ | | -| 图像 | 显著性检测 | [PAGENet](https://gitee.com/mindspore/models/tree/master/research/cv/PAGENet) |✅| ✅ | | -| 图像 | 图像检索 | [pcb](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | -| 图像 | 图像检索 | [pcb](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | -| 图像 | 图像检索 | [pcb_rpp](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | -| 图像 | 图像分类 | [PDarts](https://gitee.com/mindspore/models/tree/master/research/cv/PDarts) |✅| ✅ | | -| 图像 | 图像生成 | [PGAN](https://gitee.com/mindspore/models/tree/master/research/cv/PGAN) |✅| ✅ | | -| 图像 | 图像生成 | [Pix2Pix](https://gitee.com/mindspore/models/tree/master/research/cv/Pix2Pix) |✅| ✅ | | -| 图像 | 图像超分 | [Pix2PixHD](https://gitee.com/mindspore/models/tree/master/official/cv/Pix2PixHD) |✅| | | -| 图像 | 图像分类 | [pnasnet](https://gitee.com/mindspore/models/tree/master/research/cv/pnasnet) |✅| ✅ | | -| 图像 | 点云模型 | [pointnet](https://gitee.com/mindspore/models/tree/master/official/cv/PointNet) |✅| ✅ | | -| 图像 | 点云模型 | [pointnet2](https://gitee.com/mindspore/models/tree/master/official/cv/PointNet2) |✅| ✅ | | -| 图像 | 图像分类 | [PoseEstNet](https://gitee.com/mindspore/models/tree/master/research/cv/PAMTRI/PoseEstNet) |✅| ✅ | | -| 图像 | 图像分类 | [ProtoNet](https://gitee.com/mindspore/models/tree/master/research/cv/ProtoNet) |✅| ✅ | | -| 图像 | 图像分类 | [proxylessnas](https://gitee.com/mindspore/models/tree/master/research/cv/proxylessnas) |✅| ✅ | | -| 图像 | 语义分割 | [PSPNet](https://gitee.com/mindspore/models/tree/master/research/cv/PSPNet) |✅| | | -| 图像 | 显著性检测 | [ras](https://gitee.com/mindspore/models/tree/master/research/cv/ras) |✅| ✅ | | -| 图像 | 图像超分 | [RCAN](https://gitee.com/mindspore/models/tree/master/research/cv/RCAN) |✅| | | -| 图像 | 目标检测 | [rcnn](https://gitee.com/mindspore/models/tree/master/research/cv/rcnn) |✅| ✅ | | -| 图像 | 图像超分 | [REDNet30](https://gitee.com/mindspore/models/tree/master/research/cv/REDNet30) |✅| ✅ | | -| 图像 | 目标检测 | [RefineDet](https://gitee.com/mindspore/models/tree/master/research/cv/RefineDet) |✅| ✅ | | -| 图像 | 语义分割 | [RefineNet](https://gitee.com/mindspore/models/tree/master/research/cv/RefineNet) |✅| ✅ | | -| 图像 | 重新识别 | [ReIDStrongBaseline](https://gitee.com/mindspore/models/tree/master/research/cv/ReIDStrongBaseline) |✅| ✅ | | -| 图像 | 图像分类 | [relationnet](https://gitee.com/mindspore/models/tree/master/research/cv/relationnet) |✅| ✅ | | -| 图像 | 图像分类 | [renas](https://gitee.com/mindspore/models/tree/master/research/cv/renas) |✅| ✅ | ✅ | -| 图像 | 语义分割 | [repvgg](https://gitee.com/mindspore/models/tree/master/research/cv/repvgg) |✅| ✅ | | -| 图像 | 语义分割 | [res2net_deeplabv3](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_deeplabv3) |✅| | ✅ | -| 图像 | 目标检测 | [res2net_faster_rcnn](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_faster_rcnn) |✅| ✅ | | -| 图像 | 目标检测 | [res2net_yolov3](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_yolov3) |✅| ✅ | | -| 图像 | 图像分类 | [res2net101](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| 图像 | 图像分类 | [res2net152](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| 图像 | 图像分类 | [res2net50](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| 图像 | 图像分类 | [ResNeSt50](https://gitee.com/mindspore/models/tree/master/research/cv/ResNeSt50) |✅| ✅ | | -| 图像 | 图像分类 | [resnet50_adv_pruning](https://gitee.com/mindspore/models/tree/master/research/cv/resnet50_adv_pruning) |✅| ✅ | | -| 图像 | 图像分类 | [resnet50_bam](https://gitee.com/mindspore/models/tree/master/research/cv/resnet50_bam) |✅| ✅ | | -| 图像 | 图像分类 | [ResNet50-Quadruplet](https://gitee.com/mindspore/models/tree/master/research/cv/metric_learn) |✅| ✅ | | -| 图像 | 图像分类 | [ResNet50-Triplet](https://gitee.com/mindspore/models/tree/master/research/cv/metric_learn) |✅| ✅ | | -| 图像 | 图像分类 | [ResnetV2_101](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | -| 图像 | 图像分类 | [ResnetV2_152](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | -| 图像 | 图像分类 | [ResnetV2_50](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | -| 图像 | 图像分类 | [resnetv2_50_frn](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2_50_frn) |✅| ✅ | | -| 图像 | 图像分类 | [resnext152_64x4d](https://gitee.com/mindspore/models/tree/master/research/cv/resnext152_64x4d) |✅| ✅ | | -| 图像 | 目标检测 | [retinaface_mobilenet0.25](https://gitee.com/mindspore/models/tree/master/research/cv/retinaface) |✅| ✅ | | -| 图像 | 目标检测 | [retinanet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet101) |✅| ✅ | | -| 图像 | 目标检测 | [retinanet_resnet152](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet152) |✅| ✅ | | -| 图像 | 目标检测 | [rfcn](https://gitee.com/mindspore/models/tree/master/research/cv/rfcn) | | ✅ | | -| 图像 | 图像分类 | [SE_ResNeXt50](https://gitee.com/mindspore/models/tree/master/research/cv/SE_ResNeXt50) |✅| | | -| 图像 | 图像分类 | [senet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [senet_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [se-res2net50](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| 图像 | 图像分类 | [S-GhostNet](https://gitee.com/mindspore/models/tree/master/research/cv/S-GhostNet) |✅| | | -| 图像 | 姿态估计 | [simple_baselines](https://gitee.com/mindspore/models/tree/master/research/cv/simple_baselines) |✅| ✅ | | -| 图像 | 图像生成 | [SinGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SinGAN) |✅| | | -| 图像 | 图像分类 | [single_path_nas](https://gitee.com/mindspore/models/tree/master/research/cv/single_path_nas) |✅| ✅ | | -| 图像 | 图像分类 | [sknet](https://gitee.com/mindspore/models/tree/master/research/cv/sknet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [snn_mlp](https://gitee.com/mindspore/models/tree/master/research/cv/snn_mlp) | | ✅ | | -| 图像 | 目标检测 | [Spnas](https://gitee.com/mindspore/models/tree/master/research/cv/Spnas) |✅| | | -| 图像 | 图像分类 | [SPPNet](https://gitee.com/mindspore/models/tree/master/research/cv/SPPNet) |✅| ✅ | | -| 图像 | 图像分类 | [squeezenet](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | -| 图像 | 图像超分 | [sr_ea](https://gitee.com/mindspore/models/tree/master/research/cv/sr_ea) |✅| | | -| 图像 | 图像超分 | [SRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SRGAN) |✅| ✅ | | -| 图像 | 图像分类 | [ssc_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/ssc_resnet50) |✅| ✅ | | -| 图像 | 目标检测 | [ssd_ghostnet](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_ghostnet) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd_inception_v2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_inception_v2) | | ✅ | ✅ | -| 图像 | 目标检测 | [ssd_inceptionv2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_inceptionv2) |✅| | | -| 图像 | 目标检测 | [ssd_mobilenetV2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd_mobilenetV2_FPNlite](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2_FPNlite) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd_resnet_34](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet_34) | | ✅ | | -| 图像 | 目标检测 | [ssd_resnet34](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet34) |✅| | ✅ | -| 图像 | 目标检测 | [ssd_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet50) |✅| | | -| 图像 | 姿态估计 | [StackedHourglass](https://gitee.com/mindspore/models/tree/master/research/cv/StackedHourglass) |✅| | | -| 图像 | 图像生成 | [StarGAN](https://gitee.com/mindspore/models/tree/master/research/cv/StarGAN) |✅| ✅ | | -| 图像 | 图像生成 | [STGAN](https://gitee.com/mindspore/models/tree/master/research/cv/STGAN) |✅| ✅ | | -| 图像 | 交通预测 | [stgcn](https://gitee.com/mindspore/models/tree/master/research/cv/stgcn) |✅| ✅ | | -| 图像 | 图像分类 | [stpm](https://gitee.com/mindspore/models/tree/master/official/cv/STPM) |✅| ✅ | | -| 图像 | 图像分类 | [swin_transformer](https://gitee.com/mindspore/models/tree/master/official/cv/SwinTransformer) |✅| ✅ | | -| 图像 | 时间定位 | [tall](https://gitee.com/mindspore/models/tree/master/research/cv/tall) |✅| | | -| 图像 | 图像分类 | [TCN](https://gitee.com/mindspore/models/tree/master/research/cv/TCN) |✅| ✅ | | -| 图像 | 文本检测 | [textfusenet](https://gitee.com/mindspore/models/tree/master/research/cv/textfusenet) |✅| | | -| 图像 | 交通预测 | [tgcn](https://gitee.com/mindspore/models/tree/master/research/cv/tgcn) |✅| ✅ | | -| 图像 | 图像分类 | [tinynet](https://gitee.com/mindspore/models/tree/master/research/cv/tinynet) | | ✅ | | -| 图像 | 图像分类 | [TNT](https://gitee.com/mindspore/models/tree/master/research/cv/TNT) |✅| ✅ | | -| 图像 | 目标检测 | [u2net](https://gitee.com/mindspore/models/tree/master/research/cv/u2net) |✅| ✅ | | -| 图像 | 图像生成 | [U-GAT-IT](https://gitee.com/mindspore/models/tree/master/research/cv/U-GAT-IT) |✅| ✅ | | -| 图像 | 语义分割 | [UNet3+](https://gitee.com/mindspore/models/tree/master/research/cv/UNet3+) |✅| ✅ | | -| 图像 | 重新识别 | [VehicleNet](https://gitee.com/mindspore/models/tree/master/research/cv/VehicleNet) |✅| | | -| 图像 | 图像分类 | [vgg19](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/vgg19) |✅| ✅ | | -| 图像 | 图像分类 | [ViG](https://gitee.com/mindspore/models/tree/master/research/cv/ViG) |✅| ✅ | | -| 图像 | 图像分类 | [vit_cifar](https://gitee.com/mindspore/models/tree/master/research/cv/vit_base) |✅| ✅ | | -| 图像 | 语义分割 | [vnet](https://gitee.com/mindspore/models/tree/master/research/cv/vnet) |✅| ✅ | | -| 图像 | 图像分类 | [wave_mlp](https://gitee.com/mindspore/models/tree/master/research/cv/wave_mlp) |✅| ✅ | | -| 图像 | 图像超分 | [wdsr](https://gitee.com/mindspore/models/tree/master/research/cv/wdsr) |✅| ✅ | | -| 图像 | 图像生成 | [wgan](https://gitee.com/mindspore/models/tree/master/official/cv/WGAN) |✅| | | -| 图像 | 图像分类 | [wideresnet](https://gitee.com/mindspore/models/tree/master/research/cv/wideresnet) |✅| ✅ | | -| 图像 | 实例分割 | [Yolact++](https://gitee.com/mindspore/models/tree/master/research/cv/Yolact++) |✅| | | -| 图像 | 目标检测 | [yolov3_tiny](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_tiny) |✅| ✅ | | -| 图像 | 目标检测 | [yolox](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOX) |✅| | | -| 多模态 | 多模态 | [opt](https://gitee.com/mindspore/models/tree/master/research/mm/opt) |✅| ✅ | | -| 多模态 | 多模态 | [TokenFusion](https://gitee.com/mindspore/models/tree/master/research/cv/TokenFusion) |✅| ✅ | | -| 多模态 | 多模态 | [wukong](https://gitee.com/mindspore/models/tree/master/research/mm/wukong) |✅| | | -| 推荐 | 点击率预测 | [autodis](https://gitee.com/mindspore/models/tree/master/research/recommend/autodis) |✅| ✅ | | -| 推荐 | 点击率预测 | [DIEN](https://gitee.com/mindspore/models/tree/master/research/recommend/DIEN) |✅| ✅ | | -| 推荐 | 点击率预测 | [dlrm](https://gitee.com/mindspore/models/tree/master/research/recommend/dlrm) |✅| ✅ | | -| 推荐 | 点击率预测 | [EDCN](https://gitee.com/mindspore/models/tree/master/research/recommend/EDCN) |✅| ✅ | | -| 推荐 | 点击率预测 | [Fat-DeepFFM](https://gitee.com/mindspore/models/tree/master/research/recommend/Fat-DeepFFM) |✅| ✅ | | -| 推荐 | 点击率预测 | [mmoe](https://gitee.com/mindspore/models/tree/master/research/recommend/mmoe) |✅| ✅ | | -| 文本 | 自然语言理解 | [albert](https://gitee.com/mindspore/models/tree/master/research/nlp/albert) |✅| ✅ | | -| 文本 | 情绪分类 | [atae_lstm](https://gitee.com/mindspore/models/tree/master/research/nlp/atae_lstm) |✅| ✅ | | -| 文本 | 对话 | [dam](https://gitee.com/mindspore/models/tree/master/research/nlp/dam) |✅| | | -| 文本 | 语言模型 | [gpt2](https://gitee.com/mindspore/models/tree/master/research/nlp/gpt2) |✅| | | -| 文本 | 知识图嵌入 | [hake](https://gitee.com/mindspore/models/tree/master/research/nlp/hake) | | ✅ | | -| 文本 | 自然语言理解 | [ktnet](https://gitee.com/mindspore/models/tree/master/research/nlp/ktnet) |✅| ✅ | | -| 文本 | 命名实体识别 | [lstm_crf](https://gitee.com/mindspore/models/tree/master/research/nlp/lstm_crf) |✅| | | -| 文本 | 自然语言理解 | [luke](https://gitee.com/mindspore/models/tree/master/research/nlp/luke) |✅| ✅ | | -| 文本 | 知识图嵌入 | [rotate](https://gitee.com/mindspore/models/tree/master/research/nlp/rotate) |✅| ✅ | | -| 文本 | 情绪分类 | [senta](https://gitee.com/mindspore/models/tree/master/research/nlp/senta) |✅| ✅ | | -| 文本 | 机器翻译 | [seq2seq](https://gitee.com/mindspore/models/tree/master/research/nlp/seq2seq) |✅| | | -| 文本 | 词嵌入 | [skipgram](https://gitee.com/mindspore/models/tree/master/research/nlp/skipgram) |✅| ✅ | | -| 文本 | 机器翻译 | [speech_transformer](https://gitee.com/mindspore/models/tree/master/research/nlp/speech_transformer) |✅| | | -| 文本 | 预训练 | [ternarybert](https://gitee.com/mindspore/models/tree/master/research/nlp/ternarybert) |✅| ✅ | | -| 文本 | 自然语言理解 | [tprr](https://gitee.com/mindspore/models/tree/master/research/nlp/tprr) |✅| | | -| 文本 | 自然语言理解 | [transformer_xl](https://gitee.com/mindspore/models/tree/master/research/nlp/transformer_xl) |✅| ✅ | | -| 文本 | 知识图嵌入 | [transX](https://gitee.com/mindspore/models/tree/master/research/nlp/transX) | | ✅ | | -| 视频 | 视频分类 | [AttentionCluster](https://gitee.com/mindspore/models/tree/master/research/cv/AttentionCluster) |✅| ✅ | | -| 视频 | 其他 | [DYR](https://gitee.com/mindspore/models/tree/master/research/nlp/DYR) |✅| | | -| 视频 | 视频分类 | [ecolite](https://gitee.com/mindspore/models/tree/master/research/cv/ecolite) |✅| | | -| 视频 | 目标追踪 | [fairmot](https://gitee.com/mindspore/models/tree/master/research/cv/fairmot) |✅| ✅ | | -| 视频 | 视频分类 | [I3D](https://gitee.com/mindspore/models/tree/master/research/cv/I3D) |✅| | | -| 视频 | 目标追踪 | [JDE](https://gitee.com/mindspore/models/tree/master/research/cv/JDE) | | ✅ | | -| 视频 | 视频分割 | [OSVOS](https://gitee.com/mindspore/models/tree/master/research/cv/OSVOS) | | ✅ | | -| 视频 | 视频分类 | [r2plus1d](https://gitee.com/mindspore/models/tree/master/research/cv/r2plus1d) |✅| ✅ | | -| 视频 | 视频超分 | [rbpn](https://gitee.com/mindspore/models/tree/master/research/cv/rbpn) |✅| | | -| 视频 | 视频分类 | [resnet3d](https://gitee.com/mindspore/models/tree/master/research/cv/resnet3d) |✅| | | -| 视频 | 目标追踪 | [SiamFC](https://gitee.com/mindspore/models/tree/master/research/cv/SiamFC) |✅| | | -| 视频 | 目标追踪 | [siamRPN](https://gitee.com/mindspore/models/tree/master/research/cv/siamRPN) |✅| ✅ | | -| 视频 | 视频分类 | [slowfast](https://gitee.com/mindspore/models/tree/master/research/cv/slowfast) |✅| ✅ | | -| 视频 | 视频分类 | [stnet](https://gitee.com/mindspore/models/tree/master/research/cv/stnet) |✅| | | -| 视频 | 目标追踪 | [tracktor](https://gitee.com/mindspore/models/tree/master/research/cv/tracktor) | | ✅ | | -| 视频 | 目标追踪 | [tracktor++](https://gitee.com/mindspore/models/tree/master/research/cv/tracktor++) |✅| ✅ | | -| 视频 | 视频分类 | [trn](https://gitee.com/mindspore/models/tree/master/research/cv/trn) | | ✅ | | -| 视频 | 视频分类 | [tsm](https://gitee.com/mindspore/models/tree/master/research/cv/tsm) |✅| ✅ | | -| 视频 | 视频分类 | [tsn](https://gitee.com/mindspore/models/tree/master/research/cv/tsn) |✅| ✅ | | - -Process finished with exit code 0 +## 标准网络 +## Computer Vision +### Image Classification +| model | mindcv recipe | vanilla mindspore +:-: | :-: | :-: +| vgg | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/) +| resnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | [link](https://gitee.com/zwiori/models/tree/readme/official/cv/ResNet) | +| resnetv2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnetv2) | +| dpn | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | +| densenet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | +| senet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | +| sknet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | +| resnext | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | +| rexnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | +| resnest | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnest) | +| res2net | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | +| googlenet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/googlenet) | +| inceptionv3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inception_v3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv3) | +| inceptionv4 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inception_v4) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv4) | +| mobilenet v1 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv1) | +| mobilenet v2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | +| mobilenet v3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv3) | +| shufflenet v1 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenet_v1) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv1) | +| shufflenet v2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenet_v2) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv2) | +| xception | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/xception) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/xception) | +| ghostnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | +| nasnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/nasnet) | +| mnasnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | +| efficientnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/efficientnet)| [link](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/) | +| regnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | +| mixnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | +| hrnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/hrnet) | +| repvgg | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| bit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | +| repmlp | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repmlp) | +| convnext | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | +| vit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/VIT) | +| swin transformer | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/swintransformer) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/SwinTransformer) +| pvt | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | +| pvt v2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | +| pit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | +| coat | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | +| convit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | +| crossvit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | +| mobilevit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | +| visformer | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | +| edgenext | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | +| poolformer | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/poolformer) | +| volo | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/volo) | +| cait | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/cait) | + +### Object Detection + +#### yolo +| model | mindyolo recipe | vanilla mindspore +:-: | :-: | :-: +| yolo v3 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv3) | +| yolo v4 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov4) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv4) | +| yolo v5 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov5) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv5) | +| yolo v7 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov7) | +| yolo v8 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov8) | +| yolo x | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolovx) | + +#### others +| model | mind_series recipe | vanilla mindspore +:-: | :-: | :-: +| ssd | coming soon | [link](https://gitee.com/mindspore/models/tree/master/official/cv/SSD)| +| fast rcnn | coming soon | [link](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) | +| mask rcnn | coming soon | [link](https://gitee.com/mindspore/models/tree/master/official/cv/MaskRCNN/) | + + +### Senmatic Segmentation + +| model | mind_series recipe | vanilla mindspore +:-: | :-: | :-: +| ocrnet | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/OCRNet/) | +| deeplab v3 | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabv3) | +| deeplab v3 plus | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabV3P) | +| unet | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Unet) | +| unet3d | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Unet3d) | + +### OCR +| model | mindocr recipe | vanilla mindspore +:-: | :-: | :-: +| dbnet | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/dbnet) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/DBNet/) | +| dbnet++ | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/dbnet) | | +| psenet | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/psenet) | | +| east | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/east) | | +| fcenet | coming soon | | +| crnn | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/crnn) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/CRNN/)| +| rare(crnn_seq2seq) | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/rare) | | +| svtr | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/svtr) | | + - [社区](https://gitee.com/mindspore/models/tree/master/community) @@ -450,13 +120,6 @@ Process finished with exit code 0 `models`仓库由原[mindspore仓库](https://gitee.com/mindspore/mindspore)的model_zoo目录独立分离而来，新仓库不继承历史commit记录，如果需要查找历史提2021.9.15之前的提交，请到mindspore仓库进行查询。 -## 关联站点 - -这里是MindSpore框架提供的可以运行于包括Ascend/GPU/CPU/移动设备等多种设备的模型库。 - -相应的专属于Ascend平台的多框架模型可以参考[昇腾ModelZoo](https://hiascend.com/software/modelzoo)以及对应的[代码仓](https://gitee.com/ascend/modelzoo)。 - -MindSpore相关的预训练模型可以在[MindSpore hub](https://www.mindspore.cn/resources/hub)或[下载中心](https://download.mindspore.cn/model_zoo/). ## 免责声明 diff --git a/research/README.md b/research/README.md new file mode 100644 index 000000000..f0093f992 --- /dev/null +++ b/research/README.md @@ -0,0 +1,313 @@ +## 研究机构贡献之算法模型 +以下算法模型来自业界生态伙伴科研机构等，非官方团队维护，如有算法模型需求，请通过[mindspore-lab/models/issue](https://github.com/mindspore-lab/models/issues)联系我们 + +| 领域 | 子领域 | 网络 | Ascend | GPU | CPU | +|:------ |:------| :----------- |:------: |:------: |:-----: | +| 推荐 | 推荐系统 | [naml](https://gitee.com/mindspore/models/tree/master/research/recommend/naml) |✅| ✅ | | +| 推荐 | 推荐系统 | [ncf](https://gitee.com/mindspore/models/tree/master/research/recommend/ncf) |✅| ✅ | | +| 图像 | 图像去噪 | [brdnet](https://gitee.com/mindspore/models/tree/master/research/cv/brdnet) |✅| | | +| 图像 | 目标检测 | [centerface](https://gitee.com/mindspore/models/tree/master/research/cv/centerface) |✅| ✅ | ✅ | +| 图像 | 文本识别 | [cnnctc](https://gitee.com/mindspore/models/tree/master/research/cv/cnnctc) |✅| ✅ | ✅ | +| 图像 | 文本识别 | [crnn_seq2seq_ocr](https://gitee.com/mindspore/models/tree/master/research/cv/crnn_seq2seq_ocr) |✅| | | +| 图像 | 目标检测 | [darknet53](https://gitee.com/mindspore/models/tree/master/research/cv/darknet53) | | ✅ | | +| 图像 | 图像去噪 | [dncnn](https://gitee.com/mindspore/models/tree/master/research/cv/dncnn) | | ✅ | | +| 图像 | 文本检测 | [east](https://gitee.com/mindspore/models/tree/master/research/cv/east) |✅| ✅ | | +| 图像 | 文本识别 | [essay-recogination](https://gitee.com/mindspore/models/tree/master/research/cv/essay-recogination) | | ✅ | | +| 图像 | 语义分割 | [fastscnn](https://gitee.com/mindspore/models/tree/master/research/cv/fastscnn) |✅| | | +| 图像 | 语义分割 | [FCN8s](https://gitee.com/mindspore/models/tree/master/research/cv/FCN8s) |✅| ✅ | | +| 图像 | 图像去噪 | [LearningToSeeInTheDark](https://gitee.com/mindspore/models/tree/master/research/cv/LearningToSeeInTheDark) |✅| | | +| 图像 | 图像分类 | [lenet](https://gitee.com/mindspore/models/tree/master/research/cv/lenet) |✅| ✅ | ✅ | +| 图像 | 人群计数 | [MCNN](https://gitee.com/mindspore/models/tree/master/research/cv/MCNN) |✅| ✅ | | +| 图像 | 图像分类 | [nasnet](https://gitee.com/mindspore/models/tree/master/research/cv/nasnet) |✅| ✅ | | +| 图像 | 图像质量评估 | [nima](https://gitee.com/mindspore/models/tree/master/research/cv/nima) |✅| ✅ | | +| 图像 | 相机重定位 | [posenet](https://gitee.com/mindspore/models/tree/master/research/cv/PoseNet) |✅| ✅ | | +| 图像 | 视频预测学习 | [predrnn++](https://gitee.com/mindspore/models/tree/master/research/cv/predrnn++) |✅| | | +| 图像 | 文本检测 | [psenet](https://gitee.com/mindspore/models/tree/master/research/cv/psenet) |✅| ✅ | | +| 图像 | 图像超分 | [RDN](https://gitee.com/mindspore/models/tree/master/research/cv/RDN) |✅| ✅ | | +| 图像 | 图像分类 | [simclr](https://gitee.com/mindspore/models/tree/master/research/cv/simclr) |✅| ✅ | | +| 图像 | 关键点检测 | [simple_pose](https://gitee.com/mindspore/models/tree/master/research/cv/simple_pose) |✅| ✅ | | +| 图像 | 目标检测 | [sphereface](https://gitee.com/mindspore/models/tree/master/research/cv/sphereface) |✅| ✅ | | +| 图像 | 图像分类 | [squeezenet](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | +| 图像 | 图像分类 | [SqueezeNet_Residual](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | +| 图像 | 图像超分 | [srcnn](https://gitee.com/mindspore/models/tree/master/research/cv/srcnn) |✅| ✅ | | +| 图像 | 图像分类 | [tinydarknet](https://gitee.com/mindspore/models/tree/master/research/cv/tinydarknet) |✅| ✅ | ✅ | +| 图像 | 文本识别 | [warpctc](https://gitee.com/mindspore/models/tree/master/research/cv/warpctc) |✅| ✅ | | +| 图像 | 目标检测 | [yolov3_resnet18](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_resnet18) |✅| | | +| 推荐 | 点击率预测 | [deep_and_cross](https://gitee.com/mindspore/models/tree/master/research/recommend/deep_and_cross) | | ✅ | | +| 推荐 | 点击率预测 | [fibinet](https://gitee.com/mindspore/models/tree/master/research/recommend/fibinet) | | ✅ | | +| 文本 | 自然语言理解 | [cpm](https://gitee.com/mindspore/models/tree/master/research/nlp/cpm) |✅| ✅ | | +| 文本 | 对话 | [dgu](https://gitee.com/mindspore/models/tree/master/research/nlp/dgu) |✅| ✅ | | +| 文本 | 对话 | [duconv](https://gitee.com/mindspore/models/tree/master/research/nlp/duconv) |✅| ✅ | | +| 文本 | 情绪分类 | [emotect](https://gitee.com/mindspore/models/tree/master/research/nlp/emotect) |✅| ✅ | | +| 文本 | 自然语言理解 | [ernie](https://gitee.com/mindspore/models/tree/master/research/nlp/ernie) |✅| ✅ | | +| 文本 | 自然语言理解 | [fasttext](https://gitee.com/mindspore/models/tree/master/research/nlp/fasttext) |✅| ✅ | | +| 文本 | 自然语言理解 | [gnmt_v2](https://gitee.com/mindspore/models/tree/master/research/nlp/gnmt_v2) |✅| ✅ | | +| 文本 | 自然语言理解 | [mass](https://gitee.com/mindspore/models/tree/master/research/nlp/mass) |✅| ✅ | | +| 文本 | 自然语言理解 | [textcnn](https://gitee.com/mindspore/models/tree/master/research/nlp/textcnn) |✅| ✅ | | +| 文本 | 自然语言理解 | [tinybert](https://gitee.com/mindspore/models/tree/master/research/nlp/tinybert) |✅| ✅ | | +| 视频 | 目标追踪 | [ADNet](https://gitee.com/mindspore/models/tree/master/research/cv/ADNet) |✅| | | +| 视频 | 目标追踪 | [Deepsort](https://gitee.com/mindspore/models/tree/master/research/cv/Deepsort) |✅| ✅ | | +| 3D | 三维重建 | [cmr](https://gitee.com/mindspore/models/tree/master/research/cv/cmr) | | ✅ | | +| 3D | 三维重建 | [DecoMR](https://gitee.com/mindspore/models/tree/master/research/cv/DecoMR) | | ✅ | | +| 3D | 三维重建 | [DeepLM](https://gitee.com/mindspore/models/tree/master/research/3d/DeepLM) | | ✅ | | +| 3D | 三维重建 | [eppmvsnet](https://gitee.com/mindspore/models/tree/master/research/cv/eppmvsnet) | | ✅ | | +| 3D | 三维物体检测 | [pointpillars](https://gitee.com/mindspore/models/tree/master/research/cv/pointpillars) |✅| ✅ | | +| 语音 | 语音识别 | [ctcmodel](https://gitee.com/mindspore/models/tree/master/research/audio/ctcmodel) |✅| | | +| 语音 | 语音唤醒 | [dscnn](https://gitee.com/mindspore/models/tree/master/research/audio/dscnn) |✅| ✅ | | +| 语音 | 语音合成 | [FastSpeech](https://gitee.com/mindspore/models/tree/master/research/audio/FastSpeech) | | ✅ | | +| 语音 | 语音标注 | [fcn-4](https://gitee.com/mindspore/models/tree/master/research/audio/fcn-4) |✅| ✅ | | +| 语音 | 语音识别 | [jasper](https://gitee.com/mindspore/models/tree/master/research/audio/jasper) |✅| ✅ | | +| 语音 | 语音合成 | [wavenet](https://gitee.com/mindspore/models/tree/master/research/audio/wavenet) |✅| ✅ | | +| 图神经网络 | 图分类 | [dgcn](https://gitee.com/mindspore/models/tree/master/research/gnn/dgcn) |✅| | | +| 图神经网络 | 文本分类 | [hypertext](https://gitee.com/mindspore/models/tree/master/research/nlp/hypertext) |✅| ✅ | | +| 图神经网络 | 图分类 | [sdne](https://gitee.com/mindspore/models/tree/master/research/gnn/sdne) |✅| | | +| 图神经网络 | 社会和信息网络 | [sgcn](https://gitee.com/mindspore/models/tree/master/research/gnn/sgcn) |✅| ✅ | | +| 图神经网络 | 文本分类 | [textrcnn](https://gitee.com/mindspore/models/tree/master/research/nlp/textrcnn) |✅| ✅ | | +| 高性能计算 | 高性能计算 | [deepbsde](https://gitee.com/mindspore/models/tree/master/research/hpc/deepbsde) | | ✅ | | +| 高性能计算 | 高性能计算 | [molecular_dynamics](https://gitee.com/mindspore/models/tree/master/research/hpc/molecular_dynamics) |✅| | | +| 高性能计算 | 高性能计算 | [ocean_model](https://gitee.com/mindspore/models/tree/master/research/hpc/ocean_model) | | ✅ | | +| 高性能计算 | 高性能计算 | [pafnucy](https://gitee.com/mindspore/models/tree/master/research/hpc/pafnucy) |✅| ✅ | | +| 高性能计算 | 高性能计算 | [pfnn](https://gitee.com/mindspore/models/tree/master/research/hpc/pfnn) | | ✅ | | +| 高性能计算 | 高性能计算 | [pinns](https://gitee.com/mindspore/models/tree/master/research/hpc/pinns) | | ✅ | | +| 图像 | 图像分类 | [3D_DenseNet](https://gitee.com/mindspore/models/tree/master/research/cv/3D_DenseNet) |✅| ✅ | | +| 图像 | 语义分割 | [3dcnn](https://gitee.com/mindspore/models/tree/master/research/cv/3dcnn) |✅| ✅ | | +| 图像 | 语义分割 | [adelaide_ea](https://gitee.com/mindspore/models/tree/master/research/cv/adelaide_ea) |✅| | | +| 图像 | 文本检测 | [advanced_east](https://gitee.com/mindspore/models/tree/master/research/cv/advanced_east) |✅| ✅ | | +| 图像 | 风格转移 | [aecrnet](https://gitee.com/mindspore/models/tree/master/research/cv/aecrnet) |✅| ✅ | | +| 图像 | 重新识别 | [AlignedReID](https://gitee.com/mindspore/models/tree/master/research/cv/AlignedReID) | | ✅ | | +| 图像 | 重新识别 | [AlignedReID++](https://gitee.com/mindspore/models/tree/master/research/cv/AlignedReID++) |✅| ✅ | | +| 图像 | 姿态估计 | [AlphaPose](https://gitee.com/mindspore/models/tree/master/research/cv/AlphaPose) |✅| | | +| 图像 | 风格转移 | [APDrawingGAN](https://gitee.com/mindspore/models/tree/master/research/cv/APDrawingGAN) |✅| ✅ | | +| 图像 | 风格转移 | [ArbitraryStyleTransfer](https://gitee.com/mindspore/models/tree/master/research/cv/ArbitraryStyleTransfer) |✅| ✅ | | +| 图像 | 关键点检测 | [ArtTrack](https://gitee.com/mindspore/models/tree/master/research/cv/ArtTrack) | | ✅ | | +| 图像 | 风格转移 | [AttGAN](https://gitee.com/mindspore/models/tree/master/research/cv/AttGAN) |✅| ✅ | | +| 图像 | 图像分类 | [augvit](https://gitee.com/mindspore/models/tree/master/research/cv/augvit) | | ✅ | | +| 图像 | 图像分类 | [autoaugment](https://gitee.com/mindspore/models/tree/master/research/cv/autoaugment) |✅| ✅ | | +| 图像 | 语义分割 | [Auto-DeepLab](https://gitee.com/mindspore/models/tree/master/research/cv/Auto-DeepLab) |✅| | | +| 图像 | 神经架构搜索 | [AutoSlim](https://gitee.com/mindspore/models/tree/master/research/cv/AutoSlim) |✅| ✅ | | +| 图像 | 图像分类 | [AVA_cifar](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_cifar) |✅| ✅ | | +| 图像 | 图像分类 | [AVA_hpa](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_hpa) |✅| ✅ | | +| 图像 | 图像分类 | [cait](https://gitee.com/mindspore/models/tree/master/research/cv/cait) |✅| ✅ | | +| 图像 | 目标检测 | [CascadeRCNN](https://gitee.com/mindspore/models/tree/master/research/cv/CascadeRCNN) |✅| ✅ | | +| 图像 | 图像分类 | [CBAM](https://gitee.com/mindspore/models/tree/master/research/cv/CBAM) |✅| | | +| 图像 | 图像分类 | [cct](https://gitee.com/mindspore/models/tree/master/research/cv/cct) |✅| ✅ | | +| 图像 | 关键点检测 | [centernet](https://gitee.com/mindspore/models/tree/master/research/cv/centernet) |✅| | ✅ | +| 图像 | 关键点检测 | [centernet_det](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_det) |✅| | | +| 图像 | 关键点检测 | [centernet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet101) |✅| ✅ | | +| 图像 | 关键点检测 | [centernet_resnet50_v1](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet50_v1) |✅| | | +| 图像 | 图像生成 | [CGAN](https://gitee.com/mindspore/models/tree/master/research/cv/CGAN) |✅| ✅ | | +| 图像 | 图像分类 | [convnext](https://gitee.com/mindspore/models/tree/master/research/cv/convnext) |✅| ✅ | | +| 图像 | 图像超分 | [csd](https://gitee.com/mindspore/models/tree/master/research/cv/csd) |✅| ✅ | | +| 图像 | 图像生成 | [CTSDG](https://gitee.com/mindspore/models/tree/master/research/cv/CTSDG) | | ✅ | | +| 图像 | 图像超分 | [DBPN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) |✅| | | +| 图像 | 图像超分 | [DBPN_GAN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) |✅| | | +| 图像 | 图像生成 | [dcgan](https://gitee.com/mindspore/models/tree/master/research/cv/dcgan) |✅| ✅ | | +| 图像 | 重新识别 | [DDAG](https://gitee.com/mindspore/models/tree/master/research/cv/DDAG) |✅| ✅ | | +| 图像 | 语义分割 | [DDM](https://gitee.com/mindspore/models/tree/master/research/cv/DDM) |✅| | | +| 图像 | 语义分割 | [DDRNet](https://gitee.com/mindspore/models/tree/master/research/cv/DDRNet) |✅| ✅ | | +| 图像 | 目标检测 | [DeepID](https://gitee.com/mindspore/models/tree/master/research/cv/DeepID) |✅| ✅ | | +| 图像 | 图像检索 | [delf](https://gitee.com/mindspore/models/tree/master/research/cv/delf) |✅| | | +| 图像 | 零样本学习 | [dem](https://gitee.com/mindspore/models/tree/master/research/cv/dem) |✅| ✅ | | +| 图像 | 目标检测 | [detr](https://gitee.com/mindspore/models/tree/master/research/cv/detr) |✅| ✅ | | +| 图像 | 语义分割 | [dgcnet_res101](https://gitee.com/mindspore/models/tree/master/research/cv/dgcnet_res101) | | ✅ | | +| 图像 | 实例分割 | [dlinknet](https://gitee.com/mindspore/models/tree/master/research/cv/dlinknet) |✅| | | +| 图像 | 图像去噪 | [DnCNN](https://gitee.com/mindspore/models/tree/master/research/cv/DnCNN) |✅| | | +| 图像 | 图像分类 | [dnet_nas](https://gitee.com/mindspore/models/tree/master/research/cv/dnet_nas) |✅| | | +| 图像 | 图像分类 | [DRNet](https://gitee.com/mindspore/models/tree/master/research/cv/DRNet) |✅| ✅ | | +| 图像 | 目标检测 | [EfficientDet_d0](https://gitee.com/mindspore/models/tree/master/research/cv/EfficientDet_d0) |✅| | | +| 图像 | 图像分类 | [efficientnet-b0](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b0) |✅| | | +| 图像 | 显著性检测 | [EGnet](https://gitee.com/mindspore/models/tree/master/research/cv/EGnet) |✅| ✅ | | +| 图像 | 语义分割 | [E-NET](https://gitee.com/mindspore/models/tree/master/research/cv/E-NET) |✅| ✅ | | +| 图像 | 图像超分 | [esr_ea](https://gitee.com/mindspore/models/tree/master/research/cv/esr_ea) |✅| ✅ | | +| 图像 | 图像超分 | [ESRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/ESRGAN) |✅| ✅ | | +| 图像 | 图像分类 | [FaceAttribute](https://gitee.com/mindspore/models/tree/master/research/cv/FaceAttribute) |✅| ✅ | | +| 图像 | 目标检测 | [faceboxes](https://gitee.com/mindspore/models/tree/master/research/cv/faceboxes) |✅| | | +| 图像 | 目标检测 | [FaceDetection](https://gitee.com/mindspore/models/tree/master/research/cv/FaceDetection) |✅| ✅ | | +| 图像 | 人脸识别 | [FaceNet](https://gitee.com/mindspore/models/tree/master/research/cv/FaceNet) |✅| ✅ | | +| 图像 | 图像分类 | [FaceQualityAssessment](https://gitee.com/mindspore/models/tree/master/research/cv/FaceQualityAssessment) |✅| ✅ | ✅ | +| 图像 | 目标检测 | [FaceRecognitionForTracking](https://gitee.com/mindspore/models/tree/master/research/cv/FaceRecognitionForTracking) |✅| | ✅ | +| 图像 | 目标检测 | [faster_rcnn_dcn](https://gitee.com/mindspore/models/tree/master/research/cv/faster_rcnn_dcn) |✅| ✅ | | +| 图像 | 图像抠图 | [FCANet](https://gitee.com/mindspore/models/tree/master/research/cv/FCANet) |✅| | | +| 图像 | 图像分类 | [FDA-BNN](https://gitee.com/mindspore/models/tree/master/research/cv/FDA-BNN) |✅| ✅ | | +| 图像 | 图像分类 | [fishnet99](https://gitee.com/mindspore/models/tree/master/research/cv/fishnet99) |✅| ✅ | | +| 图像 | 光流估计 | [flownet2](https://gitee.com/mindspore/models/tree/master/research/cv/flownet2) |✅| | | +| 图像 | 图像生成 | [gan](https://gitee.com/mindspore/models/tree/master/research/cv/gan) |✅| ✅ | | +| 图像 | 图像分类 | [GENet_Res50](https://gitee.com/mindspore/models/tree/master/research/cv/GENet_Res50) |✅| | | +| 图像 | 图像分类 | [ghostnet](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet) |✅| | | +| 图像 | 图像分类 | [ghostnet_d](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet_d) |✅| ✅ | | +| 图像 | 图像分类 | [glore_res200](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) |✅| ✅ | | +| 图像 | 图像分类 | [glore_res50](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) |✅| ✅ | | +| 图像 | 图像分类 | [hardnet](https://gitee.com/mindspore/models/tree/master/research/cv/hardnet) |✅| ✅ | | +| 图像 | 边缘检测 | [hed](https://gitee.com/mindspore/models/tree/master/research/cv/hed) |✅| ✅ | | +| 图像 | 图像生成 | [HiFaceGAN](https://gitee.com/mindspore/models/tree/master/research/cv/HiFaceGAN) | | ✅ | | +| 图像 | 图像分类 | [HourNAS](https://gitee.com/mindspore/models/tree/master/research/cv/HourNAS) | | ✅ | | +| 图像 | 图像分类 | [HRNetW48_cls](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_cls) |✅| ✅ | | +| 图像 | 语义分割 | [HRNetW48_seg](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_seg) |✅| | | +| 图像 | 图像分类 | [ibnnet](https://gitee.com/mindspore/models/tree/master/research/cv/ibnnet) |✅| ✅ | | +| 图像 | 语义分割 | [ICNet](https://gitee.com/mindspore/models/tree/master/research/cv/ICNet) |✅| | | +| 图像 | 图像分类 | [inception_resnet_v2](https://gitee.com/mindspore/models/tree/master/research/cv/inception_resnet_v2) |✅| ✅ | | +| 图像 | 图像分类 | [Inceptionv2](https://gitee.com/mindspore/models/tree/master/research/cv/Inception-v2) |✅| ✅ | | +| 图像 | 图像抠图 | [IndexNet](https://gitee.com/mindspore/models/tree/master/research/cv/IndexNet) | | ✅ | | +| 图像 | 图像生成 | [IPT](https://gitee.com/mindspore/models/tree/master/research/cv/IPT) |✅| | | +| 图像 | 图像超分 | [IRN](https://gitee.com/mindspore/models/tree/master/research/cv/IRN) |✅| ✅ | | +| 图像 | 图像分类 | [ISyNet](https://gitee.com/mindspore/models/tree/master/research/cv/ISyNet) |✅| ✅ | | +| 图像 | 图像分类 | [ivpf](https://gitee.com/mindspore/models/tree/master/research/cv/ivpf) | | ✅ | | +| 图像 | 图像去噪 | [LearningToSeeInTheDark](https://gitee.com/mindspore/models/tree/master/research/cv/LearningToSeeInTheDark) |✅| | | +| 图像 | 元学习 | [LEO](https://gitee.com/mindspore/models/tree/master/research/cv/LEO) |✅| ✅ | | +| 图像 | 目标检测 | [LightCNN](https://gitee.com/mindspore/models/tree/master/research/cv/LightCNN) |✅| ✅ | ✅ | +| 图像 | 图像超分 | [lite-hrnet](https://gitee.com/mindspore/models/tree/master/research/cv/lite-hrnet) | | ✅ | | +| 图像 | 图像分类 | [lresnet100e_ir](https://gitee.com/mindspore/models/tree/master/research/cv/lresnet100e_ir) | | ✅ | | +| 图像 | 目标检测 | [m2det](https://gitee.com/mindspore/models/tree/master/research/cv/m2det) | | ✅ | | +| 图像 | 元学习 | [MAML](https://gitee.com/mindspore/models/tree/master/research/cv/MAML) |✅| ✅ | | +| 图像 | 文本识别 | [ManiDP](https://gitee.com/mindspore/models/tree/master/research/cv/ManiDP) | | ✅ | | +| 图像 | 人脸识别 | [MaskedFaceRecognition](https://gitee.com/mindspore/models/tree/master/research/cv/MaskedFaceRecognition) |✅| | | +| 图像 | 元学习 | [meta-baseline](https://gitee.com/mindspore/models/tree/master/research/cv/meta-baseline) |✅| ✅ | | +| 图像 | 重新识别 | [MGN](https://gitee.com/mindspore/models/tree/master/research/cv/MGN) |✅| ✅ | | +| 图像 | 深度估计 | [midas](https://gitee.com/mindspore/models/tree/master/research/cv/midas) |✅| ✅ | | +| 图像 | 图像去噪 | [MIMO-UNet](https://gitee.com/mindspore/models/tree/master/research/cv/MIMO-UNet) | | ✅ | | +| 图像 | 图像分类 | [mnasnet](https://gitee.com/mindspore/models/tree/master/research/cv/mnasnet) |✅| ✅ | | +| 图像 | 图像分类 | [mobilenetv3_large](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetv3_large) |✅| | ✅ | +| 图像 | 图像分类 | [mobilenetV3_small_x1_0](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetV3_small_x1_0) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [MultiTaskNet](https://gitee.com/mindspore/models/tree/master/research/cv/PAMTRI/MultiTaskNet) |✅| ✅ | | +| 图像 | 重新识别 | [MVD](https://gitee.com/mindspore/models/tree/master/research/cv/MVD) |✅| ✅ | | +| 图像 | 目标检测 | [nas-fpn](https://gitee.com/mindspore/models/tree/master/research/cv/nas-fpn) |✅| | | +| 图像 | 图像去噪 | [Neighbor2Neighbor](https://gitee.com/mindspore/models/tree/master/research/cv/Neighbor2Neighbor) |✅| ✅ | | +| 图像 | 图像分类 | [NFNet](https://gitee.com/mindspore/models/tree/master/research/cv/NFNet) |✅| ✅ | | +| 图像 | 图像质量评估 | [nima_vgg16](https://gitee.com/mindspore/models/tree/master/research/cv/nima_vgg16) | | ✅ | | +| 图像 | 语义分割 | [nnUNet](https://gitee.com/mindspore/models/tree/master/research/cv/nnUNet) |✅| ✅ | | +| 图像 | 图像分类 | [ntsnet](https://gitee.com/mindspore/models/tree/master/research/cv/ntsnet) |✅| ✅ | | +| 图像 | 重新识别 | [osnet](https://gitee.com/mindspore/models/tree/master/research/cv/osnet) |✅| ✅ | | +| 图像 | 显著性检测 | [PAGENet](https://gitee.com/mindspore/models/tree/master/research/cv/PAGENet) |✅| ✅ | | +| 图像 | 图像检索 | [pcb](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | +| 图像 | 图像检索 | [pcb](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | +| 图像 | 图像检索 | [pcb_rpp](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | +| 图像 | 图像分类 | [PDarts](https://gitee.com/mindspore/models/tree/master/research/cv/PDarts) |✅| ✅ | | +| 图像 | 图像生成 | [PGAN](https://gitee.com/mindspore/models/tree/master/research/cv/PGAN) |✅| ✅ | | +| 图像 | 图像生成 | [Pix2Pix](https://gitee.com/mindspore/models/tree/master/research/cv/Pix2Pix) |✅| ✅ | | +| 图像 | 图像分类 | [pnasnet](https://gitee.com/mindspore/models/tree/master/research/cv/pnasnet) |✅| ✅ | | +| 图像 | 图像分类 | [PoseEstNet](https://gitee.com/mindspore/models/tree/master/research/cv/PAMTRI/PoseEstNet) |✅| ✅ | | +| 图像 | 图像分类 | [ProtoNet](https://gitee.com/mindspore/models/tree/master/research/cv/ProtoNet) |✅| ✅ | | +| 图像 | 图像分类 | [proxylessnas](https://gitee.com/mindspore/models/tree/master/research/cv/proxylessnas) |✅| ✅ | | +| 图像 | 语义分割 | [PSPNet](https://gitee.com/mindspore/models/tree/master/research/cv/PSPNet) |✅| | | +| 图像 | 显著性检测 | [ras](https://gitee.com/mindspore/models/tree/master/research/cv/ras) |✅| ✅ | | +| 图像 | 图像超分 | [RCAN](https://gitee.com/mindspore/models/tree/master/research/cv/RCAN) |✅| | | +| 图像 | 目标检测 | [rcnn](https://gitee.com/mindspore/models/tree/master/research/cv/rcnn) |✅| ✅ | | +| 图像 | 图像超分 | [REDNet30](https://gitee.com/mindspore/models/tree/master/research/cv/REDNet30) |✅| ✅ | | +| 图像 | 目标检测 | [RefineDet](https://gitee.com/mindspore/models/tree/master/research/cv/RefineDet) |✅| ✅ | | +| 图像 | 语义分割 | [RefineNet](https://gitee.com/mindspore/models/tree/master/research/cv/RefineNet) |✅| ✅ | | +| 图像 | 重新识别 | [ReIDStrongBaseline](https://gitee.com/mindspore/models/tree/master/research/cv/ReIDStrongBaseline) |✅| ✅ | | +| 图像 | 图像分类 | [relationnet](https://gitee.com/mindspore/models/tree/master/research/cv/relationnet) |✅| ✅ | | +| 图像 | 图像分类 | [renas](https://gitee.com/mindspore/models/tree/master/research/cv/renas) |✅| ✅ | ✅ | +| 图像 | 语义分割 | [repvgg](https://gitee.com/mindspore/models/tree/master/research/cv/repvgg) |✅| ✅ | | +| 图像 | 语义分割 | [res2net_deeplabv3](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_deeplabv3) |✅| | ✅ | +| 图像 | 目标检测 | [res2net_faster_rcnn](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_faster_rcnn) |✅| ✅ | | +| 图像 | 目标检测 | [res2net_yolov3](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_yolov3) |✅| ✅ | | +| 图像 | 图像分类 | [res2net101](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | +| 图像 | 图像分类 | [res2net152](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | +| 图像 | 图像分类 | [res2net50](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | +| 图像 | 图像分类 | [ResNeSt50](https://gitee.com/mindspore/models/tree/master/research/cv/ResNeSt50) |✅| ✅ | | +| 图像 | 图像分类 | [resnet50_adv_pruning](https://gitee.com/mindspore/models/tree/master/research/cv/resnet50_adv_pruning) |✅| ✅ | | +| 图像 | 图像分类 | [resnet50_bam](https://gitee.com/mindspore/models/tree/master/research/cv/resnet50_bam) |✅| ✅ | | +| 图像 | 图像分类 | [ResNet50-Quadruplet](https://gitee.com/mindspore/models/tree/master/research/cv/metric_learn) |✅| ✅ | | +| 图像 | 图像分类 | [ResNet50-Triplet](https://gitee.com/mindspore/models/tree/master/research/cv/metric_learn) |✅| ✅ | | +| 图像 | 图像分类 | [ResnetV2_101](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | +| 图像 | 图像分类 | [ResnetV2_152](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | +| 图像 | 图像分类 | [ResnetV2_50](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | +| 图像 | 图像分类 | [resnetv2_50_frn](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2_50_frn) |✅| ✅ | | +| 图像 | 图像分类 | [resnext152_64x4d](https://gitee.com/mindspore/models/tree/master/research/cv/resnext152_64x4d) |✅| ✅ | | +| 图像 | 目标检测 | [retinaface_mobilenet0.25](https://gitee.com/mindspore/models/tree/master/research/cv/retinaface) |✅| ✅ | | +| 图像 | 目标检测 | [retinanet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet101) |✅| ✅ | | +| 图像 | 目标检测 | [retinanet_resnet152](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet152) |✅| ✅ | | +| 图像 | 目标检测 | [rfcn](https://gitee.com/mindspore/models/tree/master/research/cv/rfcn) | | ✅ | | +| 图像 | 图像分类 | [SE_ResNeXt50](https://gitee.com/mindspore/models/tree/master/research/cv/SE_ResNeXt50) |✅| | | +| 图像 | 图像分类 | [senet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [senet_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [se-res2net50](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | +| 图像 | 图像分类 | [S-GhostNet](https://gitee.com/mindspore/models/tree/master/research/cv/S-GhostNet) |✅| | | +| 图像 | 姿态估计 | [simple_baselines](https://gitee.com/mindspore/models/tree/master/research/cv/simple_baselines) |✅| ✅ | | +| 图像 | 图像生成 | [SinGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SinGAN) |✅| | | +| 图像 | 图像分类 | [single_path_nas](https://gitee.com/mindspore/models/tree/master/research/cv/single_path_nas) |✅| ✅ | | +| 图像 | 图像分类 | [sknet](https://gitee.com/mindspore/models/tree/master/research/cv/sknet) |✅| ✅ | ✅ | +| 图像 | 图像分类 | [snn_mlp](https://gitee.com/mindspore/models/tree/master/research/cv/snn_mlp) | | ✅ | | +| 图像 | 目标检测 | [Spnas](https://gitee.com/mindspore/models/tree/master/research/cv/Spnas) |✅| | | +| 图像 | 图像分类 | [SPPNet](https://gitee.com/mindspore/models/tree/master/research/cv/SPPNet) |✅| ✅ | | +| 图像 | 图像分类 | [squeezenet](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | +| 图像 | 图像超分 | [sr_ea](https://gitee.com/mindspore/models/tree/master/research/cv/sr_ea) |✅| | | +| 图像 | 图像超分 | [SRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SRGAN) |✅| ✅ | | +| 图像 | 图像分类 | [ssc_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/ssc_resnet50) |✅| ✅ | | +| 图像 | 目标检测 | [ssd_ghostnet](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_ghostnet) |✅| ✅ | ✅ | +| 图像 | 目标检测 | [ssd_inception_v2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_inception_v2) | | ✅ | ✅ | +| 图像 | 目标检测 | [ssd_inceptionv2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_inceptionv2) |✅| | | +| 图像 | 目标检测 | [ssd_mobilenetV2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2) |✅| ✅ | ✅ | +| 图像 | 目标检测 | [ssd_mobilenetV2_FPNlite](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2_FPNlite) |✅| ✅ | ✅ | +| 图像 | 目标检测 | [ssd_resnet_34](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet_34) | | ✅ | | +| 图像 | 目标检测 | [ssd_resnet34](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet34) |✅| | ✅ | +| 图像 | 目标检测 | [ssd_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet50) |✅| | | +| 图像 | 姿态估计 | [StackedHourglass](https://gitee.com/mindspore/models/tree/master/research/cv/StackedHourglass) |✅| | | +| 图像 | 图像生成 | [StarGAN](https://gitee.com/mindspore/models/tree/master/research/cv/StarGAN) |✅| ✅ | | +| 图像 | 图像生成 | [STGAN](https://gitee.com/mindspore/models/tree/master/research/cv/STGAN) |✅| ✅ | | +| 图像 | 交通预测 | [stgcn](https://gitee.com/mindspore/models/tree/master/research/cv/stgcn) |✅| ✅ | | +| 图像 | 时间定位 | [tall](https://gitee.com/mindspore/models/tree/master/research/cv/tall) |✅| | | +| 图像 | 图像分类 | [TCN](https://gitee.com/mindspore/models/tree/master/research/cv/TCN) |✅| ✅ | | +| 图像 | 文本检测 | [textfusenet](https://gitee.com/mindspore/models/tree/master/research/cv/textfusenet) |✅| | | +| 图像 | 交通预测 | [tgcn](https://gitee.com/mindspore/models/tree/master/research/cv/tgcn) |✅| ✅ | | +| 图像 | 图像分类 | [tinynet](https://gitee.com/mindspore/models/tree/master/research/cv/tinynet) | | ✅ | | +| 图像 | 图像分类 | [TNT](https://gitee.com/mindspore/models/tree/master/research/cv/TNT) |✅| ✅ | | +| 图像 | 目标检测 | [u2net](https://gitee.com/mindspore/models/tree/master/research/cv/u2net) |✅| ✅ | | +| 图像 | 图像生成 | [U-GAT-IT](https://gitee.com/mindspore/models/tree/master/research/cv/U-GAT-IT) |✅| ✅ | | +| 图像 | 语义分割 | [UNet3+](https://gitee.com/mindspore/models/tree/master/research/cv/UNet3+) |✅| ✅ | | +| 图像 | 重新识别 | [VehicleNet](https://gitee.com/mindspore/models/tree/master/research/cv/VehicleNet) |✅| | | +| 图像 | 图像分类 | [ViG](https://gitee.com/mindspore/models/tree/master/research/cv/ViG) |✅| ✅ | | +| 图像 | 图像分类 | [vit_cifar](https://gitee.com/mindspore/models/tree/master/research/cv/vit_base) |✅| ✅ | | +| 图像 | 语义分割 | [vnet](https://gitee.com/mindspore/models/tree/master/research/cv/vnet) |✅| ✅ | | +| 图像 | 图像分类 | [wave_mlp](https://gitee.com/mindspore/models/tree/master/research/cv/wave_mlp) |✅| ✅ | | +| 图像 | 图像超分 | [wdsr](https://gitee.com/mindspore/models/tree/master/research/cv/wdsr) |✅| ✅ | | +| 图像 | 图像分类 | [wideresnet](https://gitee.com/mindspore/models/tree/master/research/cv/wideresnet) |✅| ✅ | | +| 图像 | 实例分割 | [Yolact++](https://gitee.com/mindspore/models/tree/master/research/cv/Yolact++) |✅| | | +| 图像 | 目标检测 | [yolov3_tiny](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_tiny) |✅| ✅ | | +| 多模态 | 多模态 | [opt](https://gitee.com/mindspore/models/tree/master/research/mm/opt) |✅| ✅ | | +| 多模态 | 多模态 | [TokenFusion](https://gitee.com/mindspore/models/tree/master/research/cv/TokenFusion) |✅| ✅ | | +| 多模态 | 多模态 | [wukong](https://gitee.com/mindspore/models/tree/master/research/mm/wukong) |✅| | | +| 推荐 | 点击率预测 | [autodis](https://gitee.com/mindspore/models/tree/master/research/recommend/autodis) |✅| ✅ | | +| 推荐 | 点击率预测 | [DIEN](https://gitee.com/mindspore/models/tree/master/research/recommend/DIEN) |✅| ✅ | | +| 推荐 | 点击率预测 | [dlrm](https://gitee.com/mindspore/models/tree/master/research/recommend/dlrm) |✅| ✅ | | +| 推荐 | 点击率预测 | [EDCN](https://gitee.com/mindspore/models/tree/master/research/recommend/EDCN) |✅| ✅ | | +| 推荐 | 点击率预测 | [Fat-DeepFFM](https://gitee.com/mindspore/models/tree/master/research/recommend/Fat-DeepFFM) |✅| ✅ | | +| 推荐 | 点击率预测 | [mmoe](https://gitee.com/mindspore/models/tree/master/research/recommend/mmoe) |✅| ✅ | | +| 文本 | 自然语言理解 | [albert](https://gitee.com/mindspore/models/tree/master/research/nlp/albert) |✅| ✅ | | +| 文本 | 情绪分类 | [atae_lstm](https://gitee.com/mindspore/models/tree/master/research/nlp/atae_lstm) |✅| ✅ | | +| 文本 | 对话 | [dam](https://gitee.com/mindspore/models/tree/master/research/nlp/dam) |✅| | | +| 文本 | 语言模型 | [gpt2](https://gitee.com/mindspore/models/tree/master/research/nlp/gpt2) |✅| | | +| 文本 | 知识图嵌入 | [hake](https://gitee.com/mindspore/models/tree/master/research/nlp/hake) | | ✅ | | +| 文本 | 自然语言理解 | [ktnet](https://gitee.com/mindspore/models/tree/master/research/nlp/ktnet) |✅| ✅ | | +| 文本 | 命名实体识别 | [lstm_crf](https://gitee.com/mindspore/models/tree/master/research/nlp/lstm_crf) |✅| | | +| 文本 | 自然语言理解 | [luke](https://gitee.com/mindspore/models/tree/master/research/nlp/luke) |✅| ✅ | | +| 文本 | 知识图嵌入 | [rotate](https://gitee.com/mindspore/models/tree/master/research/nlp/rotate) |✅| ✅ | | +| 文本 | 情绪分类 | [senta](https://gitee.com/mindspore/models/tree/master/research/nlp/senta) |✅| ✅ | | +| 文本 | 机器翻译 | [seq2seq](https://gitee.com/mindspore/models/tree/master/research/nlp/seq2seq) |✅| | | +| 文本 | 词嵌入 | [skipgram](https://gitee.com/mindspore/models/tree/master/research/nlp/skipgram) |✅| ✅ | | +| 文本 | 机器翻译 | [speech_transformer](https://gitee.com/mindspore/models/tree/master/research/nlp/speech_transformer) |✅| | | +| 文本 | 预训练 | [ternarybert](https://gitee.com/mindspore/models/tree/master/research/nlp/ternarybert) |✅| ✅ | | +| 文本 | 自然语言理解 | [tprr](https://gitee.com/mindspore/models/tree/master/research/nlp/tprr) |✅| | | +| 文本 | 自然语言理解 | [transformer_xl](https://gitee.com/mindspore/models/tree/master/research/nlp/transformer_xl) |✅| ✅ | | +| 文本 | 知识图嵌入 | [transX](https://gitee.com/mindspore/models/tree/master/research/nlp/transX) | | ✅ | | +| 视频 | 视频分类 | [AttentionCluster](https://gitee.com/mindspore/models/tree/master/research/cv/AttentionCluster) |✅| ✅ | | +| 视频 | 其他 | [DYR](https://gitee.com/mindspore/models/tree/master/research/nlp/DYR) |✅| | | +| 视频 | 视频分类 | [ecolite](https://gitee.com/mindspore/models/tree/master/research/cv/ecolite) |✅| | | +| 视频 | 目标追踪 | [fairmot](https://gitee.com/mindspore/models/tree/master/research/cv/fairmot) |✅| ✅ | | +| 视频 | 视频分类 | [I3D](https://gitee.com/mindspore/models/tree/master/research/cv/I3D) |✅| | | +| 视频 | 目标追踪 | [JDE](https://gitee.com/mindspore/models/tree/master/research/cv/JDE) | | ✅ | | +| 视频 | 视频分割 | [OSVOS](https://gitee.com/mindspore/models/tree/master/research/cv/OSVOS) | | ✅ | | +| 视频 | 视频分类 | [r2plus1d](https://gitee.com/mindspore/models/tree/master/research/cv/r2plus1d) |✅| ✅ | | +| 视频 | 视频超分 | [rbpn](https://gitee.com/mindspore/models/tree/master/research/cv/rbpn) |✅| | | +| 视频 | 视频分类 | [resnet3d](https://gitee.com/mindspore/models/tree/master/research/cv/resnet3d) |✅| | | +| 视频 | 目标追踪 | [SiamFC](https://gitee.com/mindspore/models/tree/master/research/cv/SiamFC) |✅| | | +| 视频 | 目标追踪 | [siamRPN](https://gitee.com/mindspore/models/tree/master/research/cv/siamRPN) |✅| ✅ | | +| 视频 | 视频分类 | [slowfast](https://gitee.com/mindspore/models/tree/master/research/cv/slowfast) |✅| ✅ | | +| 视频 | 视频分类 | [stnet](https://gitee.com/mindspore/models/tree/master/research/cv/stnet) |✅| | | +| 视频 | 目标追踪 | [tracktor](https://gitee.com/mindspore/models/tree/master/research/cv/tracktor) | | ✅ | | +| 视频 | 目标追踪 | [tracktor++](https://gitee.com/mindspore/models/tree/master/research/cv/tracktor++) |✅| ✅ | | +| 视频 | 视频分类 | [trn](https://gitee.com/mindspore/models/tree/master/research/cv/trn) | | ✅ | | +| 视频 | 视频分类 | [tsm](https://gitee.com/mindspore/models/tree/master/research/cv/tsm) |✅| ✅ | | +| 视频 | 视频分类 | [tsn](https://gitee.com/mindspore/models/tree/master/research/cv/tsn) |✅| ✅ | | + -- Gitee From 2e12e2680ea673589e8616fe7137420b0e559da2 Mon Sep 17 00:00:00 2001 From: vigo999 Date: Fri, 2 Jun 2023 14:41:14 +0800 Subject: [PATCH 3/4] modify readme --- README.md | 661 +++--------------------------------------- README_CN.md | 246 +++++----------- official/README.md | 116 ++++++++ official/README_CN.md | 116 ++++++++ research/README.md | 314 +------------------- 5 files changed, 341 insertions(+), 1112 deletions(-) create mode 100644 official/README.md create mode 100644 official/README_CN.md diff --git a/README.md b/README.md index fd6bdabaf..39235ba2e 100644 --- a/README.md +++ b/README.md @@ -1,652 +1,67 @@ # ![MindSpore Logo](https://gitee.com/mindspore/mindspore/raw/master/docs/MindSpore-logo.png) -## 欢迎来到MindSpore ModelZoo +## Welcome to the Model Zoo for MindSpore -MindSpore models仓中提供了不同任务领域，经典的SOTA模型实现和端到端解决方案。目的是方便MindSpore用户更加方便的利用MindSpore进行研究和产品开发。 +The MindSpore models repository provides different task domains, classic SOTA model implementations and end-to-end solutions. The purpose is to make it easier for MindSpore users to use MindSpore for research and product development. -为了让开发者更好地体验MindSpore框架优势，我们将陆续增加更多的典型网络和相关预训练模型。如果您对ModelZoo有任何需求，请通过[Gitee](https://gitee.com/mindspore/mindspore/issues)或[MindSpore](https://bbs.huaweicloud.com/forum/forum-1076-1.html)与我们联系，我们将及时处理。 +In order to facilitate developers to enjoy the benefits of MindSpore framework, we will continue to add typical networks and some of the related pre-trained models. If you have needs for the model zoo, you can file an issue on [gitee](https://gitee.com/mindspore/mindspore/issues) or [MindSpore](https://bbs.huaweicloud.com/forum/forum-1076-1.html), We will consider it in time. -| 目录 | 描述 | -|------------------------| ------------------------------------------------------------ | -| [official](official) | • 官方维护，随MindSpore版本迭代更新，保证版本出口网络的精度效果
• 推荐写法，使用最新的MindSpore接口和推荐使用的特性，在保证代码可读性的基础上，有更快的性能表现
• 有详细的网络信息和说明文档，包含但不限于模型说明，数据集使用，规格支持，精度性能数据，网络checkpoint文件，MindIR文件等 | -| [research](research) | • 历史支持，测试验收通过的模型，在README里标明支持的MindSpore版本
• 按需维护，内容不会随版本迭代更新，只会适配对应的接口变更，由MindSpore开发人员进行维护支持，按需进行维护升级
• 提供较为详细的网络信息和说明文档，包含但不限于模型说明，数据集使用，规格支持，精度数据，网络checkpoint文件，MindIR文件等 | -| [community](community) | • 生态开发者贡献模型 | +| Directory | Description | +|-------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| +| [official](official) | • A collections of SOTA models implemented by MindSpore Latest API
• Maintained by MindSpore Team | +| [research](research) | • A collections of research models implemented by researchers and institution
• Maintained by researchers and institution | +| [community](community) | • A list of github/gitee repos of toolkit/models powered by MindSpore versions in the README
• Model file is not necessarily provided | -- 使用最新MindSpore API的SOTA模型 -- MindSpore优势 +## Disclaimers -- 官方维护和支持 +Mindspore only provides scripts that downloads and preprocesses public datasets. We do not own these datasets and are not responsible for their quality or maintenance. Please make sure you have permission to use the dataset under the dataset’s license. The models trained on these dataset are for non-commercial research and educational purpose only. -## 标准网络 -## Computer Vision -### Image Classification +To dataset owners: we will remove or update all public content upon request if you don’t want your dataset included on Mindspore, or wish to update it in any way. Please contact us through a Github/Gitee issue. Your understanding and contribution to this community is greatly appreciated. -| model | acc@1 | bs | cards | ms/step | amp | mindcv_config | acc@1 | bs | cards | ms/step | amp | vannila mindspore -:-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | -| vgg11| 71.86 | 32 | 8 | 61.63 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | | | | | | | -| vgg13| 72.87 | 32 | 8 | 66.47 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | | | | | | | -| vgg16| 74.61 | 32 | 8 | 73.68 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | uploading | uploading | uploading | uploading | uploading | [config](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/vgg16) | -| vgg19| 75.21 | 32 | 8 | 81.13 | O2 | [cconfig](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | uploading | uploading | uploading | uploading | uploading | [config](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/vgg19) | -| resnet18| 70.21 | 32 | 8 | 23.98 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | -| resnet34| 74.15 | 32 | 8 | 23.98 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | -| resnet50| 76.69 | 32 | 8 | 31.97 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | -| resnet101| 78.24 | 32 | 8 | 50.76 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | -| resnet152| 78.72 | 32 | 8 | 70.94 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | -| resnetv2_50| 76.90 | 32 | 8 | 35.72 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnetv2) | -| resnetv2_101| 78.48 | 32 | 8 | 56.02 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnetv2) | -| dpn92 | 79.46 | 32 | 8 | 79.89 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | -| dpn98 | 79.94 | 32 | 8 | 106.60 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | -| dpn107 | 80.05 | 32 | 8 | 107.60 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | -| dpn131 | 80.07 | 32 | 8 | 143.57 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | -| densenet121 | 75.64 | 32 | 8 | 48.07 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | -| densenet161 | 79.09 | 32 | 8 | 115.11 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | -| densenet169 | 77.26 | 32 | 8 | 73.14 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | -| densenet201 | 78.14 | 32 | 8 | 96.12 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | -| seresnet18 | 71.81 | 64 | 8 | 50.39 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | -| seresnet34 | 75.36 | 64 | 8 | 50.54 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | -| seresnet50 | 78.31 | 64 | 8 | 98.37 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | -| seresnext26 | 77.18 | 64 | 8 | 73.72 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | -| seresnext50 | 78.71 | 64 | 8 | 113.82 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | -| skresnet18 | 73.09 | 64 | 8 | 65.95 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | -| skresnet34 | 76.71 | 32 | 8 | 43.96 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | -| skresnet50_32x4d | 79.08 | 64 | 8 | 65.95 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | -| resnext50_32x4d | 78.53 | 32 | 8 | 50.25 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | -| resnext101_32x4d | 79.83 | 32 | 8 | 68.85 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | -| resnext101_64x4d | 80.30 | 32 | 8 | 112.48 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | -| resnext152_64x4d | 80.52 | 32 | 8 | 157.06 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | -| rexnet_x09 | 77.07 | 64 | 8 | 145.08 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | -| rexnet_x10 | 77.38 | 64 | 8 | 156.67 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | -| rexnet_x13 | 79.06 | 64 | 8 | 203.04 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | -| rexnet_x15 | 79.94 | 64 | 8 | 231.41 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | -| rexnet_x20 | 80.64 | 64 | 8 | 308.15 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | -| resnest50 | 80.81 | 128 | 8 | 376.18 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnest) | -| resnest101 | 82.50 | 128 | 8 | 719.84 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnest) | -| res2net50 | 79.35 | 32 | 8 | 49.16 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | -| res2net101 | 79.56 | 32 | 8 | 49.96 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | -| res2net50_v1b | 80.32 | 32 | 8 | 93.33 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | -| res2net101_v1b | 95.41 | 32 | 8 | 86.93 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | -| googlenet | 72.68 | 32 | 8 | 23.26 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/googlenet) | -| inceptionv3 | 79.11 | 32 | 8 | 49.96 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inceptionv3) | -| inceptionv4 | 80.88 | 32 | 8 | 93.33 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inceptionv4) | -| mobilenet_v1_025 | 53.87 | 64 | 8 | 75.93 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | -| mobilenet_v1_050 | 65.94 | 64 | 8 | 51.96 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | -| mobilenet_v1_075 | 70.44 | 64 | 8 | 57.55 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | -| mobilenet_v1_100 | 72.95 | 64 | 8 | 44.04 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | -| mobilenet_v2_075 | 69.98 | 256 | 8 | 169.81 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | -| mobilenet_v2_100 | 72.27 | 256 | 8 | 195.06 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | -| mobilenet_v2_140 | 75.56 | 256 | 8 | 230.06 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | -| mobilenet_v3_small | 68.10 | 75 | 8 | 67.19 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv3) | -| mobilenet_v3_large | 75.23 | 75 | 8 | 85.61 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv3) | -| shufflenet_v1_g3_x0_5 | 57.05 | 64 | 8 | 142.69 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv1) | -| shufflenet_v1_g3_x1_5 | 67.77 | 64 | 8 | 267.79 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv1) | -| shufflenet_v2_x0_5 | 57.05 | 64 | 8 | 142.69 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv2) | -| shufflenet_v2_x1_0 | 67.77 | 64 | 8 | 267.79 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv2) | -| shufflenet_v2_x1_5 | 57.05 | 64 | 8 | 142.69 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv2) | -| shufflenet_v2_x2_0 | 67.77 | 64 | 8 | 267.79 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv2) | -| xception | 79.01 | 32 | 8 | 98.03 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/xception) | -| ghostnet_50 | 66.03 | 128 | 8 | 220.88 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | -| ghostnet_100 | 73.78 | 128 | 8 | 222.67 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | -| ghostnet_130 | 75.50 | 128 | 8 | 223.11 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | -| nasnet_a_4x1056 | 73.65 | 256 | 8 | 1562.35 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/nasnet) | -| mnasnet_0.5 | 68.07 | 512 | 8 | 367.05 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | -| mnasnet_0.75 | 71.81 | 256 | 8 | 151.02 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | -| mnasnet_1.0 | 74.28 | 256 | 8 | 153.52 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | -| mnasnet_1.4 | 76.01 | 256 | 8 | 194.90 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | -| efficientnet_b0 | 76.89 | 128 | 8 | 276.77 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/efficientnet) | -| efficientnet_b1 | 78.95 | 128 | 8 | 435.90 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/efficientnet) | -| regnet_x_200mf| 68.74 | 64 | 8 | 47.56 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | -| regnet_x_400mf| 73.16 | 64 | 8 | 47.56 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | -| regnet_x_600mf| 73.34 | 64 | 8 | 48.36 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | -| regnet_x_800mf| 76.04 | 64 | 8 | 47.56 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | -| regnet_y_200mf| 70.30 | 64 | 8 | 58.35 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | -| regnet_y_400mf| 73.91 | 64 | 8 | 77.94 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | -| regnet_y_600mf| 75.69 | 64 | 8 | 79.94 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | -| regnet_y_800mf| 76.52 | 64 | 8 | 81.93 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | -| mixnet_s | 75.52 | 128 | 8 | 340.18 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | -| mixnet_m | 76.64 | 128 | 8 | 384.68 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | -| mixnet_l | 78.73 | 128 | 8 | 389.97 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | -| hrnet_w32 | 80.64 | 128 | 8 | 335.73 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/hrnet) | -| hrnet_w48 | 81.19 | 128 | 8 | 463.63 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/hrnet) | -| bit_resnet50 | 76.81 | 32 | 8 | 130.60 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | -| bit_resnet50x3 | 80.63 | 32 | 8 | 533.09 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | -| bit_resnet101 | 77.93| 16 | 8 | 128.15 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | -| repvgg_a0 | 72.19 | 32 | 8 | 27.63 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | -| repvgg_a1 | 74.19 | 32 | 8 | 27.45 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | -| repvgg_a2 | 76.63 | 32 | 8 | 39.79 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | -| repvgg_b0 | 74.99 | 32 | 8 | 33.05 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | -| repvgg_b1 | 78.81 | 32 | 8 | 68.88 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | -| repvgg_b2 | 79.29 | 32 | 8 | 106.90 | O0 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | -| repvgg_b3 | 80.46 | 32 | 8 | 137.24 | O0| [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | -| repvgg_b1g2 | 78.03 | 32 | 8 | 59.71 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | -| repvgg_b1g4 | 77.64 | 32 | 8 | 65.83 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | -| repvgg_b2g4 | 78.80 | 32 | 8 | 89.57 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | -| repmlp_t224 | 76.71 | 128 | 8 | 973.88 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repmlp) | -| convnext_tiny | 81.91 | 128 | 8 | 343.21 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | -| convnext_small | 83.40 | 128 | 8 | 405.96 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | -| convnext_base | 83.32 | 128 | 8 | 531.10 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | -| vit_b_32_224 | 75.86 | 256 | 8 | 623.09 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | -| vit_l_16_224 | 76.34| 48 | 8 | 613.98 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | -| vit_l_32_224 | 73.71 | 128 | 8 | 527.58 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | -| swintransformer_tiny | 80.82 | 256 | 8 | 1765.65 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/swintransformer) | -| pvt_tiny | 74.81 | 128 | 8 | 310.74 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | -| pvt_small | 79.66 | 128 | 8 | 431.15 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | -| pvt_medium | 81.82 | 128 | 8 | 613.08 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | -| pvt_large | 81.75 | 128 | 8 | 860.41 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | -| pvt_v2_b0 | 71.50 | 128 | 8 | 338.78 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | -| pvt_v2_b1 | 78.91 | 128 | 8 | 337.94 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | -| pvt_v2_b2 | 81.99 | 128 | 8 | 503.79 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | -| pvt_v2_b3 | 82.84 | 128 | 8 | 738.90 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | -| pvt_v2_b4 | 83.14 | 128 | 8 | 1030.06 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | -| pit_ti | 72.96 | 128 | 8 | 339.44 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | -| pit_xs | 78.41 | 128 | 8 | 338.70 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | -| pit_s | 80.56 | 128 | 8 | 336.08 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | -| pit_b | 81.87 | 128 | 8 | 350.33 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | -| coat_lite_tiny | 77.35 | 64 | 8 | 258.07 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | -| coat_lite_mini | 78.51 | 64 | 8 | 265.44 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | -| coat_tiny | 79.67 | 64 | 8 | 580.54 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | -| convit_tiny | 73.66 | 256 | 8 | 388.80 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | -| convit_tiny_plus | 77.00 | 256 | 8 | 393.60 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | -| convit_small | 81.63 | 192 | 8 | 588.73 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | -| convit_small_plus | 81.80 | 192 | 8 | 665.74 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | -| convit_base | 82.10 | 128 | 8 | 701.84 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | -| convit_base_plus | 81.96 | 128 | 8 | 983.21 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | -| crossvit_9 | 73.56 | 256 | 8 | 685.25 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | -| crossvit_15 | 81.08 | 256 | 8 | 1086.00 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | -| crossvit_18 | 81.93 | 256 | 8 | 1137.60 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | -| mobilevit_xx_small | 68.90 | uploading | uploading |uploading | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | -| mobilevit_x_small | 74.98 | uploading | uploading | uploading | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | -| mobilevit_small | 78.48 | uploading | uploading | uploading | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | -| visformer_tiny | 78.28 | 128 | 8 | 393.29 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | -| visformer_tiny_v2 | 78.82 | 256 | 8 | 627.20 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | -| visformer_small | 81.76 | 64 | 8 | 155.88 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | -| visformer_small_v2 | 82.17 | 64 | 8 | 158.27 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | -| edgenext_xx_small | 71.02 | 256 | 8 | 1207.78 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | -| edgenext_x_small | 75.14 | 256 | 8 | 1961.42 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | -| edgenext_small | 79.15 | 256 | 8 | 882.00 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | -| edgenext_base | 82.24 | 256 | 8 | 1151.98 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | -| poolformer_s12 | 77.33 | 128 | 8 | 316.77 | O3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/poolformer) | -| xcit_tiny_12_p16 | 77.67 | 128 | 8 | 352.30 | O2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/xcit) | -| volo_d1 | 81.82 | 128 | 8 | 575.54 | O3 | uploading | -| cait_s24 | 82.25 | 64 | 8 | 435.54 | O2 | uploading | +MindSpore is Apache 2.0 licensed. Please see the LICENSE file. +## License -| 领域 | 子领域 | 网络 | Ascend | GPU | CPU | -|:------ |:------| :----------- |:------: |:------: |:-----: | -| 语音 | 声纹识别 | [ecapa_tdnn](https://gitee.com/mindspore/models/tree/master/official/audio/EcapaTDNN) |✅| | | -| 语音 | 语音合成 | [lpcnet](https://gitee.com/mindspore/models/tree/master/official/audio/LPCNet) |✅| ✅ | | -| 语音 | 语音合成 | [melgan](https://gitee.com/mindspore/models/tree/master/official/audio/MELGAN) |✅| ✅ | | -| 语音 | 语音合成 | [tacotron2](https://gitee.com/mindspore/models/tree/master/official/audio/Tacotron2) |✅| | | - -| 图神经网络 | 文本分类 | [gcn](https://gitee.com/mindspore/models/tree/master/official/gnn/GCN) |✅| ✅ | | -| 推荐 | 推荐系统 | [naml](https://gitee.com/mindspore/models/tree/master/research/recommend/naml) |✅| ✅ | | -| 推荐 | 推荐系统 | [ncf](https://gitee.com/mindspore/models/tree/master/research/recommend/ncf) |✅| ✅ | | -| 推荐 | 推荐系统 | [tbnet](https://gitee.com/mindspore/models/tree/master/official/recommend/Tbnet) |✅| ✅ | | -| 图像 | 图像去噪 | [brdnet](https://gitee.com/mindspore/models/tree/master/research/cv/brdnet) |✅| | | -| 图像 | 目标检测 | [centerface](https://gitee.com/mindspore/models/tree/master/research/cv/centerface) |✅| ✅ | ✅ | -| 图像 | 文本识别 | [cnnctc](https://gitee.com/mindspore/models/tree/master/research/cv/cnnctc) |✅| ✅ | ✅ | -| 图像 | 文本识别 | [crnn](https://gitee.com/mindspore/models/tree/master/official/cv/CRNN) |✅| ✅ | ✅ | -| 图像 | 文本识别 | [crnn_seq2seq_ocr](https://gitee.com/mindspore/models/tree/master/research/cv/crnn_seq2seq_ocr) |✅| | | -| 图像 | 目标检测 | [ctpn](https://gitee.com/mindspore/models/tree/master/official/cv/CTPN) |✅| ✅ | | -| 图像 | 目标检测 | [darknet53](https://gitee.com/mindspore/models/tree/master/research/cv/darknet53) | | ✅ | | -| 图像 | 文本检测 | [dbnet](https://gitee.com/mindspore/models/tree/master/official/cv/DBNet) |✅| ✅ | ✅ | -| 图像 | 语义分割 | [deeplabv3](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabV3P) |✅| ✅ | ✅ | -| 图像 | 文本检测 | [deeptext](https://gitee.com/mindspore/models/tree/master/official/cv/DeepText) |✅| ✅ | | -| 图像 | 深度估计 | [depthnet](https://gitee.com/mindspore/models/tree/master/official/cv/DepthNet) |✅| | | -| 图像 | 图像去噪 | [dncnn](https://gitee.com/mindspore/models/tree/master/research/cv/dncnn) | | ✅ | | -| 图像 | 文本检测 | [east](https://gitee.com/mindspore/models/tree/master/research/cv/east) |✅| ✅ | | -| 图像 | 文本识别 | [essay-recogination](https://gitee.com/mindspore/models/tree/master/research/cv/essay-recogination) | | ✅ | | -| 图像 | 目标检测 | [FasterRCNN_Inception_Resnetv2](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| 图像 | 目标检测 | [FasterRCNN_ResNetV1.5_50](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| 图像 | 目标检测 | [FasterRCNN_ResNetV1_101](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| 图像 | 目标检测 | [FasterRCNN_ResNetV1_152](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| 图像 | 目标检测 | [FasterRCNN_ResNetV1_50](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) |✅| ✅ | | -| 图像 | 语义分割 | [fastscnn](https://gitee.com/mindspore/models/tree/master/research/cv/fastscnn) |✅| | | -| 图像 | 语义分割 | [FCN8s](https://gitee.com/mindspore/models/tree/master/research/cv/FCN8s) |✅| ✅ | | -| 图像 | 图像分类 | [inceptionv3](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv3) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [inceptionv4](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv4) |✅| ✅ | ✅ | -| 图像 | 图像去噪 | [LearningToSeeInTheDark](https://gitee.com/mindspore/models/tree/master/research/cv/LearningToSeeInTheDark) |✅| | | -| 图像 | 图像分类 | [lenet](https://gitee.com/mindspore/models/tree/master/research/cv/lenet) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [maskrcnn_resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/MaskRCNN/maskrcnn_resnet50) |✅| ✅ | | -| 图像 | 目标检测 | [maskrcnn_mobilenetv1](https://gitee.com/mindspore/models/tree/master/official/cv/MaskRCNN/maskrcnn_mobilenetv1) |✅| ✅ | ✅ | -| 图像 | 人群计数 | [MCNN](https://gitee.com/mindspore/models/tree/master/research/cv/MCNN) |✅| ✅ | | -| 图像 | 图像分类 | [mobilenetv1](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv1) |✅| ✅ | | -| 图像 | 图像分类 | [mobilenetv2](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv2) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [mobilenetv3](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv3) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [nasnet](https://gitee.com/mindspore/models/tree/master/research/cv/nasnet) |✅| ✅ | | -| 图像 | 图像质量评估 | [nima](https://gitee.com/mindspore/models/tree/master/research/cv/nima) |✅| ✅ | | -| 图像 | 点云模型 | [octsqueeze](https://gitee.com/mindspore/models/tree/master/official/cv/OctSqueeze) |✅| ✅ | | -| 图像 | 关键点检测 | [openpose](https://gitee.com/mindspore/models/tree/master/official/cv/OpenPose) |✅| | | -| 图像 | 缺陷检测 | [patchcore](https://gitee.com/mindspore/models/tree/master/official/cv/PatchCore) |✅| ✅ | | -| 图像 | 相机重定位 | [posenet](https://gitee.com/mindspore/models/tree/master/research/cv/PoseNet) |✅| ✅ | | -| 图像 | 视频预测学习 | [predrnn++](https://gitee.com/mindspore/models/tree/master/research/cv/predrnn++) |✅| | | -| 图像 | 文本检测 | [psenet](https://gitee.com/mindspore/models/tree/master/research/cv/psenet) |✅| ✅ | | -| 图像 | 姿态估计 | [pvnet](https://gitee.com/mindspore/models/tree/master/official/cv/PVNet) |✅| | | -| 图像 | 光流估计 | [pwcnet](https://gitee.com/mindspore/models/tree/master/official/cv/PWCNet) |✅| ✅ | | -| 图像 | 图像超分 | [RDN](https://gitee.com/mindspore/models/tree/master/research/cv/RDN) |✅| ✅ | | -| 图像 | 图像分类 | [resnet101](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [resnet152](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [resnet18](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [resnet34](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [resnet50_thor](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | | -| 图像 | 图像分类 | [resnext101](https://gitee.com/mindspore/models/tree/master/official/cv/ResNeXt) |✅| ✅ | | -| 图像 | 图像分类 | [resnext50](https://gitee.com/mindspore/models/tree/master/official/cv/ResNeXt) |✅| ✅ | | -| 图像 | 目标检测 | [retinaface_resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/RetinaFace_ResNet50) | | ✅ | | -| 图像 | 目标检测 | [retinanet](https://gitee.com/mindspore/models/tree/master/official/cv/RetinaNet) |✅| ✅ | | -| 图像 | 图像分类 | [se_resnext50](https://gitee.com/mindspore/models/tree/master/research/cv/SE_ResNeXt50) |✅| | | -| 图像 | 图像抠图 | [semantic_human_matting](https://gitee.com/mindspore/models/tree/master/official/cv/SemanticHumanMatting) |✅| | | -| 图像 | 图像分类 | [se-resnet50](https://gitee.com/mindspore/models/tree/master/official/cv/ResNet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [shufflenetv1](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv1) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [shufflenetv2](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv2) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [simclr](https://gitee.com/mindspore/models/tree/master/research/cv/simclr) |✅| ✅ | | -| 图像 | 关键点检测 | [simple_pose](https://gitee.com/mindspore/models/tree/master/research/cv/simple_pose) |✅| ✅ | | -| 图像 | 目标检测 | [sphereface](https://gitee.com/mindspore/models/tree/master/research/cv/sphereface) |✅| ✅ | | -| 图像 | 图像分类 | [squeezenet](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | -| 图像 | 图像分类 | [SqueezeNet_Residual](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | -| 图像 | 图像超分 | [srcnn](https://gitee.com/mindspore/models/tree/master/research/cv/srcnn) |✅| ✅ | | -| 图像 | 目标检测 | [ssd_mobilenet-v1-fpn](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd_mobilenet-v2](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd-resnet50-fpn](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd-vgg16](https://gitee.com/mindspore/models/tree/master/official/cv/SSD) |✅| ✅ | ✅ | -| 图像 | 缺陷检测 | [ssim-ae](https://gitee.com/mindspore/models/tree/master/official/cv/SSIM-AE) |✅| | | -| 图像 | 图像分类 | [tinydarknet](https://gitee.com/mindspore/models/tree/master/research/cv/tinydarknet) |✅| ✅ | ✅ | -| 图像 | 语义分割 | [UNet_nested](https://gitee.com/mindspore/models/tree/master/official/cv/Unet) |✅| ✅ | | -| 图像 | 语义分割 | [unet2d](https://gitee.com/mindspore/models/tree/master/official/cv/Unet) |✅| ✅ | | -| 图像 | 语义分割 | [unet3d](https://gitee.com/mindspore/models/tree/master/official/cv/Unet3d) |✅| ✅ | | -| 图像 | 图像分类 | [vgg16](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/vgg16) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [vit](https://gitee.com/mindspore/models/tree/master/official/cv/VIT) |✅| ✅ | | -| 图像 | 文本识别 | [warpctc](https://gitee.com/mindspore/models/tree/master/research/cv/warpctc) |✅| ✅ | | -| 图像 | 图像分类 | [xception](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/xception) |✅| ✅ | | -| 图像 | 目标检测 | [yolov3_darknet53](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv3) |✅| ✅ | | -| 图像 | 目标检测 | [yolov3_resnet18](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_resnet18) |✅| | | -| 图像 | 目标检测 | [yolov4](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv4) |✅| | | -| 图像 | 目标检测 | [yolov5s](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv5) |✅| ✅ | | -| 推荐 | 点击率预测 | [deep_and_cross](https://gitee.com/mindspore/models/tree/master/research/recommend/deep_and_cross) | | ✅ | | -| 推荐 | 点击率预测 | [deepfm](https://gitee.com/mindspore/models/tree/master/official/recommend/DeepFM) |✅| ✅ | | -| 推荐 | 点击率预测 | [fibinet](https://gitee.com/mindspore/models/tree/master/research/recommend/fibinet) | | ✅ | | -| 推荐 | 点击率预测 | [wide_and_deep](https://gitee.com/mindspore/models/tree/master/official/recommend/Wide_and_Deep) |✅| ✅ | | -| 推荐 | 点击率预测 | [wide_and_deep_multitable](https://gitee.com/mindspore/models/tree/master/official/recommend/Wide_and_Deep_Multitable) |✅| ✅ | | -| 文本 | 自然语言理解 | [bert_base](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | -| 文本 | 自然语言理解 | [bert_bilstm_crf](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | -| 文本 | 自然语言理解 | [bert_finetuning](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | -| 文本 | 自然语言理解 | [bert_large](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| | | -| 文本 | 自然语言理解 | [bert_nezha](https://gitee.com/mindspore/models/tree/master/official/nlp/Bert) |✅| ✅ | | -| 文本 | 自然语言理解 | [cpm](https://gitee.com/mindspore/models/tree/master/research/nlp/cpm) |✅| ✅ | | -| 文本 | 对话 | [dgu](https://gitee.com/mindspore/models/tree/master/research/nlp/dgu) |✅| ✅ | | -| 文本 | 对话 | [duconv](https://gitee.com/mindspore/models/tree/master/research/nlp/duconv) |✅| ✅ | | -| 文本 | 情绪分类 | [emotect](https://gitee.com/mindspore/models/tree/master/research/nlp/emotect) |✅| ✅ | | -| 文本 | 自然语言理解 | [ernie](https://gitee.com/mindspore/models/tree/master/research/nlp/ernie) |✅| ✅ | | -| 文本 | 自然语言理解 | [fasttext](https://gitee.com/mindspore/models/tree/master/research/nlp/fasttext) |✅| ✅ | | -| 文本 | 自然语言理解 | [gnmt_v2](https://gitee.com/mindspore/models/tree/master/research/nlp/gnmt_v2) |✅| ✅ | | -| 文本 | 自然语言理解 | [gpt3](https://gitee.com/mindspore/models/tree/master/official/nlp/GPT) |✅| | | -| 文本 | 自然语言理解 | [gru](https://gitee.com/mindspore/models/tree/master/official/nlp/GRU) |✅| ✅ | | -| 文本 | 情绪分类 | [lstm](https://gitee.com/mindspore/models/tree/master/official/nlp/LSTM) |✅| ✅ | | -| 文本 | 自然语言理解 | [mass](https://gitee.com/mindspore/models/tree/master/research/nlp/mass) |✅| ✅ | | -| 文本 | 预训练 | [pangu_alpha](https://gitee.com/mindspore/models/tree/master/official/nlp/Pangu_alpha) |✅| ✅ | | -| 文本 | 自然语言理解 | [textcnn](https://gitee.com/mindspore/models/tree/master/research/nlp/textcnn) |✅| ✅ | | -| 文本 | 自然语言理解 | [tinybert](https://gitee.com/mindspore/models/tree/master/research/nlp/tinybert) |✅| ✅ | | -| 文本 | 自然语言理解 | [transformer](https://gitee.com/mindspore/models/tree/master/official/nlp/Transformer) |✅| ✅ | | -| 视频 | 目标追踪 | [ADNet](https://gitee.com/mindspore/models/tree/master/research/cv/ADNet) |✅| | | -| 视频 | 视频分类 | [c3d](https://gitee.com/mindspore/models/tree/master/official/cv/C3D) |✅| ✅ | | -| 视频 | 目标追踪 | [Deepsort](https://gitee.com/mindspore/models/tree/master/research/cv/Deepsort) |✅| ✅ | | - -### 研究网络 - -| 领域 | 子领域 | 网络 | Ascend | GPU | CPU | -|:------ |:------| :----------- |:------: |:------: |:-----: | -| 3D | 三维重建 | [cmr](https://gitee.com/mindspore/models/tree/master/research/cv/cmr) | | ✅ | | -| 3D | 三维重建 | [DecoMR](https://gitee.com/mindspore/models/tree/master/research/cv/DecoMR) | | ✅ | | -| 3D | 三维重建 | [DeepLM](https://gitee.com/mindspore/models/tree/master/research/3d/DeepLM) | | ✅ | | -| 3D | 三维重建 | [eppmvsnet](https://gitee.com/mindspore/models/tree/master/research/cv/eppmvsnet) | | ✅ | | -| 3D | 三维物体检测 | [pointpillars](https://gitee.com/mindspore/models/tree/master/research/cv/pointpillars) |✅| ✅ | | -| 语音 | 语音识别 | [ctcmodel](https://gitee.com/mindspore/models/tree/master/research/audio/ctcmodel) |✅| | | -| 语音 | 语音识别 | [deepspeech2](https://gitee.com/mindspore/models/tree/master/official/audio/DeepSpeech2) | | ✅ | | -| 语音 | 语音唤醒 | [dscnn](https://gitee.com/mindspore/models/tree/master/research/audio/dscnn) |✅| ✅ | | -| 语音 | 语音合成 | [FastSpeech](https://gitee.com/mindspore/models/tree/master/research/audio/FastSpeech) | | ✅ | | -| 语音 | 语音标注 | [fcn-4](https://gitee.com/mindspore/models/tree/master/research/audio/fcn-4) |✅| ✅ | | -| 语音 | 语音识别 | [jasper](https://gitee.com/mindspore/models/tree/master/research/audio/jasper) |✅| ✅ | | -| 语音 | 语音合成 | [wavenet](https://gitee.com/mindspore/models/tree/master/research/audio/wavenet) |✅| ✅ | | -| 图神经网络 | 图分类 | [dgcn](https://gitee.com/mindspore/models/tree/master/research/gnn/dgcn) |✅| | | -| 图神经网络 | 文本分类 | [hypertext](https://gitee.com/mindspore/models/tree/master/research/nlp/hypertext) |✅| ✅ | | -| 图神经网络 | 图分类 | [sdne](https://gitee.com/mindspore/models/tree/master/research/gnn/sdne) |✅| | | -| 图神经网络 | 社会和信息网络 | [sgcn](https://gitee.com/mindspore/models/tree/master/research/gnn/sgcn) |✅| ✅ | | -| 图神经网络 | 文本分类 | [textrcnn](https://gitee.com/mindspore/models/tree/master/research/nlp/textrcnn) |✅| ✅ | | -| 高性能计算 | 高性能计算 | [deepbsde](https://gitee.com/mindspore/models/tree/master/research/hpc/deepbsde) | | ✅ | | -| 高性能计算 | 高性能计算 | [molecular_dynamics](https://gitee.com/mindspore/models/tree/master/research/hpc/molecular_dynamics) |✅| | | -| 高性能计算 | 高性能计算 | [ocean_model](https://gitee.com/mindspore/models/tree/master/research/hpc/ocean_model) | | ✅ | | -| 高性能计算 | 高性能计算 | [pafnucy](https://gitee.com/mindspore/models/tree/master/research/hpc/pafnucy) |✅| ✅ | | -| 高性能计算 | 高性能计算 | [pfnn](https://gitee.com/mindspore/models/tree/master/research/hpc/pfnn) | | ✅ | | -| 高性能计算 | 高性能计算 | [pinns](https://gitee.com/mindspore/models/tree/master/research/hpc/pinns) | | ✅ | | -| 图像 | 图像分类 | [3D_DenseNet](https://gitee.com/mindspore/models/tree/master/research/cv/3D_DenseNet) |✅| ✅ | | -| 图像 | 语义分割 | [3dcnn](https://gitee.com/mindspore/models/tree/master/research/cv/3dcnn) |✅| ✅ | | -| 图像 | 语义分割 | [adelaide_ea](https://gitee.com/mindspore/models/tree/master/research/cv/adelaide_ea) |✅| | | -| 图像 | 文本检测 | [advanced_east](https://gitee.com/mindspore/models/tree/master/research/cv/advanced_east) |✅| ✅ | | -| 图像 | 风格转移 | [aecrnet](https://gitee.com/mindspore/models/tree/master/research/cv/aecrnet) |✅| ✅ | | -| 图像 | 重新识别 | [AlignedReID](https://gitee.com/mindspore/models/tree/master/research/cv/AlignedReID) | | ✅ | | -| 图像 | 重新识别 | [AlignedReID++](https://gitee.com/mindspore/models/tree/master/research/cv/AlignedReID++) |✅| ✅ | | -| 图像 | 姿态估计 | [AlphaPose](https://gitee.com/mindspore/models/tree/master/research/cv/AlphaPose) |✅| | | -| 图像 | 风格转移 | [APDrawingGAN](https://gitee.com/mindspore/models/tree/master/research/cv/APDrawingGAN) |✅| ✅ | | -| 图像 | 风格转移 | [ArbitraryStyleTransfer](https://gitee.com/mindspore/models/tree/master/research/cv/ArbitraryStyleTransfer) |✅| ✅ | | -| 图像 | 目标检测 | [arcface](https://gitee.com/mindspore/models/tree/master/official/cv/Arcface) |✅| ✅ | | -| 图像 | 关键点检测 | [ArtTrack](https://gitee.com/mindspore/models/tree/master/research/cv/ArtTrack) | | ✅ | | -| 图像 | 风格转移 | [AttGAN](https://gitee.com/mindspore/models/tree/master/research/cv/AttGAN) |✅| ✅ | | -| 图像 | 图像分类 | [augvit](https://gitee.com/mindspore/models/tree/master/research/cv/augvit) | | ✅ | | -| 图像 | 图像分类 | [autoaugment](https://gitee.com/mindspore/models/tree/master/research/cv/autoaugment) |✅| ✅ | | -| 图像 | 语义分割 | [Auto-DeepLab](https://gitee.com/mindspore/models/tree/master/research/cv/Auto-DeepLab) |✅| | | -| 图像 | 神经架构搜索 | [AutoSlim](https://gitee.com/mindspore/models/tree/master/research/cv/AutoSlim) |✅| ✅ | | -| 图像 | 图像分类 | [AVA_cifar](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_cifar) |✅| ✅ | | -| 图像 | 图像分类 | [AVA_hpa](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_hpa) |✅| ✅ | | -| 图像 | 图像分类 | [cait](https://gitee.com/mindspore/models/tree/master/research/cv/cait) |✅| ✅ | | -| 图像 | 目标检测 | [CascadeRCNN](https://gitee.com/mindspore/models/tree/master/research/cv/CascadeRCNN) |✅| ✅ | | -| 图像 | 图像分类 | [CBAM](https://gitee.com/mindspore/models/tree/master/research/cv/CBAM) |✅| | | -| 图像 | 图像分类 | [cct](https://gitee.com/mindspore/models/tree/master/research/cv/cct) |✅| ✅ | | -| 图像 | 关键点检测 | [centernet](https://gitee.com/mindspore/models/tree/master/research/cv/centernet) |✅| | ✅ | -| 图像 | 关键点检测 | [centernet_det](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_det) |✅| | | -| 图像 | 关键点检测 | [centernet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet101) |✅| ✅ | | -| 图像 | 关键点检测 | [centernet_resnet50_v1](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet50_v1) |✅| | | -| 图像 | 图像生成 | [CGAN](https://gitee.com/mindspore/models/tree/master/research/cv/CGAN) |✅| ✅ | | -| 图像 | 图像分类 | [convnext](https://gitee.com/mindspore/models/tree/master/research/cv/convnext) |✅| ✅ | | -| 图像 | 图像超分 | [csd](https://gitee.com/mindspore/models/tree/master/research/cv/csd) |✅| ✅ | | -| 图像 | 图像生成 | [CTSDG](https://gitee.com/mindspore/models/tree/master/research/cv/CTSDG) | | ✅ | | -| 图像 | 风格转移 | [CycleGAN](https://gitee.com/mindspore/models/tree/master/official/cv/CycleGAN) |✅| ✅ | | -| 图像 | 图像超分 | [DBPN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) |✅| | | -| 图像 | 图像超分 | [DBPN_GAN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) |✅| | | -| 图像 | 图像生成 | [dcgan](https://gitee.com/mindspore/models/tree/master/research/cv/dcgan) |✅| ✅ | | -| 图像 | 重新识别 | [DDAG](https://gitee.com/mindspore/models/tree/master/research/cv/DDAG) |✅| ✅ | | -| 图像 | 语义分割 | [DDM](https://gitee.com/mindspore/models/tree/master/research/cv/DDM) |✅| | | -| 图像 | 语义分割 | [DDRNet](https://gitee.com/mindspore/models/tree/master/research/cv/DDRNet) |✅| ✅ | | -| 图像 | 目标检测 | [DeepID](https://gitee.com/mindspore/models/tree/master/research/cv/DeepID) |✅| ✅ | | -| 图像 | 语义分割 | [deeplabv3plus](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabV3P) |✅| ✅ | | -| 图像 | 图像检索 | [delf](https://gitee.com/mindspore/models/tree/master/research/cv/delf) |✅| | | -| 图像 | 零样本学习 | [dem](https://gitee.com/mindspore/models/tree/master/research/cv/dem) |✅| ✅ | | -| 图像 | 目标检测 | [detr](https://gitee.com/mindspore/models/tree/master/research/cv/detr) |✅| ✅ | | -| 图像 | 语义分割 | [dgcnet_res101](https://gitee.com/mindspore/models/tree/master/research/cv/dgcnet_res101) | | ✅ | | -| 图像 | 实例分割 | [dlinknet](https://gitee.com/mindspore/models/tree/master/research/cv/dlinknet) |✅| | | -| 图像 | 图像去噪 | [DnCNN](https://gitee.com/mindspore/models/tree/master/research/cv/DnCNN) |✅| | | -| 图像 | 图像分类 | [dnet_nas](https://gitee.com/mindspore/models/tree/master/research/cv/dnet_nas) |✅| | | -| 图像 | 图像分类 | [DRNet](https://gitee.com/mindspore/models/tree/master/research/cv/DRNet) |✅| ✅ | | -| 图像 | 图像超分 | [EDSR](https://gitee.com/mindspore/models/tree/master/official/cv/EDSR) |✅| | | -| 图像 | 目标检测 | [EfficientDet_d0](https://gitee.com/mindspore/models/tree/master/research/cv/EfficientDet_d0) |✅| | | -| 图像 | 图像分类 | [efficientnet-b0](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b0) |✅| | | -| 图像 | 图像分类 | [efficientnet-b1](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnet-b1) |✅| | | -| 图像 | 图像分类 | [efficientnet-b2](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnet-b2) |✅| ✅ | | -| 图像 | 图像分类 | [efficientnet-b3](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnet-b3) |✅| ✅ | | -| 图像 | 图像分类 | [efficientnetv2](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/efficientnetv2) |✅| | | -| 图像 | 显著性检测 | [EGnet](https://gitee.com/mindspore/models/tree/master/research/cv/EGnet) |✅| ✅ | | -| 图像 | 语义分割 | [E-NET](https://gitee.com/mindspore/models/tree/master/research/cv/E-NET) |✅| ✅ | | -| 图像 | 图像超分 | [esr_ea](https://gitee.com/mindspore/models/tree/master/research/cv/esr_ea) |✅| ✅ | | -| 图像 | 图像超分 | [ESRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/ESRGAN) |✅| ✅ | | -| 图像 | 图像分类 | [FaceAttribute](https://gitee.com/mindspore/models/tree/master/research/cv/FaceAttribute) |✅| ✅ | | -| 图像 | 目标检测 | [faceboxes](https://gitee.com/mindspore/models/tree/master/research/cv/faceboxes) |✅| | | -| 图像 | 目标检测 | [FaceDetection](https://gitee.com/mindspore/models/tree/master/research/cv/FaceDetection) |✅| ✅ | | -| 图像 | 人脸识别 | [FaceNet](https://gitee.com/mindspore/models/tree/master/research/cv/FaceNet) |✅| ✅ | | -| 图像 | 图像分类 | [FaceQualityAssessment](https://gitee.com/mindspore/models/tree/master/research/cv/FaceQualityAssessment) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [FaceRecognition](https://gitee.com/mindspore/models/tree/master/official/cv/FaceRecognition) |✅| ✅ | | -| 图像 | 目标检测 | [FaceRecognitionForTracking](https://gitee.com/mindspore/models/tree/master/research/cv/FaceRecognitionForTracking) |✅| | ✅ | -| 图像 | 目标检测 | [faster_rcnn_dcn](https://gitee.com/mindspore/models/tree/master/research/cv/faster_rcnn_dcn) |✅| ✅ | | -| 图像 | 图像抠图 | [FCANet](https://gitee.com/mindspore/models/tree/master/research/cv/FCANet) |✅| | | -| 图像 | 图像分类 | [FDA-BNN](https://gitee.com/mindspore/models/tree/master/research/cv/FDA-BNN) |✅| ✅ | | -| 图像 | 图像分类 | [fishnet99](https://gitee.com/mindspore/models/tree/master/research/cv/fishnet99) |✅| ✅ | | -| 图像 | 光流估计 | [flownet2](https://gitee.com/mindspore/models/tree/master/research/cv/flownet2) |✅| | | -| 图像 | 图像生成 | [gan](https://gitee.com/mindspore/models/tree/master/research/cv/gan) |✅| ✅ | | -| 图像 | 图像分类 | [GENet_Res50](https://gitee.com/mindspore/models/tree/master/research/cv/GENet_Res50) |✅| | | -| 图像 | 图像分类 | [ghostnet](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet) |✅| | | -| 图像 | 图像分类 | [ghostnet_d](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet_d) |✅| ✅ | | -| 图像 | 图像分类 | [glore_res200](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) |✅| ✅ | | -| 图像 | 图像分类 | [glore_res50](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) |✅| ✅ | | -| 图像 | 图像分类 | [hardnet](https://gitee.com/mindspore/models/tree/master/research/cv/hardnet) |✅| ✅ | | -| 图像 | 边缘检测 | [hed](https://gitee.com/mindspore/models/tree/master/research/cv/hed) |✅| ✅ | | -| 图像 | 图像生成 | [HiFaceGAN](https://gitee.com/mindspore/models/tree/master/research/cv/HiFaceGAN) | | ✅ | | -| 图像 | 图像分类 | [HourNAS](https://gitee.com/mindspore/models/tree/master/research/cv/HourNAS) | | ✅ | | -| 图像 | 图像分类 | [HRNetW48_cls](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_cls) |✅| ✅ | | -| 图像 | 语义分割 | [HRNetW48_seg](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_seg) |✅| | | -| 图像 | 图像分类 | [ibnnet](https://gitee.com/mindspore/models/tree/master/research/cv/ibnnet) |✅| ✅ | | -| 图像 | 语义分割 | [ICNet](https://gitee.com/mindspore/models/tree/master/research/cv/ICNet) |✅| | | -| 图像 | 图像分类 | [inception_resnet_v2](https://gitee.com/mindspore/models/tree/master/research/cv/inception_resnet_v2) |✅| ✅ | | -| 图像 | 图像分类 | [Inceptionv2](https://gitee.com/mindspore/models/tree/master/research/cv/Inception-v2) |✅| ✅ | | -| 图像 | 图像抠图 | [IndexNet](https://gitee.com/mindspore/models/tree/master/research/cv/IndexNet) | | ✅ | | -| 图像 | 图像生成 | [IPT](https://gitee.com/mindspore/models/tree/master/research/cv/IPT) |✅| | | -| 图像 | 图像超分 | [IRN](https://gitee.com/mindspore/models/tree/master/research/cv/IRN) |✅| ✅ | | -| 图像 | 图像分类 | [ISyNet](https://gitee.com/mindspore/models/tree/master/research/cv/ISyNet) |✅| ✅ | | -| 图像 | 图像分类 | [ivpf](https://gitee.com/mindspore/models/tree/master/research/cv/ivpf) | | ✅ | | -| 图像 | 图像去噪 | [LearningToSeeInTheDark](https://gitee.com/mindspore/models/tree/master/research/cv/LearningToSeeInTheDark) |✅| | | -| 图像 | 元学习 | [LEO](https://gitee.com/mindspore/models/tree/master/research/cv/LEO) |✅| ✅ | | -| 图像 | 目标检测 | [LightCNN](https://gitee.com/mindspore/models/tree/master/research/cv/LightCNN) |✅| ✅ | ✅ | -| 图像 | 图像超分 | [lite-hrnet](https://gitee.com/mindspore/models/tree/master/research/cv/lite-hrnet) | | ✅ | | -| 图像 | 图像分类 | [lresnet100e_ir](https://gitee.com/mindspore/models/tree/master/research/cv/lresnet100e_ir) | | ✅ | | -| 图像 | 目标检测 | [m2det](https://gitee.com/mindspore/models/tree/master/research/cv/m2det) | | ✅ | | -| 图像 | 自编码 | [mae](https://gitee.com/mindspore/models/tree/master/official/cv/MAE) |✅| ✅ | | -| 图像 | 元学习 | [MAML](https://gitee.com/mindspore/models/tree/master/research/cv/MAML) |✅| ✅ | | -| 图像 | 文本识别 | [ManiDP](https://gitee.com/mindspore/models/tree/master/research/cv/ManiDP) | | ✅ | | -| 图像 | 人脸识别 | [MaskedFaceRecognition](https://gitee.com/mindspore/models/tree/master/research/cv/MaskedFaceRecognition) |✅| | | -| 图像 | 元学习 | [meta-baseline](https://gitee.com/mindspore/models/tree/master/research/cv/meta-baseline) |✅| ✅ | | -| 图像 | 重新识别 | [MGN](https://gitee.com/mindspore/models/tree/master/research/cv/MGN) |✅| ✅ | | -| 图像 | 深度估计 | [midas](https://gitee.com/mindspore/models/tree/master/research/cv/midas) |✅| ✅ | | -| 图像 | 图像去噪 | [MIMO-UNet](https://gitee.com/mindspore/models/tree/master/research/cv/MIMO-UNet) | | ✅ | | -| 图像 | 图像分类 | [mnasnet](https://gitee.com/mindspore/models/tree/master/research/cv/mnasnet) |✅| ✅ | | -| 图像 | 图像分类 | [mobilenetv3_large](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetv3_large) |✅| | ✅ | -| 图像 | 图像分类 | [mobilenetV3_small_x1_0](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetV3_small_x1_0) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [MultiTaskNet](https://gitee.com/mindspore/models/tree/master/research/cv/PAMTRI/MultiTaskNet) |✅| ✅ | | -| 图像 | 重新识别 | [MVD](https://gitee.com/mindspore/models/tree/master/research/cv/MVD) |✅| ✅ | | -| 图像 | 目标检测 | [nas-fpn](https://gitee.com/mindspore/models/tree/master/research/cv/nas-fpn) |✅| | | -| 图像 | 图像去噪 | [Neighbor2Neighbor](https://gitee.com/mindspore/models/tree/master/research/cv/Neighbor2Neighbor) |✅| ✅ | | -| 图像 | 图像分类 | [NFNet](https://gitee.com/mindspore/models/tree/master/research/cv/NFNet) |✅| ✅ | | -| 图像 | 图像质量评估 | [nima_vgg16](https://gitee.com/mindspore/models/tree/master/research/cv/nima_vgg16) | | ✅ | | -| 图像 | 语义分割 | [nnUNet](https://gitee.com/mindspore/models/tree/master/research/cv/nnUNet) |✅| ✅ | | -| 图像 | 图像分类 | [ntsnet](https://gitee.com/mindspore/models/tree/master/research/cv/ntsnet) |✅| ✅ | | -| 图像 | 语义分割 | [OCRNet](https://gitee.com/mindspore/models/tree/master/official/cv/OCRNet) |✅| ✅ | | -| 图像 | 重新识别 | [osnet](https://gitee.com/mindspore/models/tree/master/research/cv/osnet) |✅| ✅ | | -| 图像 | 显著性检测 | [PAGENet](https://gitee.com/mindspore/models/tree/master/research/cv/PAGENet) |✅| ✅ | | -| 图像 | 图像检索 | [pcb](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | -| 图像 | 图像检索 | [pcb](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | -| 图像 | 图像检索 | [pcb_rpp](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | -| 图像 | 图像分类 | [PDarts](https://gitee.com/mindspore/models/tree/master/research/cv/PDarts) |✅| ✅ | | -| 图像 | 图像生成 | [PGAN](https://gitee.com/mindspore/models/tree/master/research/cv/PGAN) |✅| ✅ | | -| 图像 | 图像生成 | [Pix2Pix](https://gitee.com/mindspore/models/tree/master/research/cv/Pix2Pix) |✅| ✅ | | -| 图像 | 图像超分 | [Pix2PixHD](https://gitee.com/mindspore/models/tree/master/official/cv/Pix2PixHD) |✅| | | -| 图像 | 图像分类 | [pnasnet](https://gitee.com/mindspore/models/tree/master/research/cv/pnasnet) |✅| ✅ | | -| 图像 | 点云模型 | [pointnet](https://gitee.com/mindspore/models/tree/master/official/cv/PointNet) |✅| ✅ | | -| 图像 | 点云模型 | [pointnet2](https://gitee.com/mindspore/models/tree/master/official/cv/PointNet2) |✅| ✅ | | -| 图像 | 图像分类 | [PoseEstNet](https://gitee.com/mindspore/models/tree/master/research/cv/PAMTRI/PoseEstNet) |✅| ✅ | | -| 图像 | 图像分类 | [ProtoNet](https://gitee.com/mindspore/models/tree/master/research/cv/ProtoNet) |✅| ✅ | | -| 图像 | 图像分类 | [proxylessnas](https://gitee.com/mindspore/models/tree/master/research/cv/proxylessnas) |✅| ✅ | | -| 图像 | 语义分割 | [PSPNet](https://gitee.com/mindspore/models/tree/master/research/cv/PSPNet) |✅| | | -| 图像 | 显著性检测 | [ras](https://gitee.com/mindspore/models/tree/master/research/cv/ras) |✅| ✅ | | -| 图像 | 图像超分 | [RCAN](https://gitee.com/mindspore/models/tree/master/research/cv/RCAN) |✅| | | -| 图像 | 目标检测 | [rcnn](https://gitee.com/mindspore/models/tree/master/research/cv/rcnn) |✅| ✅ | | -| 图像 | 图像超分 | [REDNet30](https://gitee.com/mindspore/models/tree/master/research/cv/REDNet30) |✅| ✅ | | -| 图像 | 目标检测 | [RefineDet](https://gitee.com/mindspore/models/tree/master/research/cv/RefineDet) |✅| ✅ | | -| 图像 | 语义分割 | [RefineNet](https://gitee.com/mindspore/models/tree/master/research/cv/RefineNet) |✅| ✅ | | -| 图像 | 重新识别 | [ReIDStrongBaseline](https://gitee.com/mindspore/models/tree/master/research/cv/ReIDStrongBaseline) |✅| ✅ | | -| 图像 | 图像分类 | [relationnet](https://gitee.com/mindspore/models/tree/master/research/cv/relationnet) |✅| ✅ | | -| 图像 | 图像分类 | [renas](https://gitee.com/mindspore/models/tree/master/research/cv/renas) |✅| ✅ | ✅ | -| 图像 | 语义分割 | [repvgg](https://gitee.com/mindspore/models/tree/master/research/cv/repvgg) |✅| ✅ | | -| 图像 | 语义分割 | [res2net_deeplabv3](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_deeplabv3) |✅| | ✅ | -| 图像 | 目标检测 | [res2net_faster_rcnn](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_faster_rcnn) |✅| ✅ | | -| 图像 | 目标检测 | [res2net_yolov3](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_yolov3) |✅| ✅ | | -| 图像 | 图像分类 | [res2net101](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| 图像 | 图像分类 | [res2net152](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| 图像 | 图像分类 | [res2net50](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| 图像 | 图像分类 | [ResNeSt50](https://gitee.com/mindspore/models/tree/master/research/cv/ResNeSt50) |✅| ✅ | | -| 图像 | 图像分类 | [resnet50_adv_pruning](https://gitee.com/mindspore/models/tree/master/research/cv/resnet50_adv_pruning) |✅| ✅ | | -| 图像 | 图像分类 | [resnet50_bam](https://gitee.com/mindspore/models/tree/master/research/cv/resnet50_bam) |✅| ✅ | | -| 图像 | 图像分类 | [ResNet50-Quadruplet](https://gitee.com/mindspore/models/tree/master/research/cv/metric_learn) |✅| ✅ | | -| 图像 | 图像分类 | [ResNet50-Triplet](https://gitee.com/mindspore/models/tree/master/research/cv/metric_learn) |✅| ✅ | | -| 图像 | 图像分类 | [ResnetV2_101](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | -| 图像 | 图像分类 | [ResnetV2_152](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | -| 图像 | 图像分类 | [ResnetV2_50](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | -| 图像 | 图像分类 | [resnetv2_50_frn](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2_50_frn) |✅| ✅ | | -| 图像 | 图像分类 | [resnext152_64x4d](https://gitee.com/mindspore/models/tree/master/research/cv/resnext152_64x4d) |✅| ✅ | | -| 图像 | 目标检测 | [retinaface_mobilenet0.25](https://gitee.com/mindspore/models/tree/master/research/cv/retinaface) |✅| ✅ | | -| 图像 | 目标检测 | [retinanet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet101) |✅| ✅ | | -| 图像 | 目标检测 | [retinanet_resnet152](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet152) |✅| ✅ | | -| 图像 | 目标检测 | [rfcn](https://gitee.com/mindspore/models/tree/master/research/cv/rfcn) | | ✅ | | -| 图像 | 图像分类 | [SE_ResNeXt50](https://gitee.com/mindspore/models/tree/master/research/cv/SE_ResNeXt50) |✅| | | -| 图像 | 图像分类 | [senet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [senet_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [se-res2net50](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| 图像 | 图像分类 | [S-GhostNet](https://gitee.com/mindspore/models/tree/master/research/cv/S-GhostNet) |✅| | | -| 图像 | 姿态估计 | [simple_baselines](https://gitee.com/mindspore/models/tree/master/research/cv/simple_baselines) |✅| ✅ | | -| 图像 | 图像生成 | [SinGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SinGAN) |✅| | | -| 图像 | 图像分类 | [single_path_nas](https://gitee.com/mindspore/models/tree/master/research/cv/single_path_nas) |✅| ✅ | | -| 图像 | 图像分类 | [sknet](https://gitee.com/mindspore/models/tree/master/research/cv/sknet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [snn_mlp](https://gitee.com/mindspore/models/tree/master/research/cv/snn_mlp) | | ✅ | | -| 图像 | 目标检测 | [Spnas](https://gitee.com/mindspore/models/tree/master/research/cv/Spnas) |✅| | | -| 图像 | 图像分类 | [SPPNet](https://gitee.com/mindspore/models/tree/master/research/cv/SPPNet) |✅| ✅ | | -| 图像 | 图像分类 | [squeezenet](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | -| 图像 | 图像超分 | [sr_ea](https://gitee.com/mindspore/models/tree/master/research/cv/sr_ea) |✅| | | -| 图像 | 图像超分 | [SRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SRGAN) |✅| ✅ | | -| 图像 | 图像分类 | [ssc_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/ssc_resnet50) |✅| ✅ | | -| 图像 | 目标检测 | [ssd_ghostnet](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_ghostnet) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd_inception_v2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_inception_v2) | | ✅ | ✅ | -| 图像 | 目标检测 | [ssd_inceptionv2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_inceptionv2) |✅| | | -| 图像 | 目标检测 | [ssd_mobilenetV2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd_mobilenetV2_FPNlite](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2_FPNlite) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd_resnet_34](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet_34) | | ✅ | | -| 图像 | 目标检测 | [ssd_resnet34](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet34) |✅| | ✅ | -| 图像 | 目标检测 | [ssd_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet50) |✅| | | -| 图像 | 姿态估计 | [StackedHourglass](https://gitee.com/mindspore/models/tree/master/research/cv/StackedHourglass) |✅| | | -| 图像 | 图像生成 | [StarGAN](https://gitee.com/mindspore/models/tree/master/research/cv/StarGAN) |✅| ✅ | | -| 图像 | 图像生成 | [STGAN](https://gitee.com/mindspore/models/tree/master/research/cv/STGAN) |✅| ✅ | | -| 图像 | 交通预测 | [stgcn](https://gitee.com/mindspore/models/tree/master/research/cv/stgcn) |✅| ✅ | | -| 图像 | 图像分类 | [stpm](https://gitee.com/mindspore/models/tree/master/official/cv/STPM) |✅| ✅ | | -| 图像 | 图像分类 | [swin_transformer](https://gitee.com/mindspore/models/tree/master/official/cv/SwinTransformer) |✅| ✅ | | -| 图像 | 时间定位 | [tall](https://gitee.com/mindspore/models/tree/master/research/cv/tall) |✅| | | -| 图像 | 图像分类 | [TCN](https://gitee.com/mindspore/models/tree/master/research/cv/TCN) |✅| ✅ | | -| 图像 | 文本检测 | [textfusenet](https://gitee.com/mindspore/models/tree/master/research/cv/textfusenet) |✅| | | -| 图像 | 交通预测 | [tgcn](https://gitee.com/mindspore/models/tree/master/research/cv/tgcn) |✅| ✅ | | -| 图像 | 图像分类 | [tinynet](https://gitee.com/mindspore/models/tree/master/research/cv/tinynet) | | ✅ | | -| 图像 | 图像分类 | [TNT](https://gitee.com/mindspore/models/tree/master/research/cv/TNT) |✅| ✅ | | -| 图像 | 目标检测 | [u2net](https://gitee.com/mindspore/models/tree/master/research/cv/u2net) |✅| ✅ | | -| 图像 | 图像生成 | [U-GAT-IT](https://gitee.com/mindspore/models/tree/master/research/cv/U-GAT-IT) |✅| ✅ | | -| 图像 | 语义分割 | [UNet3+](https://gitee.com/mindspore/models/tree/master/research/cv/UNet3+) |✅| ✅ | | -| 图像 | 重新识别 | [VehicleNet](https://gitee.com/mindspore/models/tree/master/research/cv/VehicleNet) |✅| | | -| 图像 | 图像分类 | [vgg19](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/vgg19) |✅| ✅ | | -| 图像 | 图像分类 | [ViG](https://gitee.com/mindspore/models/tree/master/research/cv/ViG) |✅| ✅ | | -| 图像 | 图像分类 | [vit_cifar](https://gitee.com/mindspore/models/tree/master/research/cv/vit_base) |✅| ✅ | | -| 图像 | 语义分割 | [vnet](https://gitee.com/mindspore/models/tree/master/research/cv/vnet) |✅| ✅ | | -| 图像 | 图像分类 | [wave_mlp](https://gitee.com/mindspore/models/tree/master/research/cv/wave_mlp) |✅| ✅ | | -| 图像 | 图像超分 | [wdsr](https://gitee.com/mindspore/models/tree/master/research/cv/wdsr) |✅| ✅ | | -| 图像 | 图像生成 | [wgan](https://gitee.com/mindspore/models/tree/master/official/cv/WGAN) |✅| | | -| 图像 | 图像分类 | [wideresnet](https://gitee.com/mindspore/models/tree/master/research/cv/wideresnet) |✅| ✅ | | -| 图像 | 实例分割 | [Yolact++](https://gitee.com/mindspore/models/tree/master/research/cv/Yolact++) |✅| | | -| 图像 | 目标检测 | [yolov3_tiny](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_tiny) |✅| ✅ | | -| 图像 | 目标检测 | [yolox](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOX) |✅| | | -| 多模态 | 多模态 | [opt](https://gitee.com/mindspore/models/tree/master/research/mm/opt) |✅| ✅ | | -| 多模态 | 多模态 | [TokenFusion](https://gitee.com/mindspore/models/tree/master/research/cv/TokenFusion) |✅| ✅ | | -| 多模态 | 多模态 | [wukong](https://gitee.com/mindspore/models/tree/master/research/mm/wukong) |✅| | | -| 推荐 | 点击率预测 | [autodis](https://gitee.com/mindspore/models/tree/master/research/recommend/autodis) |✅| ✅ | | -| 推荐 | 点击率预测 | [DIEN](https://gitee.com/mindspore/models/tree/master/research/recommend/DIEN) |✅| ✅ | | -| 推荐 | 点击率预测 | [dlrm](https://gitee.com/mindspore/models/tree/master/research/recommend/dlrm) |✅| ✅ | | -| 推荐 | 点击率预测 | [EDCN](https://gitee.com/mindspore/models/tree/master/research/recommend/EDCN) |✅| ✅ | | -| 推荐 | 点击率预测 | [Fat-DeepFFM](https://gitee.com/mindspore/models/tree/master/research/recommend/Fat-DeepFFM) |✅| ✅ | | -| 推荐 | 点击率预测 | [mmoe](https://gitee.com/mindspore/models/tree/master/research/recommend/mmoe) |✅| ✅ | | -| 文本 | 自然语言理解 | [albert](https://gitee.com/mindspore/models/tree/master/research/nlp/albert) |✅| ✅ | | -| 文本 | 情绪分类 | [atae_lstm](https://gitee.com/mindspore/models/tree/master/research/nlp/atae_lstm) |✅| ✅ | | -| 文本 | 对话 | [dam](https://gitee.com/mindspore/models/tree/master/research/nlp/dam) |✅| | | -| 文本 | 语言模型 | [gpt2](https://gitee.com/mindspore/models/tree/master/research/nlp/gpt2) |✅| | | -| 文本 | 知识图嵌入 | [hake](https://gitee.com/mindspore/models/tree/master/research/nlp/hake) | | ✅ | | -| 文本 | 自然语言理解 | [ktnet](https://gitee.com/mindspore/models/tree/master/research/nlp/ktnet) |✅| ✅ | | -| 文本 | 命名实体识别 | [lstm_crf](https://gitee.com/mindspore/models/tree/master/research/nlp/lstm_crf) |✅| | | -| 文本 | 自然语言理解 | [luke](https://gitee.com/mindspore/models/tree/master/research/nlp/luke) |✅| ✅ | | -| 文本 | 知识图嵌入 | [rotate](https://gitee.com/mindspore/models/tree/master/research/nlp/rotate) |✅| ✅ | | -| 文本 | 情绪分类 | [senta](https://gitee.com/mindspore/models/tree/master/research/nlp/senta) |✅| ✅ | | -| 文本 | 机器翻译 | [seq2seq](https://gitee.com/mindspore/models/tree/master/research/nlp/seq2seq) |✅| | | -| 文本 | 词嵌入 | [skipgram](https://gitee.com/mindspore/models/tree/master/research/nlp/skipgram) |✅| ✅ | | -| 文本 | 机器翻译 | [speech_transformer](https://gitee.com/mindspore/models/tree/master/research/nlp/speech_transformer) |✅| | | -| 文本 | 预训练 | [ternarybert](https://gitee.com/mindspore/models/tree/master/research/nlp/ternarybert) |✅| ✅ | | -| 文本 | 自然语言理解 | [tprr](https://gitee.com/mindspore/models/tree/master/research/nlp/tprr) |✅| | | -| 文本 | 自然语言理解 | [transformer_xl](https://gitee.com/mindspore/models/tree/master/research/nlp/transformer_xl) |✅| ✅ | | -| 文本 | 知识图嵌入 | [transX](https://gitee.com/mindspore/models/tree/master/research/nlp/transX) | | ✅ | | -| 视频 | 视频分类 | [AttentionCluster](https://gitee.com/mindspore/models/tree/master/research/cv/AttentionCluster) |✅| ✅ | | -| 视频 | 其他 | [DYR](https://gitee.com/mindspore/models/tree/master/research/nlp/DYR) |✅| | | -| 视频 | 视频分类 | [ecolite](https://gitee.com/mindspore/models/tree/master/research/cv/ecolite) |✅| | | -| 视频 | 目标追踪 | [fairmot](https://gitee.com/mindspore/models/tree/master/research/cv/fairmot) |✅| ✅ | | -| 视频 | 视频分类 | [I3D](https://gitee.com/mindspore/models/tree/master/research/cv/I3D) |✅| | | -| 视频 | 目标追踪 | [JDE](https://gitee.com/mindspore/models/tree/master/research/cv/JDE) | | ✅ | | -| 视频 | 视频分割 | [OSVOS](https://gitee.com/mindspore/models/tree/master/research/cv/OSVOS) | | ✅ | | -| 视频 | 视频分类 | [r2plus1d](https://gitee.com/mindspore/models/tree/master/research/cv/r2plus1d) |✅| ✅ | | -| 视频 | 视频超分 | [rbpn](https://gitee.com/mindspore/models/tree/master/research/cv/rbpn) |✅| | | -| 视频 | 视频分类 | [resnet3d](https://gitee.com/mindspore/models/tree/master/research/cv/resnet3d) |✅| | | -| 视频 | 目标追踪 | [SiamFC](https://gitee.com/mindspore/models/tree/master/research/cv/SiamFC) |✅| | | -| 视频 | 目标追踪 | [siamRPN](https://gitee.com/mindspore/models/tree/master/research/cv/siamRPN) |✅| ✅ | | -| 视频 | 视频分类 | [slowfast](https://gitee.com/mindspore/models/tree/master/research/cv/slowfast) |✅| ✅ | | -| 视频 | 视频分类 | [stnet](https://gitee.com/mindspore/models/tree/master/research/cv/stnet) |✅| | | -| 视频 | 目标追踪 | [tracktor](https://gitee.com/mindspore/models/tree/master/research/cv/tracktor) | | ✅ | | -| 视频 | 目标追踪 | [tracktor++](https://gitee.com/mindspore/models/tree/master/research/cv/tracktor++) |✅| ✅ | | -| 视频 | 视频分类 | [trn](https://gitee.com/mindspore/models/tree/master/research/cv/trn) | | ✅ | | -| 视频 | 视频分类 | [tsm](https://gitee.com/mindspore/models/tree/master/research/cv/tsm) |✅| ✅ | | -| 视频 | 视频分类 | [tsn](https://gitee.com/mindspore/models/tree/master/research/cv/tsn) |✅| ✅ | | - -Process finished with exit code 0 - -- [社区](https://gitee.com/mindspore/models/tree/master/community) - -## 公告 - -### 2021.9.15 `models`独立建仓 - -`models`仓库由原[mindspore仓库](https://gitee.com/mindspore/mindspore)的model_zoo目录独立分离而来，新仓库不继承历史commit记录，如果需要查找历史提2021.9.15之前的提交，请到mindspore仓库进行查询。 - -## 关联站点 - -这里是MindSpore框架提供的可以运行于包括Ascend/GPU/CPU/移动设备等多种设备的模型库。 - -相应的专属于Ascend平台的多框架模型可以参考[昇腾ModelZoo](https://hiascend.com/software/modelzoo)以及对应的[代码仓](https://gitee.com/ascend/modelzoo)。 - -MindSpore相关的预训练模型可以在[MindSpore hub](https://www.mindspore.cn/resources/hub)或[下载中心](https://download.mindspore.cn/model_zoo/). - -## 免责声明 - -MindSpore仅提供下载和预处理公共数据集的脚本。我们不拥有这些数据集，也不对它们的质量负责或维护。请确保您具有在数据集许可下使用该数据集的权限。在这些数据集上训练的模型仅用于非商业研究和教学目的。 - -致数据集拥有者：如果您不希望将数据集包含在MindSpore中，或者希望以任何方式对其进行更新，我们将根据要求删除或更新所有公共内容。请通过GitHub或Gitee与我们联系。非常感谢您对这个社区的理解和贡献。 - -MindSpore已获得Apache 2.0许可，请参见LICENSE文件。 - -## 许可证 - -[Apache 2.0许可证](https://gitee.com/mindspore/mindspore/blob/master/LICENSE) +[Apache License 2.0](https://gitee.com/mindspore/mindspore/blob/master/LICENSE) ## FAQ -想要获取更多关于`MindSpore`框架使用本身的FAQ问题的，可以参考[官网FAQ](https://www.mindspore.cn/docs/zh-CN/master/faq/installation.html) +For more information about `MindSpore` framework, please refer to [FAQ](https://www.mindspore.cn/docs/en/master/faq/installation.html) -- **Q: 直接使用models下的模型出现内存不足错误，例如*Failed to alloc memory pool memory*, 该怎么处理?** +- **Q: How to resolve the lack of memory while using the model directly under "models" with errors such as *Failed to alloc memory pool memory*?** - **A**: 直接使用models下的模型出现内存不足的典型原因是由于运行模式（`PYNATIVE_MODE`)、运行环境配置、License控制（AI-TOKEN）的不同造成的： - - `PYNATIVE_MODE`通常比`GRAPH_MODE`使用更多内存，尤其是在需要进行反向传播计算的训练图中，当前有2种方法可以尝试解决该问题。 - 方法1：你可以尝试使用一些更小的batch size； - 方法2：添加context.set_context(mempool_block_size="XXGB")，其中，“XX”当前最大有效值可设置为“31”。 - 如果将方法1与方法2结合使用，效果会更好。 - - 运行环境由于NPU的核数、内存等配置不同也会产生类似问题。 - - License控制（AI-TOKEN）的不同档位会造成执行过程中内存开销不同，也可以尝试使用一些更小的batch size。 + **A**: The typical reason for insufficient memory when directly using models under "models" is due to differences in operating mode (`PYNATIVE_MODE`), operating environment configuration, and license control (AI-TOKEN). + - `PYNATIVE_MODE` usually uses more memory than `GRAPH_MODE` , especially in the training graph that needs back propagation calculation, there are two ways to try to solve this problem. + Method 1: You can try to use some smaller batch size; + Method 2: Add context.set_context(mempool_block_size="XXGB"), where the current maximum effective value of "XX" can be set to "31". + If method 1 and method 2 are used in combination, the effect will be better. + - The operating environment will also cause similar problems due to the different configurations of NPU cores, memory, etc.; + - Different gears of License control (AI-TOKEN ) will cause different memory overhead during execution. You can also try to use some smaller batch sizes. -- **Q: 一些网络运行中报错接口不存在，例如cannot import，该怎么处理?** +- **Q: How to resolve the error about the interface are not supported in some network operations, such as `cann not import`?** - **A**: 优先检查一下获取网络脚本的分支，与所使用的MindSpore版本是否一致，部分新分支中的模型脚本会使用一些新版本MindSpore才支持的接口，从而在使用老版本MindSpore时会发生报错. + **A**: Please check the version of MindSpore and the branch you fetch the modelzoo scripts. Some model scripits in latest branch will use new interface in the latest version of MindSpore. -- **Q: 一些模型描述中提到的*RANK_TABLE_FILE*文件，是什么？** +- **Q: What is Some *RANK_TBAL_FILE* which mentioned in many models?** - **A**: *RANK_TABLE_FILE*是一个Ascend环境上用于指定分布式集群信息的文件，更多信息可以参考生成工具[hccl_toos](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)和[分布式并行训练教程](https://mindspore.cn/docs/programming_guide/zh-CN/r1.5/distributed_training_ascend.html#id4) + **A**: *RANK_TABLE_FILE* is the config file of cluster on Ascend while running distributed training. For more information, you could refer to the generator [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) and [Parallel Distributed Training Example](https://mindspore.cn/docs/programming_guide/en/r1.5/distributed_training_ascend.html#configuring-distributed-environment-variables) -- **Q: 在windows环境上要怎么运行网络脚本？** +- **Q: How to run the scripts on Windows system?** - **A**: 多数模型都是使用bash作为启动脚本，在Windows环境上无法直接使用bash命令，你可以考虑直接运行python命令而不是bash启动脚本 ，如果你确实想需要使用bash脚本，你可以考虑使用以下几种方法来运行模型： - 1. 使用虚拟环境，可以构造一个linux的虚拟机或docker容器，然后在虚拟环境中运行脚本 - 2. 使用WSL，可以开启Windows的linux子系统来在Windows系统中运行linux，然后再WSL中运行脚本。 - 3. 使用Windows Bash，需要获取一个可以直接在Windows上运行bash的环境，常见的选择是[cygwin](http://www.cygwin.com)或[git bash](https://gitforwindows.org) - 4. 跳过bash脚本，直接调用python程序。 + **A**: Most the start-up scripts are written in `bash`, but we usually can't run bash directly on Windows. You can try start python directly without bash scripts. If you really need the start-up bash scripts, we suggest you the following method to get a bash environment on Windows: + 1. Use a virtual system or docker container with linux system. Then run the scripts in the virtual system or container. + 2. Use WSL, you could turn on the `Windows Subsystem for Linux` on Windows to obtain an linux system which could run the bash scripts. + 3. Use some bash tools on Windows, such as [cygwin](http://www.cygwin.com) and [git bash](https://gitforwindows.org). -- **Q: 网络在310推理时出现编译失败，报错信息指向gflags，例如*undefined reference to 'google::FlagRegisterer::FlagRegisterer'*，该怎么处理?** +- **Q: How to resolve the compile error point to gflags when infer on ascend310 with errors such as *undefined reference to 'google::FlagRegisterer::FlagRegisterer'*?** - **A**: 优先检查一下环境GCC版本和gflags版本是否匹配，可以参考[官方链接](https://www.mindspore.cn/install)安装对应的GCC版本，[gflags](https://github.com/gflags/gflags/archive/v2.2.2.tar.gz)安装gflags。你需要保证所使用的组件之间是ABI兼容的，更多信息可以参考[_GLIBCXX_USE_CXX11_ABI](https://gcc.gnu.org/onlinedocs/libstdc++/manual/using_dual_abi.html) + **A**: Please check the version of GCC and gflags. You can refer to [GCC](https://www.mindspore.cn/install) and [gflags](https://github.com/gflags/gflags/archive/v2.2.2.tar.gz) to install GCC and gflags. You need to ensure that the components used are ABI compatible, for more information, please refer to [_GLIBCXX_USE_CXX11_ABI](https://gcc.gnu.org/onlinedocs/libstdc++/manual/using_dual_abi.html). -- **Q: 在Mac系统上加载mindrecord格式的数据集出错,例如*Invalid file, failed to open files for reading mindrecord files.*，该怎么处理?** +- **Q: How to solve the error when loading dataset in mindrecord format on Mac system, such as *Invalid file, failed to open files for reading mindrecord files.*?** - **A**: 优先使用*ulimit -a*检查系统限制，如果*file descriptors*数量为256（默认值），需要使用*ulimit -n 1024*将其设置为1024（或者更大的值）。之后再检查文件是否损坏或者被修改。 + **A**: Please check the system limit with *ulimit -a*, if the number of *file descriptors* is 256 (default), you need to use *ulimit -n 1024* to set it to 1024 (or larger). Then check whether the file is damaged or modified. -- **Q: 我在多台服务器构成的大集群上进行训练，但是得到的精度比预期要低，该怎么办？** +- **Q: What should I do if I can't reach the accuracy while training with several servers instead of a single server?** - **A**: 当前模型库中的大部分模型只在单机内进行过验证，最大使用8卡进行训练。由于MindSpore训练时指定的`batch_size`是单卡的，所以当单机8卡升级到多机时，会导致全局的`global_batch_size`变大，这就导致需要针对当前多机场景的`global_batch_size`进行重新调参优化。 + **A**: Most of the models has only been trained on single server with at most 8 pcs. Because the `batch_size` used in MindSpore only represent the batch size of single GPU/NPU, the `global_batch_size` will increase while training with multi-server. Different `gloabl_batch_size` requires different hyper parameter including learning_rate, etc. So you have to optimize these hyperparameters will training with multi-servers. diff --git a/README_CN.md b/README_CN.md index 08b4f1942..c99bdbe38 100644 --- a/README_CN.md +++ b/README_CN.md @@ -1,176 +1,70 @@ -# ![MindSpore Logo](https://gitee.com/mindspore/mindspore/raw/master/docs/MindSpore-logo.png) - -## 欢迎来到MindSpore ModelZoo - -MindSpore models仓中提供了不同任务领域，经典的SOTA模型实现和端到端解决方案。目的是方便MindSpore用户更加方便的利用MindSpore进行研究和产品开发。 - -为了让开发者更好地体验MindSpore框架优势，我们将陆续增加更多的典型网络和相关预训练模型。如果您对ModelZoo有任何需求，请通过[Gitee](https://gitee.com/mindspore/mindspore/issues)或[MindSpore](https://bbs.huaweicloud.com/forum/forum-1076-1.html)与我们联系，我们将及时处理。 - -| 目录 | 描述 | -|------------------------| ------------------------------------------------------------ | -| [official](official) | • 官方维护，随MindSpore版本迭代更新，保证版本出口网络的精度效果
• 推荐写法，使用最新的MindSpore接口和推荐使用的特性，在保证代码可读性的基础上，有更快的性能表现
• 有详细的网络信息和说明文档，包含但不限于模型说明，数据集使用，规格支持，精度性能数据，网络checkpoint文件，MindIR文件等 | -| [research](research) | • 历史支持，测试验收通过的模型，在README里标明支持的MindSpore版本
• 按需维护，内容不会随版本迭代更新，只会适配对应的接口变更，由MindSpore开发人员进行维护支持，按需进行维护升级
• 提供较为详细的网络信息和说明文档，包含但不限于模型说明，数据集使用，规格支持，精度数据，网络checkpoint文件，MindIR文件等 | -| [community](community) | • 生态开发者贡献模型 | - -- 使用最新MindSpore API的SOTA模型 - -- MindSpore优势 - -- 官方维护和支持 - -## 标准网络 -## Computer Vision -### Image Classification -| model | mindcv recipe | vanilla mindspore -:-: | :-: | :-: -| vgg | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/) -| resnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | [link](https://gitee.com/zwiori/models/tree/readme/official/cv/ResNet) | -| resnetv2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnetv2) | -| dpn | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | -| densenet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | -| senet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | -| sknet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | -| resnext | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | -| rexnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | -| resnest | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnest) | -| res2net | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | -| googlenet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/googlenet) | -| inceptionv3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inception_v3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv3) | -| inceptionv4 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inception_v4) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv4) | -| mobilenet v1 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv1) | -| mobilenet v2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | -| mobilenet v3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv3) | -| shufflenet v1 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenet_v1) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv1) | -| shufflenet v2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenet_v2) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv2) | -| xception | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/xception) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/xception) | -| ghostnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | -| nasnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/nasnet) | -| mnasnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | -| efficientnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/efficientnet)| [link](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/) | -| regnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | -| mixnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | -| hrnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/hrnet) | -| repvgg | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | -| bit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | -| repmlp | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repmlp) | -| convnext | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | -| vit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/VIT) | -| swin transformer | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/swintransformer) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/SwinTransformer) -| pvt | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | -| pvt v2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | -| pit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | -| coat | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | -| convit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | -| crossvit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | -| mobilevit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | -| visformer | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | -| edgenext | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | -| poolformer | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/poolformer) | -| volo | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/volo) | -| cait | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/cait) | - -### Object Detection - -#### yolo -| model | mindyolo recipe | vanilla mindspore -:-: | :-: | :-: -| yolo v3 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv3) | -| yolo v4 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov4) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv4) | -| yolo v5 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov5) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv5) | -| yolo v7 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov7) | -| yolo v8 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov8) | -| yolo x | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolovx) | - -#### others -| model | mind_series recipe | vanilla mindspore -:-: | :-: | :-: -| ssd | coming soon | [link](https://gitee.com/mindspore/models/tree/master/official/cv/SSD)| -| fast rcnn | coming soon | [link](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) | -| mask rcnn | coming soon | [link](https://gitee.com/mindspore/models/tree/master/official/cv/MaskRCNN/) | - - -### Senmatic Segmentation - -| model | mind_series recipe | vanilla mindspore -:-: | :-: | :-: -| ocrnet | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/OCRNet/) | -| deeplab v3 | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabv3) | -| deeplab v3 plus | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabV3P) | -| unet | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Unet) | -| unet3d | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Unet3d) | - -### OCR -| model | mindocr recipe | vanilla mindspore -:-: | :-: | :-: -| dbnet | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/dbnet) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/DBNet/) | -| dbnet++ | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/dbnet) | | -| psenet | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/psenet) | | -| east | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/east) | | -| fcenet | coming soon | | -| crnn | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/crnn) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/CRNN/)| -| rare(crnn_seq2seq) | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/rare) | | -| svtr | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/svtr) | | - - -- [社区](https://gitee.com/mindspore/models/tree/master/community) - -## 公告 - -### 2021.9.15 `models`独立建仓 - -`models`仓库由原[mindspore仓库](https://gitee.com/mindspore/mindspore)的model_zoo目录独立分离而来，新仓库不继承历史commit记录，如果需要查找历史提2021.9.15之前的提交，请到mindspore仓库进行查询。 - - -## 免责声明 - -MindSpore仅提供下载和预处理公共数据集的脚本。我们不拥有这些数据集，也不对它们的质量负责或维护。请确保您具有在数据集许可下使用该数据集的权限。在这些数据集上训练的模型仅用于非商业研究和教学目的。 - -致数据集拥有者：如果您不希望将数据集包含在MindSpore中，或者希望以任何方式对其进行更新，我们将根据要求删除或更新所有公共内容。请通过GitHub或Gitee与我们联系。非常感谢您对这个社区的理解和贡献。 - -MindSpore已获得Apache 2.0许可，请参见LICENSE文件。 - -## 许可证 - -[Apache 2.0许可证](https://gitee.com/mindspore/mindspore/blob/master/LICENSE) - -## FAQ - -想要获取更多关于`MindSpore`框架使用本身的FAQ问题的，可以参考[官网FAQ](https://www.mindspore.cn/docs/zh-CN/master/faq/installation.html) - -- **Q: 直接使用models下的模型出现内存不足错误，例如*Failed to alloc memory pool memory*, 该怎么处理?** - - **A**: 直接使用models下的模型出现内存不足的典型原因是由于运行模式（`PYNATIVE_MODE`)、运行环境配置、License控制（AI-TOKEN）的不同造成的： - - `PYNATIVE_MODE`通常比`GRAPH_MODE`使用更多内存，尤其是在需要进行反向传播计算的训练图中，当前有2种方法可以尝试解决该问题。 - 方法1：你可以尝试使用一些更小的batch size； - 方法2：添加context.set_context(mempool_block_size="XXGB")，其中，“XX”当前最大有效值可设置为“31”。 - 如果将方法1与方法2结合使用，效果会更好。 - - 运行环境由于NPU的核数、内存等配置不同也会产生类似问题。 - - License控制（AI-TOKEN）的不同档位会造成执行过程中内存开销不同，也可以尝试使用一些更小的batch size。 - -- **Q: 一些网络运行中报错接口不存在，例如cannot import，该怎么处理?** - - **A**: 优先检查一下获取网络脚本的分支，与所使用的MindSpore版本是否一致，部分新分支中的模型脚本会使用一些新版本MindSpore才支持的接口，从而在使用老版本MindSpore时会发生报错. - -- **Q: 一些模型描述中提到的*RANK_TABLE_FILE*文件，是什么？** - - **A**: *RANK_TABLE_FILE*是一个Ascend环境上用于指定分布式集群信息的文件，更多信息可以参考生成工具[hccl_toos](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)和[分布式并行训练教程](https://mindspore.cn/docs/programming_guide/zh-CN/r1.5/distributed_training_ascend.html#id4) - -- **Q: 在windows环境上要怎么运行网络脚本？** - - **A**: 多数模型都是使用bash作为启动脚本，在Windows环境上无法直接使用bash命令，你可以考虑直接运行python命令而不是bash启动脚本 ，如果你确实想需要使用bash脚本，你可以考虑使用以下几种方法来运行模型： - 1. 使用虚拟环境，可以构造一个linux的虚拟机或docker容器，然后在虚拟环境中运行脚本 - 2. 使用WSL，可以开启Windows的linux子系统来在Windows系统中运行linux，然后再WSL中运行脚本。 - 3. 使用Windows Bash，需要获取一个可以直接在Windows上运行bash的环境，常见的选择是[cygwin](http://www.cygwin.com)或[git bash](https://gitforwindows.org) - 4. 跳过bash脚本，直接调用python程序。 - -- **Q: 网络在310推理时出现编译失败，报错信息指向gflags，例如*undefined reference to 'google::FlagRegisterer::FlagRegisterer'*，该怎么处理?** - - **A**: 优先检查一下环境GCC版本和gflags版本是否匹配，可以参考[官方链接](https://www.mindspore.cn/install)安装对应的GCC版本，[gflags](https://github.com/gflags/gflags/archive/v2.2.2.tar.gz)安装gflags。你需要保证所使用的组件之间是ABI兼容的，更多信息可以参考[_GLIBCXX_USE_CXX11_ABI](https://gcc.gnu.org/onlinedocs/libstdc++/manual/using_dual_abi.html) - -- **Q: 在Mac系统上加载mindrecord格式的数据集出错,例如*Invalid file, failed to open files for reading mindrecord files.*，该怎么处理?** - - **A**: 优先使用*ulimit -a*检查系统限制，如果*file descriptors*数量为256（默认值），需要使用*ulimit -n 1024*将其设置为1024（或者更大的值）。之后再检查文件是否损坏或者被修改。 - -- **Q: 我在多台服务器构成的大集群上进行训练，但是得到的精度比预期要低，该怎么办？** - - **A**: 当前模型库中的大部分模型只在单机内进行过验证，最大使用8卡进行训练。由于MindSpore训练时指定的`batch_size`是单卡的，所以当单机8卡升级到多机时，会导致全局的`global_batch_size`变大，这就导致需要针对当前多机场景的`global_batch_size`进行重新调参优化。 +# ![MindSpore Logo](https://gitee.com/mindspore/mindspore/raw/master/docs/MindSpore-logo.png) + +## 欢迎来到MindSpore ModelZoo + +MindSpore models仓中提供了不同任务领域，经典的SOTA模型实现和端到端解决方案。目的是方便MindSpore用户更加方便的利用MindSpore进行研究和产品开发。 + +为了让开发者更好地体验MindSpore框架优势，我们将陆续增加更多的典型网络和相关预训练模型。如果您对ModelZoo有任何需求，请通过[Gitee](https://gitee.com/mindspore/mindspore/issues)或[MindSpore](https://bbs.huaweicloud.com/forum/forum-1076-1.html)与我们联系，我们将及时处理。 + +| 目录 | 描述 | +|------------------------| ------------------------------------------------------------ | +| [official](official) | • 业界SOTA算法模型实现
• MindSpore团队官方维护| +| [research](research) | • 业界前沿研究类算法模型实现
• 研究人员/机构维护 | +| [community](community) | • github/gitee 生态AI/ML repos powered by MindSpore | + + + + +## 免责声明 + +MindSpore仅提供下载和预处理公共数据集的脚本。我们不拥有这些数据集，也不对它们的质量负责或维护。请确保您具有在数据集许可下使用该数据集的权限。在这些数据集上训练的模型仅用于非商业研究和教学目的。 + +致数据集拥有者：如果您不希望将数据集包含在MindSpore中，或者希望以任何方式对其进行更新，我们将根据要求删除或更新所有公共内容。请通过GitHub或Gitee与我们联系。非常感谢您对这个社区的理解和贡献。 + +MindSpore已获得Apache 2.0许可，请参见LICENSE文件。 + +## 许可证 + +[Apache 2.0许可证](https://gitee.com/mindspore/mindspore/blob/master/LICENSE) + +## FAQ + +想要获取更多关于`MindSpore`框架使用本身的FAQ问题的，可以参考[官网FAQ](https://www.mindspore.cn/docs/zh-CN/master/faq/installation.html) + +- **Q: 直接使用models下的模型出现内存不足错误，例如*Failed to alloc memory pool memory*, 该怎么处理?** + + **A**: 直接使用models下的模型出现内存不足的典型原因是由于运行模式（`PYNATIVE_MODE`)、运行环境配置、License控制（AI-TOKEN）的不同造成的： + - `PYNATIVE_MODE`通常比`GRAPH_MODE`使用更多内存，尤其是在需要进行反向传播计算的训练图中，当前有2种方法可以尝试解决该问题。 + 方法1：你可以尝试使用一些更小的batch size； + 方法2：添加context.set_context(mempool_block_size="XXGB")，其中，“XX”当前最大有效值可设置为“31”。 + 如果将方法1与方法2结合使用，效果会更好。 + - 运行环境由于NPU的核数、内存等配置不同也会产生类似问题。 + - License控制（AI-TOKEN）的不同档位会造成执行过程中内存开销不同，也可以尝试使用一些更小的batch size。 + +- **Q: 一些网络运行中报错接口不存在，例如cannot import，该怎么处理?** + + **A**: 优先检查一下获取网络脚本的分支，与所使用的MindSpore版本是否一致，部分新分支中的模型脚本会使用一些新版本MindSpore才支持的接口，从而在使用老版本MindSpore时会发生报错. + +- **Q: 一些模型描述中提到的*RANK_TABLE_FILE*文件，是什么？** + + **A**: *RANK_TABLE_FILE*是一个Ascend环境上用于指定分布式集群信息的文件，更多信息可以参考生成工具[hccl_toos](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)和[分布式并行训练教程](https://mindspore.cn/docs/programming_guide/zh-CN/r1.5/distributed_training_ascend.html#id4) + +- **Q: 在windows环境上要怎么运行网络脚本？** + + **A**: 多数模型都是使用bash作为启动脚本，在Windows环境上无法直接使用bash命令，你可以考虑直接运行python命令而不是bash启动脚本 ，如果你确实想需要使用bash脚本，你可以考虑使用以下几种方法来运行模型： + 1. 使用虚拟环境，可以构造一个linux的虚拟机或docker容器，然后在虚拟环境中运行脚本 + 2. 使用WSL，可以开启Windows的linux子系统来在Windows系统中运行linux，然后再WSL中运行脚本。 + 3. 使用Windows Bash，需要获取一个可以直接在Windows上运行bash的环境，常见的选择是[cygwin](http://www.cygwin.com)或[git bash](https://gitforwindows.org) + 4. 跳过bash脚本，直接调用python程序。 + +- **Q: 网络在310推理时出现编译失败，报错信息指向gflags，例如*undefined reference to 'google::FlagRegisterer::FlagRegisterer'*，该怎么处理?** + + **A**: 优先检查一下环境GCC版本和gflags版本是否匹配，可以参考[官方链接](https://www.mindspore.cn/install)安装对应的GCC版本，[gflags](https://github.com/gflags/gflags/archive/v2.2.2.tar.gz)安装gflags。你需要保证所使用的组件之间是ABI兼容的，更多信息可以参考[_GLIBCXX_USE_CXX11_ABI](https://gcc.gnu.org/onlinedocs/libstdc++/manual/using_dual_abi.html) + +- **Q: 在Mac系统上加载mindrecord格式的数据集出错,例如*Invalid file, failed to open files for reading mindrecord files.*，该怎么处理?** + + **A**: 优先使用*ulimit -a*检查系统限制，如果*file descriptors*数量为256（默认值），需要使用*ulimit -n 1024*将其设置为1024（或者更大的值）。之后再检查文件是否损坏或者被修改。 + +- **Q: 我在多台服务器构成的大集群上进行训练，但是得到的精度比预期要低，该怎么办？** + + **A**: 当前模型库中的大部分模型只在单机内进行过验证，最大使用8卡进行训练。由于MindSpore训练时指定的`batch_size`是单卡的，所以当单机8卡升级到多机时，会导致全局的`global_batch_size`变大，这就导致需要针对当前多机场景的`global_batch_size`进行重新调参优化。 