From ea8443351bab37f0df60dbe3292814e70e9ab827 Mon Sep 17 00:00:00 2001 From: wwfu Date: Sun, 14 Jan 2024 12:02:08 +0800 Subject: [PATCH] =?UTF-8?q?=E6=8E=A8=E7=90=86=E7=8E=AF=E5=A2=83=E4=B8=8E?= =?UTF-8?q?=E5=85=AC=E7=BD=91=E5=9C=B0=E5=9D=80=E6=95=B4=E6=94=B9?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../classfication/Wide_ResNet101_2/README.md | 35 +------------------ .../Wide_ResNet50_2_for_Pytorch/README.md | 35 +------------------ .../volo/public_address_statement.md | 5 +++ .../contrib/cv/classfication/volo/readme.md | 19 +--------- .../cv/classfication/vovnet39/README.md | 15 +------- .../cv/classfication/xception/README.md | 14 -------- .../contrib/cv/classfication/xcit/README.md | 22 +----------- .../contrib/cv/detection/3DUnet/README.md | 2 -- .../cv/detection/AdvancedEAST/README.md | 18 ---------- .../contrib/cv/detection/AlphaPose/README.md | 16 --------- .../contrib/cv/detection/BSN/README.md | 20 ----------- .../contrib/cv/detection/CTPN/README.md | 19 ---------- .../Cascade-RCNN-Resnet101-FPN-DCN/README.md | 21 +---------- .../Cascade-RCNN-Resnet50-FPN/README.md | 21 +---------- .../detection/Cascade_RCNN_R101_FPN/README.md | 20 +---------- .../contrib/cv/detection/CenterFace/README.md | 15 -------- .../contrib/cv/detection/CenterNet/README.md | 16 --------- .../DSFD/public_address_statement.md | 6 ++++ .../contrib/cv/detection/Deepspeech/README.md | 2 -- .../contrib/cv/detection/Detr/README.md | 15 -------- .../Detr/public_address_statement.md | 3 ++ .../cv/detection/EAST_MobileNetV3/README.md | 16 --------- .../cv/detection/EAST_ResNet50_vd/README.md | 18 +--------- .../cv/detection/EfficientDetD0/README.md | 24 +------------ .../public_address_statement.md | 28 +++++++++++++++ .../cv/detection/EfficientDetD7/README.md | 16 --------- .../FCENet/public_address_statement.md | 1 - .../contrib/cv/detection/FCENet/readme.md | 14 -------- .../contrib/cv/detection/FairMOT/README.md | 22 +----------- .../Faster_R-CNN_DCN_Res101/readme.md | 21 ----------- .../Faster_R-CNN_DCN_Res50/README.md | 18 ---------- .../detection/Faster_R-CNN_ResNet50/README.md | 18 +--------- .../cv/detection/ch_PP-OCRv2_det/README.md | 17 --------- .../cv/detection/ch_PP-OCRv3_det/README.md | 15 -------- .../ch_ppocr_server_v2.0_det/README.md | 16 --------- .../cv/detection/en_PP-OCRv3_det/README.md | 17 --------- 36 files changed, 54 insertions(+), 546 deletions(-) create mode 100644 ACL_PyTorch/contrib/cv/classfication/volo/public_address_statement.md create mode 100644 ACL_PyTorch/contrib/cv/detection/DSFD/public_address_statement.md create mode 100644 ACL_PyTorch/contrib/cv/detection/Detr/public_address_statement.md create mode 100644 ACL_PyTorch/contrib/cv/detection/EfficientDetD0/public_address_statement.md diff --git a/ACL_PyTorch/contrib/cv/classfication/Wide_ResNet101_2/README.md b/ACL_PyTorch/contrib/cv/classfication/Wide_ResNet101_2/README.md index d5f9345d1a..8cf0f797cd 100644 --- a/ACL_PyTorch/contrib/cv/classfication/Wide_ResNet101_2/README.md +++ b/ACL_PyTorch/contrib/cv/classfication/Wide_ResNet101_2/README.md @@ -5,10 +5,6 @@ - [输入输出数据](#section540883920406) - - -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -17,7 +13,7 @@ - [模型推理性能&精度](#ZH-CN_TOPIC_0000001172201573) - ****** +****** @@ -50,35 +46,6 @@ | output1 | FLOAT32 | 1 x 1000 | ND | -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | - | 固件与驱动 | 1.0.17 