diff --git a/README.md b/README.md index 3a944ced333a235be3b0042cb1c22bfe1957fcb5..960767b801b97a45ea54448379b33dd245f6862c 100644 --- a/README.md +++ b/README.md @@ -48,7 +48,7 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, |Computer Vision (CV) | Image Classification | [ResNeXt50](https://gitee.com/mindspore/models/tree/master/official/cv/resnext) | ✅ | ✅ | | |Computer Vision (CV) | Image Classification | [ResNeXt101](https://gitee.com/mindspore/models/tree/master/official/cv/resnext) | ✅ | | | |Computer Vision (CV) | Image Classification | [SE-ResNet50](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | ✅ | | | -| Computer Vision（CV） | Image Classification | [SE-ResNext50](https://gitee.com/mindspore/models/tree/master/official/cv/SE_ResNeXt50) | ✅ | | | +| Computer Vision（CV） | Image Classification | [SE-ResNext50](https://gitee.com/mindspore/models/tree/master/official/cv/se_resnext50) | ✅ | | | | Computer Vision (CV) | Image Classification | [ShuffleNetV1](https://gitee.com/mindspore/models/tree/master/official/cv/shufflenetv1) | ✅ | | | | Computer Vision (CV) | Image Classification | [ShuffleNetV2](https://gitee.com/mindspore/models/tree/master/official/cv/shufflenetv2) | | ✅ | | | Computer Vision (CV) | Image Classification | [SqueezeNet](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) | ✅ | | | @@ -83,8 +83,9 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | Computer Vision (CV) | Semantic Segmentation | [U-Net2D (Medical)](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | ✅ | | | | Computer Vision (CV) | Semantic Segmentation | [U-Net3D (Medical)](https://gitee.com/mindspore/models/tree/master/official/cv/unet3d) | ✅ | | | | Computer Vision (CV) | Semantic Segmentation | [U-Net++](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | ✅ | | | -| Computer Vision (CV) | Semantic Segmentation | [Fast-SCNN](https://gitee.com/mindspore/models/tree/master/official/cv/fasterscnn) | ✅ | | | +| Computer Vision (CV) | Semantic Segmentation | [Fast-SCNN](https://gitee.com/mindspore/models/tree/master/official/cv/fastscnn) | ✅ | | | | Computer Vision (CV) | Semantic Segmentation | [FCN8s](https://gitee.com/mindspore/models/tree/master/official/cv/FCN8s) | ✅ | | | +| Computer Vision (CV) | 6DoF Pose Estimation | [PVNet](https://gitee.com/mindspore/models/tree/master/official/cv/pvnet) | ✅ | | | | Computer Vision (CV) | Keypoint Detection | [OpenPose](https://gitee.com/mindspore/models/tree/master/official/cv/openpose) | ✅ | | | | Computer Vision (CV) | Keypoint Detection | [SimplePoseNet](https://gitee.com/mindspore/models/tree/master/official/cv/simple_pose) | ✅ | | | | Computer Vision (CV) | Scene Text Detection | [East](https://gitee.com/mindspore/models/tree/master/official/cv/east) | ✅ | | | @@ -94,6 +95,7 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | Computer Vision (CV) | Scene Text Recognition |[CRNN-Seq2Seq-OCR](https://gitee.com/mindspore/models/tree/master/official/cv/crnn_seq2seq_ocr) | ✅ | | | | Computer Vision (CV) | Scene Text Recognition |[WarpCTC](https://gitee.com/mindspore/models/tree/master/official/cv/warpctc) | ✅ | | | | Computer Vision (CV) | Defect Detection |[ssim-ae](https://gitee.com/mindspore/models/tree/master/official/cv/ssim-ae) | ✅ | | | +| Computer Vision (CV) | Defect Detection |[PatchCore](https://gitee.com/mindspore/models/tree/master/official/cv/patchcore) | ✅ | | | | Computer Vision (CV) | Face Detection | [RetinaFace-ResNet50](https://gitee.com/mindspore/models/tree/master/official/cv/retinaface_resnet50) | ✅ | ✅ | | | Computer Vision (CV) | Face Detection | [CenterFace](https://gitee.com/mindspore/models/tree/master/official/cv/centerface) | ✅ | | | | Computer Vision (CV) | Face Detection | [SphereFace](https://gitee.com/mindspore/models/tree/master/official/cv/sphereface) | ✅ | | | @@ -103,6 +105,7 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | Computer Vision (CV) | Image Matting | [Semantic Human Matting](https://gitee.com/mindspore/models/tree/master/official/cv/semantic_human_matting) | ✅ | | | | Computer Vision (CV) | Video Classification | [C3D](https://gitee.com/mindspore/models/tree/master/official/cv/c3d) | ✅ | | | | Computer Vision (CV) | Image Super-Resolution | [SRCNN](https://gitee.com/mindspore/models/tree/master/official/cv/srcnn) | ✅ | | | +| Computer Vision (CV) | Image Super-Resolution |[RDN](https://gitee.com/mindspore/models/tree/master/official/cv/RDN) | ✅ | ✅ | | | Computer