diff --git a/official/README.md b/official/README.md new file mode 100644 index 000000000..64cc227ea --- /dev/null +++ b/official/README.md @@ -0,0 +1,116 @@ + +### 官方标准模型 + +#### WHAT IS NEW: +- We've done code refactoring for classic SOTA models,modularized data processing, model definition&creation, training process and other common components with new lanched MindSpore CV/NLP/Audio/Yolo/OCR Series toolbox +- Old models were implemented by original MindSpore API with some tricks for training process speedup + + +#### +**** +#### + +### Computer Vision +#### Image Classification（backbone） +| model | mindcv recipe | vanilla mindspore +:-: | :-: | :-: +| vgg | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/) +| resnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | [link](https://gitee.com/zwiori/models/tree/readme/official/cv/ResNet) | +| resnetv2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnetv2) | +| dpn | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | +| densenet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | +| senet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | +| sknet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | +| resnext | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | +| rexnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | +| resnest | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnest) | +| res2net | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | +| googlenet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/googlenet) | +| inceptionv3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inception_v3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv3) | +| inceptionv4 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inception_v4) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv4) | +| mobilenet v1 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv1) | +| mobilenet v2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | +| mobilenet v3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv3) | +| shufflenet v1 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenet_v1) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv1) | +| shufflenet v2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenet_v2) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv2) | +| xception | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/xception) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/xception) | +| ghostnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | +| nasnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/nasnet) | +| mnasnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | +| efficientnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/efficientnet)| [link](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/) | +| regnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | +| mixnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | +| hrnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/hrnet) | +| repvgg | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| bit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | +| repmlp | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repmlp) | +| convnext | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | +| vit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/VIT) | +| swin transformer | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/swintransformer) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/SwinTransformer) +| pvt | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | +| pvt v2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | +| pit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | +| coat | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | +| convit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | +| crossvit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | +| mobilevit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | +| visformer | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | +| edgenext | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | +| poolformer | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/poolformer) | +| volo | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/volo) | +| cait | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/cait) | + +### Object Detection + +#### yolo +| model | mindyolo recipe | vanilla mindspore +:-: | :-: | :-: +| yolo v3 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv3) | +| yolo v4 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov4) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv4) | +| yolo v5 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov5) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv5) | +| yolo v7 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov7) | +| yolo v8 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov8) | +| yolo x | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolovx) | + +#### Classic +| model | mind_series recipe | vanilla mindspore +:-: | :-: | :-: +| ssd | coming soon | [link](https://gitee.com/mindspore/models/tree/master/official/cv/SSD)| +| fast rcnn | coming soon | [link](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) | +| mask rcnn | coming soon | [link](https://gitee.com/mindspore/models/tree/master/official/cv/MaskRCNN/) | + +### Semantic Segmentation + +| model | mind_series recipe | vanilla mindspore +:-: | :-: | :-: +| ocrnet | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/OCRNet/) | +| deeplab v3 | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabv3) | +| deeplab v3 plus | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabV3P) | +| unet | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Unet) | +| unet3d | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Unet3d) | + +### OCR +| model | mindocr recipe | vanilla mindspore +:-: | :-: | :-: +| dbnet | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/dbnet) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/DBNet/) | +| dbnet++ | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/dbnet) | | +| psenet | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/psenet) | | +| east | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/east) | | +| fcenet | coming soon | | +| crnn | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/crnn) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/CRNN/)| +| rare(crnn_seq2seq) | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/rare) | | +| svtr | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/svtr) | | + + + +## Disclaimers + +Mindspore only provides scripts that downloads and preprocesses public datasets. We do not own these datasets and are not responsible for their quality or maintenance. Please make sure you have permission to use the dataset under the dataset’s license. The models trained on these dataset are for non-commercial research and educational purpose only. + +To dataset owners: we will remove or update all public content upon request if you don’t want your dataset included on Mindspore, or wish to update it in any way. Please contact us through a Github/Gitee issue. Your understanding and contribution to this community is greatly appreciated. + +MindSpore is Apache 2.0 licensed. Please see the LICENSE file. + +## License + +[Apache License 2.0](https://gitee.com/mindspore/mindspore/blob/master/LICENSE) \ No newline at end of file diff --git a/official/README_CN.md b/official/README_CN.md new file mode 100644 index 000000000..762b3239c --- /dev/null +++ b/official/README_CN.md @@ -0,0 +1,116 @@ + +### 官方标准模型 + +#### WHAT IS NEW: +- 我们对经典SOTA模型进行了重构，模块化数据处理，模型定义，训练流程等常用组件，推出MindSpore CV/NLP/Audio/Yolo/OCR等系列 +- 原models仓模型实现是基于MindSpore原生API，并且有一定训练推理加速优化 + + +#### +**** +#### + +### 计算机视觉 +#### 图像分类（骨干类） +| model | mindcv recipe | vanilla mindspore +:-: | :-: | :-: +| vgg | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/VGG/) +| resnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | [link](https://gitee.com/zwiori/models/tree/readme/official/cv/ResNet) | +| resnetv2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnetv2) | +| dpn | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | +| densenet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | +| senet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | +| sknet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | +| resnext | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | +| rexnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | +| resnest | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnest) | +| res2net | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | +| googlenet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/googlenet) | +| inceptionv3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inception_v3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv3) | +| inceptionv4 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inception_v4) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/inceptionv4) | +| mobilenet v1 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv1) | +| mobilenet v2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | +| mobilenet v3 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/MobileNet/mobilenetv3) | +| shufflenet v1 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenet_v1) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv1) | +| shufflenet v2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenet_v2) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/ShuffleNet/shufflenetv2) | +| xception | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/xception) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Inception/xception) | +| ghostnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | +| nasnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/nasnet) | +| mnasnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | +| efficientnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/efficientnet)| [link](https://gitee.com/mindspore/models/tree/master/official/cv/Efficientnet/) | +| regnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | +| mixnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | +| hrnet | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/hrnet) | +| repvgg | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | +| bit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | +| repmlp | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repmlp) | +| convnext | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | +| vit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/VIT) | +| swin transformer | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/swintransformer) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/SwinTransformer) +| pvt | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | +| pvt v2 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | +| pit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | +| coat | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | +| convit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | +| crossvit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | +| mobilevit | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | +| visformer | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | +| edgenext | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | +| poolformer | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/poolformer) | +| volo | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/volo) | +| cait | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/cait) | + +### 目标检测 + +#### yolo +| model | mindyolo recipe | vanilla mindspore +:-: | :-: | :-: +| yolo v3 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv3) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv3) | +| yolo v4 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov4) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv4) | +| yolo v5 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov5) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/YOLOv5) | +| yolo v7 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov7) | +| yolo v8 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov8) | +| yolo x | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolovx) | + +#### 经典 +| model | mind_series recipe | vanilla mindspore +:-: | :-: | :-: +| ssd | coming soon | [link](https://gitee.com/mindspore/models/tree/master/official/cv/SSD)| +| fast rcnn | coming soon | [link](https://gitee.com/mindspore/models/tree/master/official/cv/FasterRCNN) | +| mask rcnn | coming soon | [link](https://gitee.com/mindspore/models/tree/master/official/cv/MaskRCNN/) | + +### 语义分割 + +| model | mind_series recipe | vanilla mindspore +:-: | :-: | :-: +| ocrnet | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/OCRNet/) | +| deeplab v3 | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabv3) | +| deeplab v3 plus | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/DeepLabV3P) | +| unet | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Unet) | +| unet3d | | [link](https://gitee.com/mindspore/models/tree/master/official/cv/Unet3d) | + +### OCR +| model | mindocr recipe | vanilla mindspore +:-: | :-: | :-: +| dbnet | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/dbnet) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/DBNet/) | +| dbnet++ | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/dbnet) | | +| psenet | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/psenet) | | +| east | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/east) | | +| fcenet | coming soon | | +| crnn | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/crnn) | [link](https://gitee.com/mindspore/models/tree/master/official/cv/CRNN/)| +| rare(crnn_seq2seq) | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/rare) | | +| svtr | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/svtr) | | + + + +## 免责声明 + +MindSpore仅提供下载和预处理公共数据集的脚本。我们不拥有这些数据集，也不对它们的质量负责或维护。请确保您具有在数据集许可下使用该数据集的权限。在这些数据集上训练的模型仅用于非商业研究和教学目的。 + +致数据集拥有者：如果您不希望将数据集包含在MindSpore中，或者希望以任何方式对其进行更新，我们将根据要求删除或更新所有公共内容。请通过GitHub或Gitee与我们联系。非常感谢您对这个社区的理解和贡献。 + +MindSpore已获得Apache 2.0许可，请参见LICENSE文件。 + +## 许可证 + +[Apache 2.0许可证](https://gitee.com/mindspore/mindspore/blob/master/LICENSE) diff --git a/research/README.md b/research/README.md index f0093f992..c28378df5 100644 --- a/research/README.md +++ b/research/README.md @@ -1,313 +1 @@ -## 研究机构贡献之算法模型 -以下算法模型来自业界生态伙伴科研机构等，非官方团队维护，如有算法模型需求，请通过[mindspore-lab/models/issue](https://github.com/mindspore-lab/models/issues)联系我们 - -| 领域 | 子领域 | 网络 | Ascend | GPU | CPU | -|:------ |:------| :----------- |:------: |:------: |:-----: | -| 推荐 | 推荐系统 | [naml](https://gitee.com/mindspore/models/tree/master/research/recommend/naml) |✅| ✅ | | -| 推荐 | 推荐系统 | [ncf](https://gitee.com/mindspore/models/tree/master/research/recommend/ncf) |✅| ✅ | | -| 图像 | 图像去噪 | [brdnet](https://gitee.com/mindspore/models/tree/master/research/cv/brdnet) |✅| | | -| 图像 | 目标检测 | [centerface](https://gitee.com/mindspore/models/tree/master/research/cv/centerface) |✅| ✅ | ✅ | -| 图像 | 文本识别 | [cnnctc](https://gitee.com/mindspore/models/tree/master/research/cv/cnnctc) |✅| ✅ | ✅ | -| 图像 | 文本识别 | [crnn_seq2seq_ocr](https://gitee.com/mindspore/models/tree/master/research/cv/crnn_seq2seq_ocr) |✅| | | -| 图像 | 目标检测 | [darknet53](https://gitee.com/mindspore/models/tree/master/research/cv/darknet53) | | ✅ | | -| 图像 | 图像去噪 | [dncnn](https://gitee.com/mindspore/models/tree/master/research/cv/dncnn) | | ✅ | | -| 图像 | 文本检测 | [east](https://gitee.com/mindspore/models/tree/master/research/cv/east) |✅| ✅ | | -| 图像 | 文本识别 | [essay-recogination](https://gitee.com/mindspore/models/tree/master/research/cv/essay-recogination) | | ✅ | | -| 图像 | 语义分割 | [fastscnn](https://gitee.com/mindspore/models/tree/master/research/cv/fastscnn) |✅| | | -| 图像 | 语义分割 | [FCN8s](https://gitee.com/mindspore/models/tree/master/research/cv/FCN8s) |✅| ✅ | | -| 图像 | 图像去噪 | [LearningToSeeInTheDark](https://gitee.com/mindspore/models/tree/master/research/cv/LearningToSeeInTheDark) |✅| | | -| 图像 | 图像分类 | [lenet](https://gitee.com/mindspore/models/tree/master/research/cv/lenet) |✅| ✅ | ✅ | -| 图像 | 人群计数 | [MCNN](https://gitee.com/mindspore/models/tree/master/research/cv/MCNN) |✅| ✅ | | -| 图像 | 图像分类 | [nasnet](https://gitee.com/mindspore/models/tree/master/research/cv/nasnet) |✅| ✅ | | -| 图像 | 图像质量评估 | [nima](https://gitee.com/mindspore/models/tree/master/research/cv/nima) |✅| ✅ | | -| 图像 | 相机重定位 | [posenet](https://gitee.com/mindspore/models/tree/master/research/cv/PoseNet) |✅| ✅ | | -| 图像 | 视频预测学习 | [predrnn++](https://gitee.com/mindspore/models/tree/master/research/cv/predrnn++) |✅| | | -| 图像 | 文本检测 | [psenet](https://gitee.com/mindspore/models/tree/master/research/cv/psenet) |✅| ✅ | | -| 图像 | 图像超分 | [RDN](https://gitee.com/mindspore/models/tree/master/research/cv/RDN) |✅| ✅ | | -| 图像 | 图像分类 | [simclr](https://gitee.com/mindspore/models/tree/master/research/cv/simclr) |✅| ✅ | | -| 图像 | 关键点检测 | [simple_pose](https://gitee.com/mindspore/models/tree/master/research/cv/simple_pose) |✅| ✅ | | -| 图像 | 目标检测 | [sphereface](https://gitee.com/mindspore/models/tree/master/research/cv/sphereface) |✅| ✅ | | -| 图像 | 图像分类 | [squeezenet](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | -| 图像 | 图像分类 | [SqueezeNet_Residual](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | -| 图像 | 图像超分 | [srcnn](https://gitee.com/mindspore/models/tree/master/research/cv/srcnn) |✅| ✅ | | -| 图像 | 图像分类 | [tinydarknet](https://gitee.com/mindspore/models/tree/master/research/cv/tinydarknet) |✅| ✅ | ✅ | -| 图像 | 文本识别 | [warpctc](https://gitee.com/mindspore/models/tree/master/research/cv/warpctc) |✅| ✅ | | -| 图像 | 目标检测 | [yolov3_resnet18](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_resnet18) |✅| | | -| 推荐 | 点击率预测 | [deep_and_cross](https://gitee.com/mindspore/models/tree/master/research/recommend/deep_and_cross) | | ✅ | | -| 推荐 | 点击率预测 | [fibinet](https://gitee.com/mindspore/models/tree/master/research/recommend/fibinet) | | ✅ | | -| 文本 | 自然语言理解 | [cpm](https://gitee.com/mindspore/models/tree/master/research/nlp/cpm) |✅| ✅ | | -| 文本 | 对话 | [dgu](https://gitee.com/mindspore/models/tree/master/research/nlp/dgu) |✅| ✅ | | -| 文本 | 对话 | [duconv](https://gitee.com/mindspore/models/tree/master/research/nlp/duconv) |✅| ✅ | | -| 文本 | 情绪分类 | [emotect](https://gitee.com/mindspore/models/tree/master/research/nlp/emotect) |✅| ✅ | | -| 文本 | 自然语言理解 | [ernie](https://gitee.com/mindspore/models/tree/master/research/nlp/ernie) |✅| ✅ | | -| 文本 | 自然语言理解 | [fasttext](https://gitee.com/mindspore/models/tree/master/research/nlp/fasttext) |✅| ✅ | | -| 文本 | 自然语言理解 | [gnmt_v2](https://gitee.com/mindspore/models/tree/master/research/nlp/gnmt_v2) |✅| ✅ | | -| 文本 | 自然语言理解 | [mass](https://gitee.com/mindspore/models/tree/master/research/nlp/mass) |✅| ✅ | | -| 文本 | 自然语言理解 | [textcnn](https://gitee.com/mindspore/models/tree/master/research/nlp/textcnn) |✅| ✅ | | -| 文本 | 自然语言理解 | [tinybert](https://gitee.com/mindspore/models/tree/master/research/nlp/tinybert) |✅| ✅ | | -| 视频 | 目标追踪 | [ADNet](https://gitee.com/mindspore/models/tree/master/research/cv/ADNet) |✅| | | -| 视频 | 目标追踪 | [Deepsort](https://gitee.com/mindspore/models/tree/master/research/cv/Deepsort) |✅| ✅ | | -| 3D | 三维重建 | [cmr](https://gitee.com/mindspore/models/tree/master/research/cv/cmr) | | ✅ | | -| 3D | 三维重建 | [DecoMR](https://gitee.com/mindspore/models/tree/master/research/cv/DecoMR) | | ✅ | | -| 3D | 三维重建 | [DeepLM](https://gitee.com/mindspore/models/tree/master/research/3d/DeepLM) | | ✅ | | -| 3D | 三维重建 | [eppmvsnet](https://gitee.com/mindspore/models/tree/master/research/cv/eppmvsnet) | | ✅ | | -| 3D | 三维物体检测 | [pointpillars](https://gitee.com/mindspore/models/tree/master/research/cv/pointpillars) |✅| ✅ | | -| 语音 | 语音识别 | [ctcmodel](https://gitee.com/mindspore/models/tree/master/research/audio/ctcmodel) |✅| | | -| 语音 | 语音唤醒 | [dscnn](https://gitee.com/mindspore/models/tree/master/research/audio/dscnn) |✅| ✅ | | -| 语音 | 语音合成 | [FastSpeech](https://gitee.com/mindspore/models/tree/master/research/audio/FastSpeech) | | ✅ | | -| 语音 | 语音标注 | [fcn-4](https://gitee.com/mindspore/models/tree/master/research/audio/fcn-4) |✅| ✅ | | -| 语音 | 语音识别 | [jasper](https://gitee.com/mindspore/models/tree/master/research/audio/jasper) |✅| ✅ | | -| 语音 | 语音合成 | [wavenet](https://gitee.com/mindspore/models/tree/master/research/audio/wavenet) |✅| ✅ | | -| 图神经网络 | 图分类 | [dgcn](https://gitee.com/mindspore/models/tree/master/research/gnn/dgcn) |✅| | | -| 图神经网络 | 文本分类 | [hypertext](https://gitee.com/mindspore/models/tree/master/research/nlp/hypertext) |✅| ✅ | | -| 图神经网络 | 图分类 | [sdne](https://gitee.com/mindspore/models/tree/master/research/gnn/sdne) |✅| | | -| 图神经网络 | 社会和信息网络 | [sgcn](https://gitee.com/mindspore/models/tree/master/research/gnn/sgcn) |✅| ✅ | | -| 图神经网络 | 文本分类 | [textrcnn](https://gitee.com/mindspore/models/tree/master/research/nlp/textrcnn) |✅| ✅ | | -| 高性能计算 | 高性能计算 | [deepbsde](https://gitee.com/mindspore/models/tree/master/research/hpc/deepbsde) | | ✅ | | -| 高性能计算 | 高性能计算 | [molecular_dynamics](https://gitee.com/mindspore/models/tree/master/research/hpc/molecular_dynamics) |✅| | | -| 高性能计算 | 高性能计算 | [ocean_model](https://gitee.com/mindspore/models/tree/master/research/hpc/ocean_model) | | ✅ | | -| 高性能计算 | 高性能计算 | [pafnucy](https://gitee.com/mindspore/models/tree/master/research/hpc/pafnucy) |✅| ✅ | | -| 高性能计算 | 高性能计算 | [pfnn](https://gitee.com/mindspore/models/tree/master/research/hpc/pfnn) | | ✅ | | -| 高性能计算 | 高性能计算 | [pinns](https://gitee.com/mindspore/models/tree/master/research/hpc/pinns) | | ✅ | | -| 图像 | 图像分类 | [3D_DenseNet](https://gitee.com/mindspore/models/tree/master/research/cv/3D_DenseNet) |✅| ✅ | | -| 图像 | 语义分割 | [3dcnn](https://gitee.com/mindspore/models/tree/master/research/cv/3dcnn) |✅| ✅ | | -| 图像 | 语义分割 | [adelaide_ea](https://gitee.com/mindspore/models/tree/master/research/cv/adelaide_ea) |✅| | | -| 图像 | 文本检测 | [advanced_east](https://gitee.com/mindspore/models/tree/master/research/cv/advanced_east) |✅| ✅ | | -| 图像 | 风格转移 | [aecrnet](https://gitee.com/mindspore/models/tree/master/research/cv/aecrnet) |✅| ✅ | | -| 图像 | 重新识别 | [AlignedReID](https://gitee.com/mindspore/models/tree/master/research/cv/AlignedReID) | | ✅ | | -| 图像 | 重新识别 | [AlignedReID++](https://gitee.com/mindspore/models/tree/master/research/cv/AlignedReID++) |✅| ✅ | | -| 图像 | 姿态估计 | [AlphaPose](https://gitee.com/mindspore/models/tree/master/research/cv/AlphaPose) |✅| | | -| 图像 | 风格转移 | [APDrawingGAN](https://gitee.com/mindspore/models/tree/master/research/cv/APDrawingGAN) |✅| ✅ | | -| 图像 | 风格转移 | [ArbitraryStyleTransfer](https://gitee.com/mindspore/models/tree/master/research/cv/ArbitraryStyleTransfer) |✅| ✅ | | -| 图像 | 关键点检测 | [ArtTrack](https://gitee.com/mindspore/models/tree/master/research/cv/ArtTrack) | | ✅ | | -| 图像 | 风格转移 | [AttGAN](https://gitee.com/mindspore/models/tree/master/research/cv/AttGAN) |✅| ✅ | | -| 图像 | 图像分类 | [augvit](https://gitee.com/mindspore/models/tree/master/research/cv/augvit) | | ✅ | | -| 图像 | 图像分类 | [autoaugment](https://gitee.com/mindspore/models/tree/master/research/cv/autoaugment) |✅| ✅ | | -| 图像 | 语义分割 | [Auto-DeepLab](https://gitee.com/mindspore/models/tree/master/research/cv/Auto-DeepLab) |✅| | | -| 图像 | 神经架构搜索 | [AutoSlim](https://gitee.com/mindspore/models/tree/master/research/cv/AutoSlim) |✅| ✅ | | -| 图像 | 图像分类 | [AVA_cifar](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_cifar) |✅| ✅ | | -| 图像 | 图像分类 | [AVA_hpa](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_hpa) |✅| ✅ | | -| 图像 | 图像分类 | [cait](https://gitee.com/mindspore/models/tree/master/research/cv/cait) |✅| ✅ | | -| 图像 | 目标检测 | [CascadeRCNN](https://gitee.com/mindspore/models/tree/master/research/cv/CascadeRCNN) |✅| ✅ | | -| 图像 | 图像分类 | [CBAM](https://gitee.com/mindspore/models/tree/master/research/cv/CBAM) |✅| | | -| 图像 | 图像分类 | [cct](https://gitee.com/mindspore/models/tree/master/research/cv/cct) |✅| ✅ | | -| 图像 | 关键点检测 | [centernet](https://gitee.com/mindspore/models/tree/master/research/cv/centernet) |✅| | ✅ | -| 图像 | 关键点检测 | [centernet_det](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_det) |✅| | | -| 图像 | 关键点检测 | [centernet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet101) |✅| ✅ | | -| 图像 | 关键点检测 | [centernet_resnet50_v1](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet50_v1) |✅| | | -| 图像 | 图像生成 | [CGAN](https://gitee.com/mindspore/models/tree/master/research/cv/CGAN) |✅| ✅ | | -| 图像 | 图像分类 | [convnext](https://gitee.com/mindspore/models/tree/master/research/cv/convnext) |✅| ✅ | | -| 图像 | 图像超分 | [csd](https://gitee.com/mindspore/models/tree/master/research/cv/csd) |✅| ✅ | | -| 图像 | 图像生成 | [CTSDG](https://gitee.com/mindspore/models/tree/master/research/cv/CTSDG) | | ✅ | | -| 图像 | 图像超分 | [DBPN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) |✅| | | -| 图像 | 图像超分 | [DBPN_GAN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) |✅| | | -| 图像 | 图像生成 | [dcgan](https://gitee.com/mindspore/models/tree/master/research/cv/dcgan) |✅| ✅ | | -| 图像 | 重新识别 | [DDAG](https://gitee.com/mindspore/models/tree/master/research/cv/DDAG) |✅| ✅ | | -| 图像 | 语义分割 | [DDM](https://gitee.com/mindspore/models/tree/master/research/cv/DDM) |✅| | | -| 图像 | 语义分割 | [DDRNet](https://gitee.com/mindspore/models/tree/master/research/cv/DDRNet) |✅| ✅ | | -| 图像 | 目标检测 | [DeepID](https://gitee.com/mindspore/models/tree/master/research/cv/DeepID) |✅| ✅ | | -| 图像 | 图像检索 | [delf](https://gitee.com/mindspore/models/tree/master/research/cv/delf) |✅| | | -| 图像 | 零样本学习 | [dem](https://gitee.com/mindspore/models/tree/master/research/cv/dem) |✅| ✅ | | -| 图像 | 目标检测 | [detr](https://gitee.com/mindspore/models/tree/master/research/cv/detr) |✅| ✅ | | -| 图像 | 语义分割 | [dgcnet_res101](https://gitee.com/mindspore/models/tree/master/research/cv/dgcnet_res101) | | ✅ | | -| 图像 | 实例分割 | [dlinknet](https://gitee.com/mindspore/models/tree/master/research/cv/dlinknet) |✅| | | -| 图像 | 图像去噪 | [DnCNN](https://gitee.com/mindspore/models/tree/master/research/cv/DnCNN) |✅| | | -| 图像 | 图像分类 | [dnet_nas](https://gitee.com/mindspore/models/tree/master/research/cv/dnet_nas) |✅| | | -| 图像 | 图像分类 | [DRNet](https://gitee.com/mindspore/models/tree/master/research/cv/DRNet) |✅| ✅ | | -| 图像 | 目标检测 | [EfficientDet_d0](https://gitee.com/mindspore/models/tree/master/research/cv/EfficientDet_d0) |✅| | | -| 图像 | 图像分类 | [efficientnet-b0](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b0) |✅| | | -| 图像 | 显著性检测 | [EGnet](https://gitee.com/mindspore/models/tree/master/research/cv/EGnet) |✅| ✅ | | -| 图像 | 语义分割 | [E-NET](https://gitee.com/mindspore/models/tree/master/research/cv/E-NET) |✅| ✅ | | -| 图像 | 图像超分 | [esr_ea](https://gitee.com/mindspore/models/tree/master/research/cv/esr_ea) |✅| ✅ | | -| 图像 | 图像超分 | [ESRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/ESRGAN) |✅| ✅ | | -| 图像 | 图像分类 | [FaceAttribute](https://gitee.com/mindspore/models/tree/master/research/cv/FaceAttribute) |✅| ✅ | | -| 图像 | 目标检测 | [faceboxes](https://gitee.com/mindspore/models/tree/master/research/cv/faceboxes) |✅| | | -| 图像 | 目标检测 | [FaceDetection](https://gitee.com/mindspore/models/tree/master/research/cv/FaceDetection) |✅| ✅ | | -| 图像 | 人脸识别 | [FaceNet](https://gitee.com/mindspore/models/tree/master/research/cv/FaceNet) |✅| ✅ | | -| 图像 | 图像分类 | [FaceQualityAssessment](https://gitee.com/mindspore/models/tree/master/research/cv/FaceQualityAssessment) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [FaceRecognitionForTracking](https://gitee.com/mindspore/models/tree/master/research/cv/FaceRecognitionForTracking) |✅| | ✅ | -| 图像 | 目标检测 | [faster_rcnn_dcn](https://gitee.com/mindspore/models/tree/master/research/cv/faster_rcnn_dcn) |✅| ✅ | | -| 图像 | 图像抠图 | [FCANet](https://gitee.com/mindspore/models/tree/master/research/cv/FCANet) |✅| | | -| 图像 | 图像分类 | [FDA-BNN](https://gitee.com/mindspore/models/tree/master/research/cv/FDA-BNN) |✅| ✅ | | -| 图像 | 图像分类 | [fishnet99](https://gitee.com/mindspore/models/tree/master/research/cv/fishnet99) |✅| ✅ | | -| 图像 | 光流估计 | [flownet2](https://gitee.com/mindspore/models/tree/master/research/cv/flownet2) |✅| | | -| 图像 | 图像生成 | [gan](https://gitee.com/mindspore/models/tree/master/research/cv/gan) |✅| ✅ | | -| 图像 | 图像分类 | [GENet_Res50](https://gitee.com/mindspore/models/tree/master/research/cv/GENet_Res50) |✅| | | -| 图像 | 图像分类 | [ghostnet](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet) |✅| | | -| 图像 | 图像分类 | [ghostnet_d](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet_d) |✅| ✅ | | -| 图像 | 图像分类 | [glore_res200](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) |✅| ✅ | | -| 图像 | 图像分类 | [glore_res50](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) |✅| ✅ | | -| 图像 | 图像分类 | [hardnet](https://gitee.com/mindspore/models/tree/master/research/cv/hardnet) |✅| ✅ | | -| 图像 | 边缘检测 | [hed](https://gitee.com/mindspore/models/tree/master/research/cv/hed) |✅| ✅ | | -| 图像 | 图像生成 | [HiFaceGAN](https://gitee.com/mindspore/models/tree/master/research/cv/HiFaceGAN) | | ✅ | | -| 图像 | 图像分类 | [HourNAS](https://gitee.com/mindspore/models/tree/master/research/cv/HourNAS) | | ✅ | | -| 图像 | 图像分类 | [HRNetW48_cls](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_cls) |✅| ✅ | | -| 图像 | 语义分割 | [HRNetW48_seg](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_seg) |✅| | | -| 图像 | 图像分类 | [ibnnet](https://gitee.com/mindspore/models/tree/master/research/cv/ibnnet) |✅| ✅ | | -| 图像 | 语义分割 | [ICNet](https://gitee.com/mindspore/models/tree/master/research/cv/ICNet) |✅| | | -| 图像 | 图像分类 | [inception_resnet_v2](https://gitee.com/mindspore/models/tree/master/research/cv/inception_resnet_v2) |✅| ✅ | | -| 图像 | 图像分类 | [Inceptionv2](https://gitee.com/mindspore/models/tree/master/research/cv/Inception-v2) |✅| ✅ | | -| 图像 | 图像抠图 | [IndexNet](https://gitee.com/mindspore/models/tree/master/research/cv/IndexNet) | | ✅ | | -| 图像 | 图像生成 | [IPT](https://gitee.com/mindspore/models/tree/master/research/cv/IPT) |✅| | | -| 图像 | 图像超分 | [IRN](https://gitee.com/mindspore/models/tree/master/research/cv/IRN) |✅| ✅ | | -| 图像 | 图像分类 | [ISyNet](https://gitee.com/mindspore/models/tree/master/research/cv/ISyNet) |✅| ✅ | | -| 图像 | 图像分类 | [ivpf](https://gitee.com/mindspore/models/tree/master/research/cv/ivpf) | | ✅ | | -| 图像 | 图像去噪 | [LearningToSeeInTheDark](https://gitee.com/mindspore/models/tree/master/research/cv/LearningToSeeInTheDark) |✅| | | -| 图像 | 元学习 | [LEO](https://gitee.com/mindspore/models/tree/master/research/cv/LEO) |✅| ✅ | | -| 图像 | 目标检测 | [LightCNN](https://gitee.com/mindspore/models/tree/master/research/cv/LightCNN) |✅| ✅ | ✅ | -| 图像 | 图像超分 | [lite-hrnet](https://gitee.com/mindspore/models/tree/master/research/cv/lite-hrnet) | | ✅ | | -| 图像 | 图像分类 | [lresnet100e_ir](https://gitee.com/mindspore/models/tree/master/research/cv/lresnet100e_ir) | | ✅ | | -| 图像 | 目标检测 | [m2det](https://gitee.com/mindspore/models/tree/master/research/cv/m2det) | | ✅ | | -| 图像 | 元学习 | [MAML](https://gitee.com/mindspore/models/tree/master/research/cv/MAML) |✅| ✅ | | -| 图像 | 文本识别 | [ManiDP](https://gitee.com/mindspore/models/tree/master/research/cv/ManiDP) | | ✅ | | -| 图像 | 人脸识别 | [MaskedFaceRecognition](https://gitee.com/mindspore/models/tree/master/research/cv/MaskedFaceRecognition) |✅| | | -| 图像 | 元学习 | [meta-baseline](https://gitee.com/mindspore/models/tree/master/research/cv/meta-baseline) |✅| ✅ | | -| 图像 | 重新识别 | [MGN](https://gitee.com/mindspore/models/tree/master/research/cv/MGN) |✅| ✅ | | -| 图像 | 深度估计 | [midas](https://gitee.com/mindspore/models/tree/master/research/cv/midas) |✅| ✅ | | -| 图像 | 图像去噪 | [MIMO-UNet](https://gitee.com/mindspore/models/tree/master/research/cv/MIMO-UNet) | | ✅ | | -| 图像 | 图像分类 | [mnasnet](https://gitee.com/mindspore/models/tree/master/research/cv/mnasnet) |✅| ✅ | | -| 图像 | 图像分类 | [mobilenetv3_large](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetv3_large) |✅| | ✅ | -| 图像 | 图像分类 | [mobilenetV3_small_x1_0](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetV3_small_x1_0) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [MultiTaskNet](https://gitee.com/mindspore/models/tree/master/research/cv/PAMTRI/MultiTaskNet) |✅| ✅ | | -| 图像 | 重新识别 | [MVD](https://gitee.com/mindspore/models/tree/master/research/cv/MVD) |✅| ✅ | | -| 图像 | 目标检测 | [nas-fpn](https://gitee.com/mindspore/models/tree/master/research/cv/nas-fpn) |✅| | | -| 图像 | 图像去噪 | [Neighbor2Neighbor](https://gitee.com/mindspore/models/tree/master/research/cv/Neighbor2Neighbor) |✅| ✅ | | -| 图像 | 图像分类 | [NFNet](https://gitee.com/mindspore/models/tree/master/research/cv/NFNet) |✅| ✅ | | -| 图像 | 图像质量评估 | [nima_vgg16](https://gitee.com/mindspore/models/tree/master/research/cv/nima_vgg16) | | ✅ | | -| 图像 | 语义分割 | [nnUNet](https://gitee.com/mindspore/models/tree/master/research/cv/nnUNet) |✅| ✅ | | -| 图像 | 图像分类 | [ntsnet](https://gitee.com/mindspore/models/tree/master/research/cv/ntsnet) |✅| ✅ | | -| 图像 | 重新识别 | [osnet](https://gitee.com/mindspore/models/tree/master/research/cv/osnet) |✅| ✅ | | -| 图像 | 显著性检测 | [PAGENet](https://gitee.com/mindspore/models/tree/master/research/cv/PAGENet) |✅| ✅ | | -| 图像 | 图像检索 | [pcb](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | -| 图像 | 图像检索 | [pcb](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | -| 图像 | 图像检索 | [pcb_rpp](https://gitee.com/mindspore/models/tree/master/research/cv/pcb_rpp) | | ✅ | | -| 图像 | 图像分类 | [PDarts](https://gitee.com/mindspore/models/tree/master/research/cv/PDarts) |✅| ✅ | | -| 图像 | 图像生成 | [PGAN](https://gitee.com/mindspore/models/tree/master/research/cv/PGAN) |✅| ✅ | | -| 图像 | 图像生成 | [Pix2Pix](https://gitee.com/mindspore/models/tree/master/research/cv/Pix2Pix) |✅| ✅ | | -| 图像 | 图像分类 | [pnasnet](https://gitee.com/mindspore/models/tree/master/research/cv/pnasnet) |✅| ✅ | | -| 图像 | 图像分类 | [PoseEstNet](https://gitee.com/mindspore/models/tree/master/research/cv/PAMTRI/PoseEstNet) |✅| ✅ | | -| 图像 | 图像分类 | [ProtoNet](https://gitee.com/mindspore/models/tree/master/research/cv/ProtoNet) |✅| ✅ | | -| 图像 | 图像分类 | [proxylessnas](https://gitee.com/mindspore/models/tree/master/research/cv/proxylessnas) |✅| ✅ | | -| 图像 | 语义分割 | [PSPNet](https://gitee.com/mindspore/models/tree/master/research/cv/PSPNet) |✅| | | -| 图像 | 显著性检测 | [ras](https://gitee.com/mindspore/models/tree/master/research/cv/ras) |✅| ✅ | | -| 图像 | 图像超分 | [RCAN](https://gitee.com/mindspore/models/tree/master/research/cv/RCAN) |✅| | | -| 图像 | 目标检测 | [rcnn](https://gitee.com/mindspore/models/tree/master/research/cv/rcnn) |✅| ✅ | | -| 图像 | 图像超分 | [REDNet30](https://gitee.com/mindspore/models/tree/master/research/cv/REDNet30) |✅| ✅ | | -| 图像 | 目标检测 | [RefineDet](https://gitee.com/mindspore/models/tree/master/research/cv/RefineDet) |✅| ✅ | | -| 图像 | 语义分割 | [RefineNet](https://gitee.com/mindspore/models/tree/master/research/cv/RefineNet) |✅| ✅ | | -| 图像 | 重新识别 | [ReIDStrongBaseline](https://gitee.com/mindspore/models/tree/master/research/cv/ReIDStrongBaseline) |✅| ✅ | | -| 图像 | 图像分类 | [relationnet](https://gitee.com/mindspore/models/tree/master/research/cv/relationnet) |✅| ✅ | | -| 图像 | 图像分类 | [renas](https://gitee.com/mindspore/models/tree/master/research/cv/renas) |✅| ✅ | ✅ | -| 图像 | 语义分割 | [repvgg](https://gitee.com/mindspore/models/tree/master/research/cv/repvgg) |✅| ✅ | | -| 图像 | 语义分割 | [res2net_deeplabv3](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_deeplabv3) |✅| | ✅ | -| 图像 | 目标检测 | [res2net_faster_rcnn](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_faster_rcnn) |✅| ✅ | | -| 图像 | 目标检测 | [res2net_yolov3](https://gitee.com/mindspore/models/tree/master/research/cv/res2net_yolov3) |✅| ✅ | | -| 图像 | 图像分类 | [res2net101](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| 图像 | 图像分类 | [res2net152](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| 图像 | 图像分类 | [res2net50](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| 图像 | 图像分类 | [ResNeSt50](https://gitee.com/mindspore/models/tree/master/research/cv/ResNeSt50) |✅| ✅ | | -| 图像 | 图像分类 | [resnet50_adv_pruning](https://gitee.com/mindspore/models/tree/master/research/cv/resnet50_adv_pruning) |✅| ✅ | | -| 图像 | 图像分类 | [resnet50_bam](https://gitee.com/mindspore/models/tree/master/research/cv/resnet50_bam) |✅| ✅ | | -| 图像 | 图像分类 | [ResNet50-Quadruplet](https://gitee.com/mindspore/models/tree/master/research/cv/metric_learn) |✅| ✅ | | -| 图像 | 图像分类 | [ResNet50-Triplet](https://gitee.com/mindspore/models/tree/master/research/cv/metric_learn) |✅| ✅ | | -| 图像 | 图像分类 | [ResnetV2_101](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | -| 图像 | 图像分类 | [ResnetV2_152](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | -| 图像 | 图像分类 | [ResnetV2_50](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |✅| ✅ | | -| 图像 | 图像分类 | [resnetv2_50_frn](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2_50_frn) |✅| ✅ | | -| 图像 | 图像分类 | [resnext152_64x4d](https://gitee.com/mindspore/models/tree/master/research/cv/resnext152_64x4d) |✅| ✅ | | -| 图像 | 目标检测 | [retinaface_mobilenet0.25](https://gitee.com/mindspore/models/tree/master/research/cv/retinaface) |✅| ✅ | | -| 图像 | 目标检测 | [retinanet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet101) |✅| ✅ | | -| 图像 | 目标检测 | [retinanet_resnet152](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet152) |✅| ✅ | | -| 图像 | 目标检测 | [rfcn](https://gitee.com/mindspore/models/tree/master/research/cv/rfcn) | | ✅ | | -| 图像 | 图像分类 | [SE_ResNeXt50](https://gitee.com/mindspore/models/tree/master/research/cv/SE_ResNeXt50) |✅| | | -| 图像 | 图像分类 | [senet_resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [senet_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [se-res2net50](https://gitee.com/mindspore/models/tree/master/research/cv/res2net) |✅| ✅ | | -| 图像 | 图像分类 | [S-GhostNet](https://gitee.com/mindspore/models/tree/master/research/cv/S-GhostNet) |✅| | | -| 图像 | 姿态估计 | [simple_baselines](https://gitee.com/mindspore/models/tree/master/research/cv/simple_baselines) |✅| ✅ | | -| 图像 | 图像生成 | [SinGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SinGAN) |✅| | | -| 图像 | 图像分类 | [single_path_nas](https://gitee.com/mindspore/models/tree/master/research/cv/single_path_nas) |✅| ✅ | | -| 图像 | 图像分类 | [sknet](https://gitee.com/mindspore/models/tree/master/research/cv/sknet) |✅| ✅ | ✅ | -| 图像 | 图像分类 | [snn_mlp](https://gitee.com/mindspore/models/tree/master/research/cv/snn_mlp) | | ✅ | | -| 图像 | 目标检测 | [Spnas](https://gitee.com/mindspore/models/tree/master/research/cv/Spnas) |✅| | | -| 图像 | 图像分类 | [SPPNet](https://gitee.com/mindspore/models/tree/master/research/cv/SPPNet) |✅| ✅ | | -| 图像 | 图像分类 | [squeezenet](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) |✅| ✅ | | -| 图像 | 图像超分 | [sr_ea](https://gitee.com/mindspore/models/tree/master/research/cv/sr_ea) |✅| | | -| 图像 | 图像超分 | [SRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SRGAN) |✅| ✅ | | -| 图像 | 图像分类 | [ssc_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/ssc_resnet50) |✅| ✅ | | -| 图像 | 目标检测 | [ssd_ghostnet](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_ghostnet) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd_inception_v2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_inception_v2) | | ✅ | ✅ | -| 图像 | 目标检测 | [ssd_inceptionv2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_inceptionv2) |✅| | | -| 图像 | 目标检测 | [ssd_mobilenetV2](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd_mobilenetV2_FPNlite](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2_FPNlite) |✅| ✅ | ✅ | -| 图像 | 目标检测 | [ssd_resnet_34](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet_34) | | ✅ | | -| 图像 | 目标检测 | [ssd_resnet34](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet34) |✅| | ✅ | -| 图像 | 目标检测 | [ssd_resnet50](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_resnet50) |✅| | | -| 图像 | 姿态估计 | [StackedHourglass](https://gitee.com/mindspore/models/tree/master/research/cv/StackedHourglass) |✅| | | -| 图像 | 图像生成 | [StarGAN](https://gitee.com/mindspore/models/tree/master/research/cv/StarGAN) |✅| ✅ | | -| 图像 | 图像生成 | [STGAN](https://gitee.com/mindspore/models/tree/master/research/cv/STGAN) |✅| ✅ | | -| 图像 | 交通预测 | [stgcn](https://gitee.com/mindspore/models/tree/master/research/cv/stgcn) |✅| ✅ | | -| 图像 | 时间定位 | [tall](https://gitee.com/mindspore/models/tree/master/research/cv/tall) |✅| | | -| 图像 | 图像分类 | [TCN](https://gitee.com/mindspore/models/tree/master/research/cv/TCN) |✅| ✅ | | -| 图像 | 文本检测 | [textfusenet](https://gitee.com/mindspore/models/tree/master/research/cv/textfusenet) |✅| | | -| 图像 | 交通预测 | [tgcn](https://gitee.com/mindspore/models/tree/master/research/cv/tgcn) |✅| ✅ | | -| 图像 | 图像分类 | [tinynet](https://gitee.com/mindspore/models/tree/master/research/cv/tinynet) | | ✅ | | -| 图像 | 图像分类 | [TNT](https://gitee.com/mindspore/models/tree/master/research/cv/TNT) |✅| ✅ | | -| 图像 | 目标检测 | [u2net](https://gitee.com/mindspore/models/tree/master/research/cv/u2net) |✅| ✅ | | -| 图像 | 图像生成 | [U-GAT-IT](https://gitee.com/mindspore/models/tree/master/research/cv/U-GAT-IT) |✅| ✅ | | -| 图像 | 语义分割 | [UNet3+](https://gitee.com/mindspore/models/tree/master/research/cv/UNet3+) |✅| ✅ | | -| 图像 | 重新识别 | [VehicleNet](https://gitee.com/mindspore/models/tree/master/research/cv/VehicleNet) |✅| | | -| 图像 | 图像分类 | [ViG](https://gitee.com/mindspore/models/tree/master/research/cv/ViG) |✅| ✅ | | -| 图像 | 图像分类 | [vit_cifar](https://gitee.com/mindspore/models/tree/master/research/cv/vit_base) |✅| ✅ | | -| 图像 | 语义分割 | [vnet](https://gitee.com/mindspore/models/tree/master/research/cv/vnet) |✅| ✅ | | -| 图像 | 图像分类 | [wave_mlp](https://gitee.com/mindspore/models/tree/master/research/cv/wave_mlp) |✅| ✅ | | -| 图像 | 图像超分 | [wdsr](https://gitee.com/mindspore/models/tree/master/research/cv/wdsr) |✅| ✅ | | -| 图像 | 图像分类 | [wideresnet](https://gitee.com/mindspore/models/tree/master/research/cv/wideresnet) |✅| ✅ | | -| 图像 | 实例分割 | [Yolact++](https://gitee.com/mindspore/models/tree/master/research/cv/Yolact++) |✅| | | -| 图像 | 目标检测 | [yolov3_tiny](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_tiny) |✅| ✅ | | -| 多模态 | 多模态 | [opt](https://gitee.com/mindspore/models/tree/master/research/mm/opt) |✅| ✅ | | -| 多模态 | 多模态 | [TokenFusion](https://gitee.com/mindspore/models/tree/master/research/cv/TokenFusion) |✅| ✅ | | -| 多模态 | 多模态 | [wukong](https://gitee.com/mindspore/models/tree/master/research/mm/wukong) |✅| | | -| 推荐 | 点击率预测 | [autodis](https://gitee.com/mindspore/models/tree/master/research/recommend/autodis) |✅| ✅ | | -| 推荐 | 点击率预测 | [DIEN](https://gitee.com/mindspore/models/tree/master/research/recommend/DIEN) |✅| ✅ | | -| 推荐 | 点击率预测 | [dlrm](https://gitee.com/mindspore/models/tree/master/research/recommend/dlrm) |✅| ✅ | | -| 推荐 | 点击率预测 | [EDCN](https://gitee.com/mindspore/models/tree/master/research/recommend/EDCN) |✅| ✅ | | -| 推荐 | 点击率预测 | [Fat-DeepFFM](https://gitee.com/mindspore/models/tree/master/research/recommend/Fat-DeepFFM) |✅| ✅ | | -| 推荐 | 点击率预测 | [mmoe](https://gitee.com/mindspore/models/tree/master/research/recommend/mmoe) |✅| ✅ | | -| 文本 | 自然语言理解 | [albert](https://gitee.com/mindspore/models/tree/master/research/nlp/albert) |✅| ✅ | | -| 文本 | 情绪分类 | [atae_lstm](https://gitee.com/mindspore/models/tree/master/research/nlp/atae_lstm) |✅| ✅ | | -| 文本 | 对话 | [dam](https://gitee.com/mindspore/models/tree/master/research/nlp/dam) |✅| | | -| 文本 | 语言模型 | [gpt2](https://gitee.com/mindspore/models/tree/master/research/nlp/gpt2) |✅| | | -| 文本 | 知识图嵌入 | [hake](https://gitee.com/mindspore/models/tree/master/research/nlp/hake) | | ✅ | | -| 文本 | 自然语言理解 | [ktnet](https://gitee.com/mindspore/models/tree/master/research/nlp/ktnet) |✅| ✅ | | -| 文本 | 命名实体识别 | [lstm_crf](https://gitee.com/mindspore/models/tree/master/research/nlp/lstm_crf) |✅| | | -| 文本 | 自然语言理解 | [luke](https://gitee.com/mindspore/models/tree/master/research/nlp/luke) |✅| ✅ | | -| 文本 | 知识图嵌入 | [rotate](https://gitee.com/mindspore/models/tree/master/research/nlp/rotate) |✅| ✅ | | -| 文本 | 情绪分类 | [senta](https://gitee.com/mindspore/models/tree/master/research/nlp/senta) |✅| ✅ | | -| 文本 | 机器翻译 | [seq2seq](https://gitee.com/mindspore/models/tree/master/research/nlp/seq2seq) |✅| | | -| 文本 | 词嵌入 | [skipgram](https://gitee.com/mindspore/models/tree/master/research/nlp/skipgram) |✅| ✅ | | -| 文本 | 机器翻译 | [speech_transformer](https://gitee.com/mindspore/models/tree/master/research/nlp/speech_transformer) |✅| | | -| 文本 | 预训练 | [ternarybert](https://gitee.com/mindspore/models/tree/master/research/nlp/ternarybert) |✅| ✅ | | -| 文本 | 自然语言理解 | [tprr](https://gitee.com/mindspore/models/tree/master/research/nlp/tprr) |✅| | | -| 文本 | 自然语言理解 | [transformer_xl](https://gitee.com/mindspore/models/tree/master/research/nlp/transformer_xl) |✅| ✅ | | -| 文本 | 知识图嵌入 | [transX](https://gitee.com/mindspore/models/tree/master/research/nlp/transX) | | ✅ | | -| 视频 | 视频分类 | [AttentionCluster](https://gitee.com/mindspore/models/tree/master/research/cv/AttentionCluster) |✅| ✅ | | -| 视频 | 其他 | [DYR](https://gitee.com/mindspore/models/tree/master/research/nlp/DYR) |✅| | | -| 视频 | 视频分类 | [ecolite](https://gitee.com/mindspore/models/tree/master/research/cv/ecolite) |✅| | | -| 视频 | 目标追踪 | [fairmot](https://gitee.com/mindspore/models/tree/master/research/cv/fairmot) |✅| ✅ | | -| 视频 | 视频分类 | [I3D](https://gitee.com/mindspore/models/tree/master/research/cv/I3D) |✅| | | -| 视频 | 目标追踪 | [JDE](https://gitee.com/mindspore/models/tree/master/research/cv/JDE) | | ✅ | | -| 视频 | 视频分割 | [OSVOS](https://gitee.com/mindspore/models/tree/master/research/cv/OSVOS) | | ✅ | | -| 视频 | 视频分类 | [r2plus1d](https://gitee.com/mindspore/models/tree/master/research/cv/r2plus1d) |✅| ✅ | | -| 视频 | 视频超分 | [rbpn](https://gitee.com/mindspore/models/tree/master/research/cv/rbpn) |✅| | | -| 视频 | 视频分类 | [resnet3d](https://gitee.com/mindspore/models/tree/master/research/cv/resnet3d) |✅| | | -| 视频 | 目标追踪 | [SiamFC](https://gitee.com/mindspore/models/tree/master/research/cv/SiamFC) |✅| | | -| 视频 | 目标追踪 | [siamRPN](https://gitee.com/mindspore/models/tree/master/research/cv/siamRPN) |✅| ✅ | | -| 视频 | 视频分类 | [slowfast](https://gitee.com/mindspore/models/tree/master/research/cv/slowfast) |✅| ✅ | | -| 视频 | 视频分类 | [stnet](https://gitee.com/mindspore/models/tree/master/research/cv/stnet) |✅| | | -| 视频 | 目标追踪 | [tracktor](https://gitee.com/mindspore/models/tree/master/research/cv/tracktor) | | ✅ | | -| 视频 | 目标追踪 | [tracktor++](https://gitee.com/mindspore/models/tree/master/research/cv/tracktor++) |✅| ✅ | | -| 视频 | 视频分类 | [trn](https://gitee.com/mindspore/models/tree/master/research/cv/trn) | | ✅ | | -| 视频 | 视频分类 | [tsm](https://gitee.com/mindspore/models/tree/master/research/cv/tsm) |✅| ✅ | | -| 视频 | 视频分类 | [tsn](https://gitee.com/mindspore/models/tree/master/research/cv/tsn) |✅| ✅ | | - + coming soon \ No newline at end of file -- Gitee From 099ac566c1827354705a6d8e69e900b658918f7b Mon Sep 17 00:00:00 2001 From: zhaoting Date: Fri, 2 Jun 2023 07:32:05 +0000 Subject: [PATCH 4/4] Update official/README.md --- official/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/official/README.md b/official/README.md index 64cc227ea..f89b87384 100644 --- a/official/README.md +++ b/official/README.md @@ -1,5 +1,5 @@ -### 官方标准模型 +### Official models #### WHAT IS NEW: - We've done code refactoring for classic SOTA models,modularized data processing, model definition&creation, training process and other common components with new lanched MindSpore CV/NLP/Audio/Yolo/OCR Series toolbox -- Gitee