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - | PyTorch | 1.8.1 | - | - | 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - -- 该模型需要以下依赖 - - **表 2** 依赖列表 - - | 依赖名称 | 版本 | - | ------------- | -------- | - | onnx | 1.7.0 | - | Torch | 1.8.1 | - | TorchVision | 0.9.1 | - | numpy | 1.18.5 | - | Pillow | 7.2.0 | - | opencv-python | 4.2.0.34 | - - - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/classfication/Wide_ResNet50_2_for_Pytorch/README.md b/ACL_PyTorch/contrib/cv/classfication/Wide_ResNet50_2_for_Pytorch/README.md index 38fc2752d7..ab14e9244b 100644 --- a/ACL_PyTorch/contrib/cv/classfication/Wide_ResNet50_2_for_Pytorch/README.md +++ b/ACL_PyTorch/contrib/cv/classfication/Wide_ResNet50_2_for_Pytorch/README.md @@ -5,10 +5,6 @@ - [输入输出数据](#section540883920406) - - -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -17,7 +13,7 @@ - [模型推理性能&精度](#ZH-CN_TOPIC_0000001172201573) - ****** +****** @@ -52,35 +48,6 @@ | output1 | FLOAT32 | 1 x 1000 | NCHW | -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | - | 固件与驱动 | 1.0.17 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - | PyTorch | 1.8.1 | - | - | 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - -- 该模型需要以下依赖 - - **表 2** 依赖列表 - - | 依赖名称 | 版本 | - | ------------- | -------- | - | onnx | 1.7.0 | - | Torch | 1.8.1 | - | TorchVision | 0.9.1 | - | numpy | 1.18.5 | - | Pillow | 7.2.0 | - | opencv-python | 4.2.0.34 | - - - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/classfication/volo/public_address_statement.md b/ACL_PyTorch/contrib/cv/classfication/volo/public_address_statement.md new file mode 100644 index 0000000000..473ec01571 --- /dev/null +++ b/ACL_PyTorch/contrib/cv/classfication/volo/public_address_statement.md @@ -0,0 +1,5 @@ +| 类型 | 开源代码地址 | 文件名 | 公网IP地址/公网URL地址/域名/邮箱地 | 用途说明 | +| ---- | ----------- | ----- | -------------------------------- | --------| +| 开源代码引入 | https://github.com/sail-sg/volo/blob/main/models/volo.py | ACL_PyTorch/contrib/cv/classfication/volo/volo.py | https://github.com/zihangJiang/TokenLabeling | 函数用途说明 | +| 开源代码引入 | https://github.com/sail-sg/volo/blob/main/models/volo.py | ACL_PyTorch/contrib/cv/classfication/volo/volo.py | https://github.com/zihangJiang/TokenLabeling | 参数说明 | +| 开源代码引入 | https://github.com/sail-sg/volo/blob/main/models/volo.py | ACL_PyTorch/contrib/cv/classfication/volo/volo.py | https://github.com/zihangJiang/TokenLabeling | 参数说明 | \ No newline at end of file diff --git a/ACL_PyTorch/contrib/cv/classfication/volo/readme.md b/ACL_PyTorch/contrib/cv/classfication/volo/readme.md index cb8a89e35a..2734ec3ce0 100644 --- a/ACL_PyTorch/contrib/cv/classfication/volo/readme.md +++ b/ACL_PyTorch/contrib/cv/classfication/volo/readme.md @@ -1,7 +1,6 @@ # VOLO Onnx模型端到端推理指导 - [概述](#概述) - [输入输出数据](#输入输出数据) -- [推理环境准备](#推理环境准备) - [快速上手](#快速上手) @@ -11,7 +10,7 @@ - [模型推理性能](#模型推理性能) - ****** +****** @@ -46,22 +45,6 @@ VOLO采用两阶段架构设计，同时考虑了更具细粒度的token表示 | output | batchsize x 1000 | FLOAT32 | ND | -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - -| 配套 | 版本 | 环境准备指导 | -| ------------------------------------------------------------ |---------| ------------------------------------------------------------ | -| 固件与驱动 | 22.0.2 | [Pytorch框架推理环境准备](https://gitee.com/link?target=https%3A%2F%2Fwww.hiascend.com%2Fdocument%2Fdetail%2Fzh%2FModelZoo%2Fpytorchframework%2Fpies) | -| CANN | 6.0.RC1 | - | -| Python | 3.7.5 | - | -| PyTorch | 1.10.0 | - | -| 