Vision (CV) | Image Denoising | [BRDNet](https://gitee.com/mindspore/models/tree/master/official/cv/brdnet) | ✅ | | | | Computer Vision (CV) | Image Denoising | [DnCNN](https://gitee.com/mindspore/models/tree/master/official/cv/dncnn) | ✅ | | | | Computer Vision (CV) | Image Denoising | [Learning-to-See-in-the-Dark](https://gitee.com/mindspore/models/tree/master/official/cv/LearningToSeeInTheDark) | ✅ | | | @@ -138,12 +141,12 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | Computer Vision (CV) | Image Classification |[3D Densenet](https://gitee.com/mindspore/models/tree/master/research/cv/3D_DenseNet) | ✅ | | | | Computer Vision (CV) | Image Classification |[Auto Augment](https://gitee.com/mindspore/models/tree/master/research/cv/autoaugment) | ✅ | | | | Computer Vision (CV) | Image Classification |[AVA](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_cifar) | ✅ | | | -| Computer Vision (CV) | Image Classification |[CCT](https://gitee.com/mindspore/models/tree/master/research/cv/CCT) | ✅ | | | +| Computer Vision (CV) | Image Classification |[CCT](https://gitee.com/mindspore/models/tree/master/research/cv/cct) | ✅ | | | | Computer Vision (CV) | Image Classification |[dnet-nas](https://gitee.com/mindspore/models/tree/master/research/cv/dnet_nas) | ✅ | | | -| Computer Vision (CV) | Image Classification |[Efficientnet-b0](https://gitee.com/mindspore/models/tree/master/research/cv/efficient-b0) | ✅ | | | -| Computer Vision (CV) | Image Classification |[Efficientnet-b1](https://gitee.com/mindspore/models/tree/master/research/cv/efficient-b1) | ✅ | | | -| Computer Vision (CV) | Image Classification |[Efficientnet-b2](https://gitee.com/mindspore/models/tree/master/research/cv/efficient-b2) | ✅ | | | -| Computer Vision (CV) | Image Classification |[Efficientnet-b3](https://gitee.com/mindspore/models/tree/master/research/cv/efficient-b3) | ✅ | | | +| Computer Vision (CV) | Image Classification |[Efficientnet-b0](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b0) | ✅ | | | +| Computer Vision (CV) | Image Classification |[Efficientnet-b1](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b1) | ✅ | | | +| Computer Vision (CV) | Image Classification |[Efficientnet-b2](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b2) | ✅ | | | +| Computer Vision (CV) | Image Classification |[Efficientnet-b3](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b3) | ✅ | | | | Computer Vision (CV) | Image Classification |[FDA-BNN](https://gitee.com/mindspore/models/tree/master/research/cv/FDA-BNN) | ✅ | | | | Computer Vision (CV) | Image Classification |[fishnet99](https://gitee.com/mindspore/models/tree/master/research/cv/fishnet99) | ✅ | | | | Computer Vision (CV) | Image Classification |[GENET](https://gitee.com/mindspore/models/tree/master/research/cv/GENet_Res50) | ✅ | | | @@ -159,10 +162,10 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | Computer Vision (CV) | Image Classification |[META-Baseline](https://gitee.com/mindspore/models/tree/master/research/cv/meta-baseline) | ✅ | | | | Computer Vision (CV) | Image Classification |[MNasNet](https://gitee.com/mindspore/models/tree/master/research/cv/mnasnet) | ✅ | | | | Computer Vision (CV) | Image Classification |[MobilenetV3-Large](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetv3_large) | ✅ | | | -| Computer Vision (CV) | Image Classification |[MobilenetV3-Small](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetv3_small_x1_0) | ✅ | | | +| Computer Vision (CV) | Image Classification |[MobilenetV3-Small](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetV3_small_x1_0) | ✅ | | | | Computer Vision (CV) | Image Classification |[NFNet-F0](https://gitee.com/mindspore/models/tree/master/research/cv/NFNet) | ✅ | | | | Computer Vision (CV) | Image Classification |[ntsnet](https://gitee.com/mindspore/models/tree/master/research/cv/ntsnet) | ✅ | | | -| Computer Vision (CV) | Image Classification |[Pdarts](https://gitee.com/mindspore/models/tree/master/research/cv/Pdarts) | ✅ | | | +| Computer Vision (CV) | Image Classification |[Pdarts](https://gitee.com/mindspore/models/tree/master/research/cv/PDarts) | ✅ | | | | Computer Vision (CV) | Image Classification |[PNASNet-5](https://gitee.com/mindspore/models/tree/master/research/cv/pnasnet) | ✅ | | | | Computer Vision (CV) | Image Classification |[ProtoNet](https://gitee.com/mindspore/models/tree/master/research/cv/ProtoNet) | ✅ | | | | Computer Vision (CV) | Image Classification |[Proxylessnas](https://gitee.com/mindspore/models/tree/master/research/cv/proxylessnas) | ✅ | | | @@ -205,7 +208,7 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | Computer Vision (CV) | Face Recognition | [LightCNN](https://gitee.com/mindspore/models/tree/master/research/cv/LightCNN) | ✅ | | | | Computer Vision (CV) | Object Detection | [Spnas](https://gitee.com/mindspore/models/tree/master/research/cv/Spnas) | ✅ | | | | Computer Vision (CV) | Object Detection | [SSD-GhostNet](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_ghostnet) | ✅ | | | -| Computer Vision (CV） | Object Detection | [EGNet](https://gitee.com/mindspore/models/tree/master/research/cv/EGNet) | ✅ | | | +| Computer Vision (CV） | Object Detection | [EGNet](https://gitee.com/mindspore/models/tree/master/research/cv/EGnet) | ✅ | | | | Computer Vision (CV) | Object Detection | [FasterRCNN-FPN-DCN](https://gitee.com/mindspore/models/tree/master/research/cv/faster_rcnn_dcn) | ✅ | | | | Computer Vision (CV) | Object Detection | [NAS-FPN](https://gitee.com/mindspore/models/tree/master/research/cv/nas-fpn) | ✅ | | | | Computer Vision (CV) | Object Detection | [RAS](https://gitee.com/mindspore/models/tree/master/research/cv/ras) | ✅ | | | @@ -223,9 +226,8 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | Computer Vision (CV) | Object Detection | [U-2-Net](https://gitee.com/mindspore/models/tree/master/research/cv/u2net) | ✅ | | | | Computer Vision (CV) | Object Detection | [YOLOV3-tiny](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_tiny) | ✅ | | | | Computer Vision (CV) | Object Tracking |[SiamFC](https://gitee.com/mindspore/models/tree/master/research/cv/SiamFC) | ✅ | | | -| Computer Vision (CV) | Object Tracking |[SiamRPN](https://gitee.com/mindspore/models/tree/master/research/cv/SiamRPN) | ✅ | | | +| Computer Vision (CV) | Object Tracking |[SiamRPN](https://gitee.com/mindspore/models/tree/master/research/cv/siamRPN) | ✅ | | | | Computer Vision (CV) | Object Tracking |[FairMOT](https://gitee.com/mindspore/models/tree/master/research/cv/fairmot) | ✅ | | | -| Computer Vision (CV) | Defect Detection |[PathCore](https://gitee.com/mindspore/models/tree/master/research/cv/PathCore) | ✅ | | | | Computer Vision (CV) | Key Point Detection | [CenterNet](https://gitee.com/mindspore/models/tree/master/research/cv/centernet) | ✅ | | ✅ | | Computer Vision (CV) | Key Point Detection | [CenterNet-hourglass](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_det) | ✅ | | | | Computer Vision (CV) | Key Point Detection | [CenterNet-resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet101) | ✅ | | | @@ -252,12 +254,11 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | Computer Vision (CV) | Image Super-Resolution |[CSD](https://gitee.com/mindspore/models/tree/master/research/cv/csd) | ✅ | | | | Computer Vision (CV) | Image Super-Resolution |[DBPN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) | ✅ | | | | Computer Vision (CV) | Image Super-Resolution |[EDSR](https://gitee.com/mindspore/models/tree/master/research/cv/EDSR) | ✅ | | | -| Computer Vision (CV) | Image Super-Resolution |[esr-ea](https://gitee.com/mindspore/models/tree/master/research/cv/esr-ea) | ✅ | | | +| Computer Vision (CV) | Image Super-Resolution |[esr-ea](https://gitee.com/mindspore/models/tree/master/research/cv/esr_ea) | ✅ | | | | Computer Vision (CV) | Image Super-Resolution |[ESRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/ESRGAN) | ✅ | | | | Computer Vision (CV) | Image Super-Resolution |[IRN](https://gitee.com/mindspore/models/tree/master/research/cv/IRN) | ✅ | | | | Computer Vision (CV) | Image Super-Resolution |[RCAN](https://gitee.com/mindspore/models/tree/master/research/cv/RCAN) | ✅ | | | -| Computer Vision (CV) | Image Super-Resolution |[RDN](https://gitee.com/mindspore/models/tree/master/research/cv/RDN) | ✅ | | | -| Computer Vision (CV) | Image Super-Resolution |[sr-ea](https://gitee.com/mindspore/models/tree/master/research/cv/sr-ea) | ✅ | | | +| Computer Vision (CV) | Image Super-Resolution |[sr-ea](https://gitee.com/mindspore/models/tree/master/research/cv/sr_ea) | ✅ | | | | Computer Vision (CV) | Image Super-Resolution |[SRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SRGAN) | ✅ | | | | Computer Vision (CV) | Image Super-Resolution |[wdsr](https://gitee.com/mindspore/models/tree/master/research/cv/wdsr) | ✅ | | | | Computer Vision (CV) | Image Denoising |[Neighbor2Neighbor](https://gitee.com/mindspore/models/tree/master/research/cv/Neighbor2Neighbor) | ✅ | | | @@ -290,20 +291,18 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | Computer Vision (CV) | Pose Estimation | [AlphaPose](https://gitee.com/mindspore/models/tree/master/research/cv/AlphaPose) | ✅ | | | | Computer Vision (CV) | Pose Estimation | [Hourglass](https://gitee.com/mindspore/models/tree/master/research/cv/StackedHourglass) | ✅ | | | | Computer Vision (CV) | Pose Estimation | [Simple Baseline](https://gitee.com/mindspore/models/tree/master/research/cv/simple_baselines) | ✅ | | | -| Computer Vision (CV) | 6DoF Pose Estimation | [PVNet](https://gitee.com/mindspore/models/tree/master/research/cv/pvnet) | ✅ | | | | Computer Vision (CV) | Image Retrieval |[Delf](https://gitee.com/mindspore/models/tree/master/research/cv/delf) | ✅ | | | | Natural Language Processing (NLP) | Word Embedding | [Word2Vec Skip-Gram](https://gitee.com/mindspore/models/tree/master/research/nlp/skipgram) | ✅ | | | | Natural Language Processing (NLP) | Dialogue Generation | [DAM](https://gitee.com/mindspore/models/tree/master/research/nlp/dam) | ✅ | | | | Natural Language Processing (NLP) | Machine Translation | [Seq2Seq](https://gitee.com/mindspore/models/tree/master/research/nlp/seq2seq) | ✅ | | | | Natural Language Processing (NLP) | Emotion Classification | [Senta](https://gitee.com/mindspore/models/tree/master/research/nlp/senta) | ✅ | | | | Natural Language Processing (NLP) | Emotion Classification | [Attention LSTM](https://gitee.com/mindspore/models/tree/master/research/nlp/atae_lstm) | ✅ | | | -| Natural Language Processing (NLP) | Named Entity Recognition | [LSTM_CRF](https://gitee.com/mindspore/models/tree/master/research/nlp/lstm) | ✅ | | | +| Natural Language Processing (NLP) | Named Entity Recognition | [LSTM_CRF](https://gitee.com/mindspore/models/tree/master/research/nlp/lstm_crf) | ✅ | | | | Natural Language Processing (NLP) | Text Classification | [HyperText](https://gitee.com/mindspore/models/tree/master/research/nlp/hypertext) | ✅ | | | | Natural Language Processing (NLP) | Text Classification | [TextRCNN](https://gitee.com/mindspore/models/tree/master/research/nlp/textrcnn) | ✅ | | | | Natural Language Processing (NLP) | Natural Language Understanding | [ALBert](https://gitee.com/mindspore/models/tree/master/research/nlp/albert) | ✅ | | | | Natural Language Processing (NLP) | Natural Language Understanding | [KT-Net](https://gitee.com/mindspore/models/tree/master/research/nlp/ktnet) | ✅ | | | | Natural Language Processing (NLP) | Natural Language Understanding | [LUKE](https://gitee.com/mindspore/models/tree/master/research/nlp/luke) | ✅ | | | -| Natural Language Processing (NLP) | Natural Language Understanding | [DS-CNN](https://gitee.com/mindspore/models/tree/master/research/nlp/dscnn) | ✅ | | | | Natural Language Processing (NLP) | Natural Language Understanding | [TPRR](https://gitee.com/mindspore/models/tree/master/research/nlp/tprr) | ✅ | | | | Natural Language Processing (NLP) | Knowledge Graph Embedding | [RotatE](https://gitee.com/mindspore/models/tree/master/research/nlp/rotate) | ✅ | | | | Recommender | Recommender System, CTR prediction | [AutoDis](https://gitee.com/mindspore/models/tree/master/research/recommend/autodis) | ✅ | | | @@ -316,7 +315,7 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | Audio | Keyword Spotting | [DS-CNN](https://gitee.com/mindspore/models/tree/master/research/audio/dscnn) | ✅ | | | | Audio | Speech Recognition | [CTCModel](https://gitee.com/mindspore/models/tree/master/research/audio/ctcmodel) | ✅ | | | | Audio | Speech Synthesis | [Wavenet](https://gitee.com/mindspore/models/tree/master/research/audio/wavenet) | ✅ | | | -| GNN | Traffic Prediction | [STGCN](https://gitee.com/mindspore/models/tree/master/research/cv/STGCN) | ✅ | | | +| GNN | Traffic Prediction | [STGCN](https://gitee.com/mindspore/models/tree/master/research/cv/stgcn) | ✅ | | | | GNN | Traffic Prediction | [TGCN](https://gitee.com/mindspore/models/tree/master/research/cv/tgcn) | ✅ | | | | GNN | Social and Information Networks | [SGCN](https://gitee.com/mindspore/models/tree/master/research/gnn/sgcn) | ✅ | | | | GNN | Graph Classification | [DGCN](https://gitee.com/mindspore/models/tree/master/research/gnn/dgcn) | ✅ | | | diff --git a/README_CN.md b/README_CN.md index 88eae6866cd105a05841ee39e02525610c42c164..1c3a831abebb2f6ffaf98208330589dc5f28240a 100644 --- a/README_CN.md +++ b/README_CN.md @@ -48,7 +48,7 @@ |计算机视觉（CV） | 图像分类（Image Classification） | [ResNeXt50](https://gitee.com/mindspore/models/tree/master/official/cv/resnext) | ✅ | ✅ | | |计算机视觉（CV） | 图像分类（Image Classification） | [ResNeXt101](https://gitee.com/mindspore/models/tree/master/official/cv/resnext) | ✅ | | | |计算机视觉（CV） | 图像分类（Image Classification） | [SE-ResNet50](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | ✅ | | | -|计算机视觉（CV） | 图像分类（Image Classification） | [SE-ResNext50](https://gitee.com/mindspore/models/tree/master/official/cv/SE_ResNeXt50) | ✅ | | | +|计算机视觉（CV） | 图像分类（Image Classification） | [SE-ResNext50](https://gitee.com/mindspore/models/tree/master/official/cv/se_resnext50) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） | [ShuffleNetV1](https://gitee.com/mindspore/models/tree/master/official/cv/shufflenetv1) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） | [ShuffleNetV2](https://gitee.com/mindspore/models/tree/master/official/cv/shufflenetv2) | | ✅ | | | 计算机视觉（CV） | 图像分类（Image Classification） |[SqueezeNet](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) | ✅ | | | @@ -83,8 +83,9 @@ | 计算机视觉（CV） | 语义分割（Semantic Segmentation） | [U-Net2D (Medical)](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | ✅ | | | | 计算机视觉（CV） | 语义分割（Semantic Segmentation） | [U-Net3D (Medical)](https://gitee.com/mindspore/models/tree/master/official/cv/unet3d) | ✅ | | | | 计算机视觉（CV） | 语义分割（Semantic Segmentation） | [U-Net++](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | ✅ | | | -| 计算机视觉（CV） | 语义分割（Semantic Segmentation） | [Fast-SCNN](https://gitee.com/mindspore/models/tree/master/official/cv/fasterscnn) | ✅ | | | +| 计算机视觉（CV） | 语义分割（Semantic Segmentation） | [Fast-SCNN](https://gitee.com/mindspore/models/tree/master/official/cv/fastscnn) | ✅ | | | | 计算机视觉（CV） | 语义分割（Semantic Segmentation） | [FCN8s](https://gitee.com/mindspore/models/tree/master/official/cv/FCN8s) | ✅ | | | +| 计算机视觉（CV） | 姿态检测（6DoF Pose Estimation） | [PVNet](https://gitee.com/mindspore/models/tree/master/official/cv/pvnet) | ✅ | | | | 计算机视觉（CV） | 关键点检测（Keypoint Detection） |[OpenPose](https://gitee.com/mindspore/models/tree/master/official/cv/openpose) | ✅ | | | | 计算机视觉（CV） | 关键点检测（Keypoint Detection） |[SimplePoseNet](https://gitee.com/mindspore/models/tree/master/official/cv/simple_pose) | ✅ | | | | 计算机视觉（CV） | 文本检测（Scene Text Detection） | [East](https://gitee.com/mindspore/models/tree/master/official/cv/east) | ✅ | | | @@ -93,6 +94,7 @@ | 计算机视觉（CV） | 文本识别（Scene Text Recognition） |[CNN+CTC](https://gitee.com/mindspore/models/tree/master/official/cv/cnnctc) | ✅ | | | | 计算机视觉（CV） | 文本识别（Scene Text Recognition） |[CRNN-Seq2Seq-OCR](https://gitee.com/mindspore/models/tree/master/official/cv/crnn_seq2seq_ocr) | ✅ | | | | 计算机视觉（CV） | 文本识别（Scene Text Recognition） |[WarpCTC](https://gitee.com/mindspore/models/tree/master/official/cv/warpctc) | ✅ | | | +| 计算机视觉（CV） | 缺陷检测（Defect Detection） |[PatchCore](https://gitee.com/mindspore/models/tree/master/official/cv/patchcore) | ✅ | | | | 计算机视觉（CV） | 缺陷检测（Defect Detection） |[ssim-ae](https://gitee.com/mindspore/models/tree/master/official/cv/ssim-ae) | ✅ | | | | 计算机视觉（CV） | 人脸检测（Face Detection） | [RetinaFace-ResNet50](https://gitee.com/mindspore/models/tree/master/official/cv/retinaface_resnet50) | ✅ | ✅ | | | 计算机视觉（CV） | 人脸检测（Face Detection） | [CenterFace](https://gitee.com/mindspore/models/tree/master/official/cv/centerface) | ✅ | | | @@ -102,6 +104,7 @@ | 计算机视觉（CV） | 相机重定位（Camera Relocalization） | [PoseNet](https://gitee.com/mindspore/models/tree/master/official/cv/posenet) | ✅ | | | | 计算机视觉（CV） | 图像抠图（Image Matting） | [Semantic Human Matting](https://gitee.com/mindspore/models/tree/master/official/cv/semantic_human_matting) | ✅ | | | | 计算机视觉（CV） | 视频分类（Video Classification） | [C3D](https://gitee.com/mindspore/models/tree/master/official/cv/c3d) | ✅ | | | +| 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[RDN](https://gitee.com/mindspore/models/tree/master/official/cv/RDN) | ✅ | ✅ | | | 计算机视觉（CV） | 图像超分（Image Super-Resolution） | [SRCNN](https://gitee.com/mindspore/models/tree/master/official/cv/srcnn) | ✅ | | | | 计算机视觉（CV） | 图像去噪（Image Denoising） | [BRDNet](https://gitee.com/mindspore/models/tree/master/official/cv/brdnet) | ✅ | | | | 计算机视觉（CV） | 图像去噪（Image Denoising） | [DnCNN](https://gitee.com/mindspore/models/tree/master/official/cv/dncnn) | ✅ | | | @@ -138,12 +141,12 @@ | 计算机视觉（CV） | 图像分类（Image Classification） |[3D