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | | | - - - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/classfication/vovnet39/README.md b/ACL_PyTorch/contrib/cv/classfication/vovnet39/README.md index 31d2c1f7b0..864252d2c8 100644 --- a/ACL_PyTorch/contrib/cv/classfication/vovnet39/README.md +++ b/ACL_PyTorch/contrib/cv/classfication/vovnet39/README.md @@ -5,8 +5,6 @@ - [输入输出数据](#section540883920406) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -15,7 +13,7 @@ - [模型推理性能&精度](#ZH-CN_TOPIC_0000001172201573) - ****** +****** # 概述 @@ -44,17 +42,6 @@ | -------- | -------- | -------- | ------------ | | output | FLOAT32 | 1 x 1000 | ND | -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ---------- | ------- | ----------------------------------------------------------------------------------------------------- | - | 固件与驱动 | 22.0.2 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 5.1.RC2 | - | - | Python | 3.7.5 | - | # 快速上手 diff --git a/ACL_PyTorch/contrib/cv/classfication/xception/README.md b/ACL_PyTorch/contrib/cv/classfication/xception/README.md index e89b8ff535..d5269882b6 100644 --- a/ACL_PyTorch/contrib/cv/classfication/xception/README.md +++ b/ACL_PyTorch/contrib/cv/classfication/xception/README.md @@ -2,7 +2,6 @@ - [概述](#概述) - [输入输出数据](#输入输出数据) -- [推理环境](#推理环境) - [快速上手](#快速上手) - [获取源码](#获取源码) - [准备数据集](#准备数据集) @@ -35,20 +34,7 @@ Xception是Google公司继Inception后提出的对 Inception-v3 的另一种改 ---- -# 推理环境 -- 该模型推理所需配套的软件如下： - - | 配套 | 版本 | 环境准备指导 | - | --------- | ------- | ---------- | - | 固件与驱动 | 1.0.17 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - - 说明：请根据推理卡型号与 CANN 版本选择相匹配的固件与驱动版本。 - - ----- # 快速上手 ## 安装 diff --git a/ACL_PyTorch/contrib/cv/classfication/xcit/README.md b/ACL_PyTorch/contrib/cv/classfication/xcit/README.md index 3df1f5a347..04b697a18f 100644 --- a/ACL_PyTorch/contrib/cv/classfication/xcit/README.md +++ b/ACL_PyTorch/contrib/cv/classfication/xcit/README.md @@ -3,8 +3,6 @@ - [概述](#ZH-CN_TOPIC_0000001172161501) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -13,9 +11,7 @@ - [模型推理性能](#ZH-CN_TOPIC_0000001172201573) -- [配套环境](#ZH-CN_TOPIC_0000001126121892) - - ****** +****** # 概述 @@ -57,22 +53,6 @@ Xcit是针对于图片处理设计的基于Transformer架构的神经网络。 | output1 | batchsize x 1000 | FLOAT32 | ND | - - -# 推理环境准备\[所有版本\] - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - -| 配套 | 版本 | 环境准备指导 | -| ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | -| 固件与驱动 | 1.0.15 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | -| CANN | 5.1.RC1 | - | -| Python | 3.7.5 | - | -| PyTorch | 1.8.0 | - | -| 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - # 快速上手 diff --git a/ACL_PyTorch/contrib/cv/detection/3DUnet/README.md b/ACL_PyTorch/contrib/cv/detection/3DUnet/README.md index c14869723a..284a3450fd 100644 --- a/ACL_PyTorch/contrib/cv/detection/3DUnet/README.md +++ b/ACL_PyTorch/contrib/cv/detection/3DUnet/README.md @@ -46,8 +46,6 @@ ### 2.1 深度学习框架 ``` -CANN 5.0.4 - pytorch >= 1.4.0 torchvision >= 0.6.0 onnx >= 1.7.0 diff --git a/ACL_PyTorch/contrib/cv/detection/AdvancedEAST/README.md b/ACL_PyTorch/contrib/cv/detection/AdvancedEAST/README.md index e09f125447..4dc5708ff4 100644 --- a/ACL_PyTorch/contrib/cv/detection/AdvancedEAST/README.md +++ b/ACL_PyTorch/contrib/cv/detection/AdvancedEAST/README.md @@ -5,8 +5,6 @@ - [输入输出数据](#section540883920406) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -50,22 +48,6 @@ AdvancedEAST是一种用于场景图像文本检测的算法，它主要基于EA | output1 | FLOAT32 | batchsize x 7 x 184 x 184 | ND | - - -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ---------- | ---------------------------------- | ------------------------------------------------------------ | - | 固件与驱动 | 1.0.16（NPU驱动固件版本为5.1.RC2） | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 5.1.RC2 | - | - | Python | 3.7.5 | - | - - - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/AlphaPose/README.md b/ACL_PyTorch/contrib/cv/detection/AlphaPose/README.md index 5911ab05e2..03442a661f 100644 --- a/ACL_PyTorch/contrib/cv/detection/AlphaPose/README.md +++ b/ACL_PyTorch/contrib/cv/detection/AlphaPose/README.md @@ -4,8 +4,6 @@ - [输入输出数据](#section540883920406) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -14,7 +12,6 @@ - [模型推理性能&精度](#ZH-CN_TOPIC_0000001172201573) -- [配套环境](#ZH-CN_TOPIC_0000001126121892) # 概述 @@ -43,19 +40,6 @@ | -------- | -------- | -------- | ------------ | | output | batch_size x 17 x 64 x 48 | FLOAT32 | NCHW | -# 推理环境准备\[所有版本\] - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - -| 配套 | 版本 | 环境准备指导 | -| ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | -| 固件与驱动 | 1.0.17 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | -| CANN | 6.0.RC1 | - | -| Python | 3.7.5 | - | -| PyTorch | 1.5.0+ | - | -| 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | # 快速上手 diff --git a/ACL_PyTorch/contrib/cv/detection/BSN/README.md b/ACL_PyTorch/contrib/cv/detection/BSN/README.md index bb2cbdc2e0..19a4db7b1b 100644 --- a/ACL_PyTorch/contrib/cv/detection/BSN/README.md +++ b/ACL_PyTorch/contrib/cv/detection/BSN/README.md @@ -3,8 +3,6 @@ - [概述](#ZH-CN_TOPIC_0000001172161501) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -13,10 +11,6 @@ - [模型推理性能](#ZH-CN_TOPIC_0000001172201573) -- [配套环境](#ZH-CN_TOPIC_0000001126121892) - - - # 概述 @@ -70,20 +64,6 @@ code_path=ACL_PyTorch/contrib/cv/detection | PEM model | FLOAT32 | batchsize x 1000 x 1 | ND | -# 推理环境准备\[所有版本\] - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ------------------------------------------------------------ | ------------------- | ------------------------------------------------------------ | - | 固件与驱动 | 1.0.17 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - | PyTorch | 1.5.0 | - | - | 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | | | - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/CTPN/README.md b/ACL_PyTorch/contrib/cv/detection/CTPN/README.md index a6ebc1d46e..f1734d13fb 100644 --- a/ACL_PyTorch/contrib/cv/detection/CTPN/README.md +++ b/ACL_PyTorch/contrib/cv/detection/CTPN/README.md @@ -5,10 +5,6 @@ - [输入输出数据](#section540883920406) - - -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -57,21 +53,6 @@ CTPN是一种文字检测算法，它结合了CNN与LSTM深度网络，能有效 - -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | :------------------------------------------------------------: | :-------: | :------------------------------------------------------------: | - | 固件与驱动 | 1.0.16 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 5.1.RC2 | - | - | Python | 3.7.5 | \ | - | 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/Cascade-RCNN-Resnet101-FPN-DCN/README.md b/ACL_PyTorch/contrib/cv/detection/Cascade-RCNN-Resnet101-FPN-DCN/README.md index 6988d3b8d6..13ef929f6a 100644 --- a/ACL_PyTorch/contrib/cv/detection/Cascade-RCNN-Resnet101-FPN-DCN/README.md +++ b/ACL_PyTorch/contrib/cv/detection/Cascade-RCNN-Resnet101-FPN-DCN/README.md @@ -5,10 +5,6 @@ - [输入输出数据](#section540883920406) - - -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -17,7 +13,7 @@ - [模型推理性能&精度](#ZH-CN_TOPIC_0000001172201573) - ****** +****** @@ -56,21 +52,6 @@ Cascade-RCNN-Resnet101-FPN-DCN是利用Deformable Conv（可变形卷积）和De | output | FLOAT32 | 100 x 5 | ND | -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | - | 固件与驱动 | 1.0.17(NPU驱动固件版本为6.0.RC1) | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - | Pytorch | 1.7.0 | - | - - - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/Cascade-RCNN-Resnet50-FPN/README.md b/ACL_PyTorch/contrib/cv/detection/Cascade-RCNN-Resnet50-FPN/README.md index fd65d97f0b..f3017331a3 100644 --- a/ACL_PyTorch/contrib/cv/detection/Cascade-RCNN-Resnet50-FPN/README.md +++ b/ACL_PyTorch/contrib/cv/detection/Cascade-RCNN-Resnet50-FPN/README.md @@ -5,10 +5,6 @@ - [输入输出数据](#section540883920406) - - -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -17,9 +13,7 @@ - [模型推理性能&精度](#ZH-CN_TOPIC_0000001172201573) - ****** - - +****** # 概述 @@ -56,19 +50,6 @@ Cascade-RCNN_DCN在之前的cascade-RCNN的基础上，采用形变卷积算子 | boxes | FLOAT32 | 100 x 5 | ND | | labels | INT64 | 100 x 1 | ND | -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | - | 固件与驱动 | 1.0.17(NPU驱动固件版本为6.0.RC1) | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - - # 快速上手 diff --git a/ACL_PyTorch/contrib/cv/detection/Cascade_RCNN_R101_FPN/README.md b/ACL_PyTorch/contrib/cv/detection/Cascade_RCNN_R101_FPN/README.md index b7b6e4ccf8..2f114ab2b2 100644 --- a/ACL_PyTorch/contrib/cv/detection/Cascade_RCNN_R101_FPN/README.md +++ b/ACL_PyTorch/contrib/cv/detection/Cascade_RCNN_R101_FPN/README.md @@ -5,10 +5,6 @@ - [输入输出数据](#section540883920406) - - -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -17,7 +13,7 @@ - [模型推理性能&精度](#ZH-CN_TOPIC_0000001172201573) - ****** +****** @@ -56,20 +52,6 @@ Cascade R-CNN是目标检测two-stage算法的代表之一，使用cascade回归 | boxes | FLOAT32 | 100 x 5 | ND | | labels | INT64 | 100 x 1 | ND | -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | - | 固件与驱动 | 1.0.17(NPU驱动固件版本为6.0.RC1) | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - - - # 快速上手 diff --git a/ACL_PyTorch/contrib/cv/detection/CenterFace/README.md b/ACL_PyTorch/contrib/cv/detection/CenterFace/README.md index 233b625e7d..b7aa2f1451 100644 --- a/ACL_PyTorch/contrib/cv/detection/CenterFace/README.md +++ b/ACL_PyTorch/contrib/cv/detection/CenterFace/README.md @@ -5,8 +5,6 @@ - [输入输出数据](#section540883920406) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -49,19 +47,6 @@ | output4 | FLOAT32 | 1 x 400000 | ND | -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ----------- | ------- | ------------------------------------------------------------ | - | 固件与驱动 | 1.0.17（NPU驱动固件版本为6.0.RC1） | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/CenterNet/README.md b/ACL_PyTorch/contrib/cv/detection/CenterNet/README.md index e8d67023d7..f3d9a934de 100644 --- a/ACL_PyTorch/contrib/cv/detection/CenterNet/README.md +++ b/ACL_PyTorch/contrib/cv/detection/CenterNet/README.md @@ -5,8 +5,6 @@ - [输入输出数据](#section540883920406) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -52,20 +50,6 @@ CenterNet 是在 2019 年提出的用于目标检测的模型，相比传统依 | output3 | FLOAT32 | batchsize x 2 x 128 x 128 | ND | -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ---------- | ------- | ------------------------------------------------------------ | - | 固件与驱动 | 22.0.2 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 