Densenet](https://gitee.com/mindspore/models/tree/master/research/cv/3D_DenseNet) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[Auto Augment](https://gitee.com/mindspore/models/tree/master/research/cv/autoaugment) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[AVA](https://gitee.com/mindspore/models/tree/master/research/cv/AVA_cifar) | ✅ | | | -| 计算机视觉（CV） | 图像分类（Image Classification） |[CCT](https://gitee.com/mindspore/models/tree/master/research/cv/CCT) | ✅ | | | +| 计算机视觉（CV） | 图像分类（Image Classification） |[CCT](https://gitee.com/mindspore/models/tree/master/research/cv/cct) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[dnet-nas](https://gitee.com/mindspore/models/tree/master/research/cv/dnet_nas) | ✅ | | | -| 计算机视觉（CV） | 图像分类（Image Classification） |[Efficientnet-b0](https://gitee.com/mindspore/models/tree/master/research/cv/efficient-b0) | ✅ | | | -| 计算机视觉（CV） | 图像分类（Image Classification） |[Efficientnet-b1](https://gitee.com/mindspore/models/tree/master/research/cv/efficient-b1) | ✅ | | | -| 计算机视觉（CV） | 图像分类（Image Classification） |[Efficientnet-b2](https://gitee.com/mindspore/models/tree/master/research/cv/efficient-b2) | ✅ | | | -| 计算机视觉（CV） | 图像分类（Image Classification） |[Efficientnet-b3](https://gitee.com/mindspore/models/tree/master/research/cv/efficient-b3) | ✅ | | | +| 计算机视觉（CV） | 图像分类（Image Classification） |[Efficientnet-b0](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b0) | ✅ | | | +| 计算机视觉（CV） | 图像分类（Image Classification） |[Efficientnet-b1](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b1) | ✅ | | | +| 计算机视觉（CV） | 图像分类（Image Classification） |[Efficientnet-b2](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b2) | ✅ | | | +| 计算机视觉（CV） | 图像分类（Image Classification） |[Efficientnet-b3](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b3) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[FDA-BNN](https://gitee.com/mindspore/models/tree/master/research/cv/FDA-BNN) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[fishnet99](https://gitee.com/mindspore/models/tree/master/research/cv/fishnet99) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[GENET](https://gitee.com/mindspore/models/tree/master/research/cv/GENet_Res50) | ✅ | | | @@ -159,10 +162,10 @@ | 计算机视觉（CV） | 图像分类（Image Classification） |[META-Baseline](https://gitee.com/mindspore/models/tree/master/research/cv/meta-baseline) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[MNasNet](https://gitee.com/mindspore/models/tree/master/research/cv/mnasnet) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[MobilenetV3-Large](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetv3_large) | ✅ | | | -| 计算机视觉（CV） | 图像分类（Image Classification） |[MobilenetV3-Small](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetv3_small_x1_0) | ✅ | | | +| 计算机视觉（CV） | 图像分类（Image Classification） |[MobilenetV3-Small](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetV3_small_x1_0) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[NFNet-F0](https://gitee.com/mindspore/models/tree/master/research/cv/NFNet) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[ntsnet](https://gitee.com/mindspore/models/tree/master/research/cv/ntsnet) | ✅ | | | -| 计算机视觉（CV） | 图像分类（Image Classification） |[Pdarts](https://gitee.com/mindspore/models/tree/master/research/cv/Pdarts) | ✅ | | | +| 计算机视觉（CV） | 图像分类（Image Classification） |[Pdarts](https://gitee.com/mindspore/models/tree/master/research/cv/PDarts) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[PNASNet-5](https://gitee.com/mindspore/models/tree/master/research/cv/pnasnet) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[ProtoNet](https://gitee.com/mindspore/models/tree/master/research/cv/ProtoNet) | ✅ | | | | 计算机视觉（CV） | 图像分类（Image Classification） |[Proxylessnas](https://gitee.com/mindspore/models/tree/master/research/cv/proxylessnas) | ✅ | | | @@ -205,7 +208,7 @@ | 计算机视觉（CV） | 人脸识别（Face Recognition） | [LightCNN](https://gitee.com/mindspore/models/tree/master/research/cv/LightCNN) | ✅ | | | | 计算机视觉（CV） | 目标检测（Object Detection） | [Spnas](https://gitee.com/mindspore/models/tree/master/research/cv/Spnas) | ✅ | | | | 计算机视觉（CV） | 目标检测（Object Detection） | [SSD-GhostNet](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_ghostnet) | ✅ | | | -| 计算机视觉（CV） | 目标检测（Object Detection） | [EGNet](https://gitee.com/mindspore/models/tree/master/research/cv/EGNet) | ✅ | | | +| 计算机视觉（CV） | 目标检测（Object Detection） | [EGNet](https://gitee.com/mindspore/models/tree/master/research/cv/EGnet) | ✅ | | | | 计算机视觉（CV） | 目标检测（Object Detection） | [FasterRCNN-FPN-DCN](https://gitee.com/mindspore/models/tree/master/research/cv/faster_rcnn_dcn) | ✅ | | | | 计算机视觉（CV） | 目标检测（Object Detection） | [NAS-FPN](https://gitee.com/mindspore/models/tree/master/research/cv/nas-fpn) | ✅ | | | | 计算机视觉（CV） | 目标检测（Object Detection） | [RAS](https://gitee.com/mindspore/models/tree/master/research/cv/ras) | ✅ | | | @@ -223,9 +226,8 @@ | 计算机视觉（CV） | 目标检测（Object Detection） | [U-2-Net](https://gitee.com/mindspore/models/tree/master/research/cv/u2net) | ✅ | | | | 计算机视觉（CV） | 目标检测（Object Detection） | [YOLOV3-tiny](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_tiny) | ✅ | | | | 计算机视觉（CV） | 目标跟踪（Object Tracking） |[SiamFC](https://gitee.com/mindspore/models/tree/master/research/cv/SiamFC) | ✅ | | | -| 计算机视觉（CV） | 目标跟踪（Object Tracking） |[SiamRPN](https://gitee.com/mindspore/models/tree/master/research/cv/SiamRPN) | ✅ | | | +| 计算机视觉（CV） | 目标跟踪（Object Tracking） |[SiamRPN](https://gitee.com/mindspore/models/tree/master/research/cv/siamRPN) | ✅ | | | | 计算机视觉（CV） | 目标跟踪（Object Tracking） |[FairMOT](https://gitee.com/mindspore/models/tree/master/research/cv/fairmot) | ✅ | | | -| 计算机视觉（CV） | 缺陷检测（Defect Detection） |[PathCore](https://gitee.com/mindspore/models/tree/master/research/cv/PathCore) | ✅ | | | | 计算机视觉（CV） | 关键点检测（Key Point Detection） | [CenterNet](https://gitee.com/mindspore/models/tree/master/research/cv/centernet) | ✅ | | ✅ | | 计算机视觉（CV） | 关键点检测（Key Point Detection） | [CenterNet-hourglass](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_det) | ✅ | | | | 计算机视觉（CV） | 关键点检测（Key Point Detection） | [CenterNet-resnet101](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet101) | ✅ | | | @@ -253,12 +255,11 @@ | 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[CSD](https://gitee.com/mindspore/models/tree/master/research/cv/csd) | ✅ | | | | 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[DBPN](https://gitee.com/mindspore/models/tree/master/research/cv/DBPN) | ✅ | | | | 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[EDSR](https://gitee.com/mindspore/models/tree/master/research/cv/EDSR) | ✅ | | | -| 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[esr-ea](https://gitee.com/mindspore/models/tree/master/research/cv/esr-ea) | ✅ | | | +| 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[esr-ea](https://gitee.com/mindspore/models/tree/master/research/cv/esr_ea) | ✅ | | | | 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[ESRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/ESRGAN) | ✅ | | | | 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[IRN](https://gitee.com/mindspore/models/tree/master/research/cv/IRN) | ✅ | | | | 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[RCAN](https://gitee.com/mindspore/models/tree/master/research/cv/RCAN) | ✅ | | | -| 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[RDN](https://gitee.com/mindspore/models/tree/master/research/cv/RDN) | ✅ | | | -| 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[sr-ea](https://gitee.com/mindspore/models/tree/master/research/cv/sr-ea) | ✅ | | | +| 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[sr-ea](https://gitee.com/mindspore/models/tree/master/research/cv/sr_ea) | ✅ | | | | 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[SRGAN](https://gitee.com/mindspore/models/tree/master/research/cv/SRGAN) | ✅ | | | | 计算机视觉（CV） | 图像超分（Image Super-Resolution） |[wdsr](https://gitee.com/mindspore/models/tree/master/research/cv/wdsr) | ✅ | | | | 计算机视觉（CV） | 图像去噪（Image Denoising） |[Neighbor2Neighbor](https://gitee.com/mindspore/models/tree/master/research/cv/Neighbor2Neighbor) | ✅ | | | @@ -291,20 +292,18 @@ | 计算机视觉（CV） | 姿态估计（Pose Estimation） | [AlphaPose](https://gitee.com/mindspore/models/tree/master/research/cv/AlphaPose) | ✅ | | | | 计算机视觉（CV） | 姿态估计（Pose Estimation） | [Hourglass](https://gitee.com/mindspore/models/tree/master/research/cv/StackedHourglass) | ✅ | | | | 计算机视觉（CV） | 姿态估计（Pose Estimation） | [Simple Baseline](https://gitee.com/mindspore/models/tree/master/research/cv/simple_baselines) | ✅ | | | -| 计算机视觉（CV） | 姿态检测（6DoF Pose Estimation） | [PVNet](https://gitee.com/mindspore/models/tree/master/research/cv/pvnet) | ✅ | | | | 计算机视觉（CV） | 图像检索（Image Retrieval） |[Delf](https://gitee.com/mindspore/models/tree/master/research/cv/delf) | ✅ | | | | 自然语言处理（NLP） | 词嵌入（Word Embedding） | [Word2Vec Skip-Gram](https://gitee.com/mindspore/models/tree/master/research/nlp/skipgram) | ✅ | | | | 自然语言处理（NLP） | 对话系统（Dialogue Generation) | [DAM](https://gitee.com/mindspore/models/tree/master/research/nlp/dam) | ✅ | | | | 自然语言处理（NLP） | 机器翻译（Machine Translation) | [Seq2Seq](https://gitee.com/mindspore/models/tree/master/research/nlp/seq2seq) | ✅ | | | | 自然语言处理（NLP） | 情感分析（Emotion Classification) | [Senta](https://gitee.com/mindspore/models/tree/master/research/nlp/senta) | ✅ | | | | 自然语言处理（NLP） | 情感分析（Emotion Classification) | [Attention LSTM](https://gitee.com/mindspore/models/tree/master/research/nlp/atae_lstm) | ✅ | | | -| 自然语言处理（NLP） | 命名实体识别（Named Entity Recognition) | [LSTM_CRF](https://gitee.com/mindspore/models/tree/master/research/nlp/lstm) | ✅ | | | +| 自然语言处理（NLP） | 命名实体识别（Named Entity Recognition) | [LSTM_CRF](https://gitee.com/mindspore/models/tree/master/research/nlp/lstm_crf) | ✅ | | | | 自然语言处理（NLP） | 文本分类（Text Classification) | [HyperText](https://gitee.com/mindspore/models/tree/master/research/nlp/hypertext) | ✅ | | | | 自然语言处理（NLP） | 文本分类（Text Classification) | [TextRCNN](https://gitee.com/mindspore/models/tree/master/research/nlp/textrcnn) | ✅ | | | | 自然语言处理（NLP） | 自然语言理解（Natural Language Understanding） | [ALBert](https://gitee.com/mindspore/models/tree/master/research/nlp/albert) | ✅ | | | | 自然语言处理（NLP） | 自然语言理解（Natural Language Understanding） | [KT-Net](https://gitee.com/mindspore/models/tree/master/research/nlp/ktnet) | ✅ | | | | 自然语言处理（NLP） | 自然语言理解（Natural Language Understanding） | [LUKE](https://gitee.com/mindspore/models/tree/master/research/nlp/luke) | ✅ | | | -| 自然语言处理（NLP） | 自然语言理解（Natural Language Understanding） | [DS-CNN](https://gitee.com/mindspore/models/tree/master/research/nlp/dscnn) | ✅ | | | | 自然语言处理（NLP） | 自然语言理解（Natural Language Understanding） | [TextRCNN](https://gitee.com/mindspore/models/tree/master/research/nlp/textrcnn) | ✅ | | | | 自然语言处理（NLP） | 自然语言理解（Natural Language Understanding） | [TPRR](https://gitee.com/mindspore/models/tree/master/research/nlp/tprr) | ✅ | | | | 自然语言处理（NLP） | 知识图谱嵌入（Knowledge Graph Embedding） | [RotatE](https://gitee.com/mindspore/models/tree/master/research/nlp/rotate) | ✅ | | | @@ -318,7 +317,7 @@ |语音（Audio） | 关键词识别（Keyword Spotting） | [DS-CNN](https://gitee.com/mindspore/models/tree/master/research/audio/dscnn) | ✅ | | | |语音（Audio） | 语音识别（Speech Recognition） | [CTCModel](https://gitee.com/mindspore/models/tree/master/research/audio/ctcmodel) | ✅ | | | |语音（Audio） | 语音合成（Speech Synthesis） | [Wavenet](https://gitee.com/mindspore/models/tree/master/research/audio/wavenet) | ✅ | | | -| 图神经网络（GNN） | 交通预测（Traffic Prediction) | [STGCN](https://gitee.com/mindspore/models/tree/master/research/cv/STGCN) | ✅ | | | +| 图神经网络（GNN） | 交通预测（Traffic Prediction) | [STGCN](https://gitee.com/mindspore/models/tree/master/research/cv/stgcn) | ✅ | | | | 图神经网络（GNN） | 交通预测（Traffic Prediction) | [TGCN](https://gitee.com/mindspore/models/tree/master/research/cv/tgcn) | ✅ | | | | 图神经网络（GNN） | 社交信息网络（Social and Information Networks） | [SGCN](https://gitee.com/mindspore/models/tree/master/research/gnn/sgcn) | ✅ | | | | 图神经网络（GNN） | 图结构数据分类（Graph Classification） | [DGCN](https://gitee.com/mindspore/models/tree/master/research/gnn/dgcn) | ✅ | | | diff --git a/research/cv/csd/README.md b/research/cv/csd/README.md index 223e61f18e71fc93b85ccb7599710036ff408f93..eb6a9f8e72a3d810058ae5d5bc196093a6d90fd3 100644 --- a/research/cv/csd/README.md +++ b/research/cv/csd/README.md @@ -133,8 +133,8 @@ Major parameters in scripts as follows: ### Train CSD -[VGG19](https://gitee.com/mindspore/models/tree/ea6f2efda78921d02b4f4d8d40b6b329bfce08f3/research/cv/vgg19) pre-trained on ImageNet is used in our contrastive loss. -You could download the pre-trained model from [https://download.mindspore.cn/model_zoo/](https://download.mindspore.cn/model_zoo/) or train according to [VGG19](https://gitee.com/mindspore/models/tree/ea6f2efda78921d02b4f4d8d40b6b329bfce08f3/research/cv/vgg19) and place it in `./` . +[VGG19](https://gitee.com/mindspore/models/tree/master/research/cv/vgg19) pre-trained on ImageNet is used in our contrastive loss. +You could download the pre-trained model from [https://download.mindspore.cn/model_zoo/](https://download.mindspore.cn/model_zoo/) or train according to [VGG19](https://gitee.com/mindspore/models/tree/master/research/cv/vgg19) and place it in `./` . You should specify the VGG ckpt file in `[VGG_MODEL]`. Since we use the outputs of teacher model as the positive samples, it is necessary to pre-train the teacher model.