5.1.RC2 | - | - | Python | 3.7.5 | - | - - - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/DSFD/public_address_statement.md b/ACL_PyTorch/contrib/cv/detection/DSFD/public_address_statement.md new file mode 100644 index 0000000000..da10bcab0d --- /dev/null +++ b/ACL_PyTorch/contrib/cv/detection/DSFD/public_address_statement.md @@ -0,0 +1,6 @@ +| 类型 | 开源代码地址 | 文件名 | 公网IP地址/公网URL地址/域名/邮箱地 | 用途说明 | +| ---- | ----------- | ----- | -------------------------------- | --------| +| 开发引入 | / | ACL_PyTorch/contrib/cv/detection/DSFD/DSFD.patch | https://github.com/Hakuyume/chainer-ssd | 说明源码地址 | +| 开发引入 | / | ACL_PyTorch/contrib/cv/detection/DSFD/DSFD.patch | https://github.com/fmassa/object-detection.torch | 说明源码地址 | +| 开发引入 | / | ACL_PyTorch/contrib/cv/detection/DSFD/DSFD.patch | https://arxiv.org/pdf/1512.02325.pdf | 论文链接地址 | +| 开发引入 | / | ACL_PyTorch/contrib/cv/detection/DSFD/DSFD.patch | https://arxiv.org/pdf/1512.02325.pdf | 论文链接地址 | \ No newline at end of file diff --git a/ACL_PyTorch/contrib/cv/detection/Deepspeech/README.md b/ACL_PyTorch/contrib/cv/detection/Deepspeech/README.md index d431ebb170..b6d0cbaac6 100644 --- a/ACL_PyTorch/contrib/cv/detection/Deepspeech/README.md +++ b/ACL_PyTorch/contrib/cv/detection/Deepspeech/README.md @@ -29,8 +29,6 @@ 深度学习框架与第三方库 ``` -python3.7.5 - torch == 1.8.0 torchaudio == 0.8.0 torchvision == 0.9.0 diff --git a/ACL_PyTorch/contrib/cv/detection/Detr/README.md b/ACL_PyTorch/contrib/cv/detection/Detr/README.md index f0ed2969a1..b3d53d5376 100755 --- a/ACL_PyTorch/contrib/cv/detection/Detr/README.md +++ b/ACL_PyTorch/contrib/cv/detection/Detr/README.md @@ -2,8 +2,6 @@ - [概述](##概述) -- [推理环境准备](##推理环境准备) - - [快速上手](##快速上手) - [获取源码](##获取源码) @@ -65,19 +63,6 @@ DETR是将目标检测视为一个集合预测问题（集合其实和anchors的 | Pred_logits | 1 x 100 x 4 | FLOAT32 | NCHW | -## 推理环境准备[所有版本] - -- 该模型需要以下插件与驱动。 - - **表 1** 版本配套表 - -| 配套 | 版本 |环境准备指导 -| -------- | ------- |------------- -|固件与驱动 | 22.0.2 |[Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) -| CANN | 5.1.RC2 |- -| PyTorch | 1.5.0 |- - - ## 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/Detr/public_address_statement.md b/ACL_PyTorch/contrib/cv/detection/Detr/public_address_statement.md new file mode 100644 index 0000000000..1863588b77 --- /dev/null +++ b/ACL_PyTorch/contrib/cv/detection/Detr/public_address_statement.md @@ -0,0 +1,3 @@ +| 类型 | 开源代码地址 | 文件名 | 公网IP地址/公网URL地址/域名/邮箱地 | 用途说明 | +| ---- | ----------- | ----- | -------------------------------- | --------| +| 开发引入 | / | ACL_PyTorch/contrib/cv/detection/Detr/detr.patch | https://dl.fbaipublicfiles.com/detr/detr-r50-e632da11.pth | 权重下载链接 | \ No newline at end of file diff --git a/ACL_PyTorch/contrib/cv/detection/EAST_MobileNetV3/README.md b/ACL_PyTorch/contrib/cv/detection/EAST_MobileNetV3/README.md index 7602b49f0a..86b098edbc 100644 --- a/ACL_PyTorch/contrib/cv/detection/EAST_MobileNetV3/README.md +++ b/ACL_PyTorch/contrib/cv/detection/EAST_MobileNetV3/README.md @@ -1,7 +1,6 @@ # EAST_MobileNetV3 模型推理指导 - [概述](#概述) -- [推理环境](#推理环境) - [快速上手](#快速上手) - [获取源码](#获取源码) - [准备数据集](#准备数据集) @@ -39,21 +38,6 @@ EAST是一个高效准确的场景文本检测器，通过两步进行文本检 | score | FLOAT32 | ND | batchsize x 1 x 176 x 320 | - ----- -# 推理环境 - -- 该模型推理所需配套的软件如下： - - | 配套 | 版本 | 环境准备指导 | - | --------- | ------- | ---------- | - | 固件与驱动 | 1.0.17 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - - 说明：请根据 CANN 版本选择相匹配的固件与驱动版本。 - - ---- # 快速上手 diff --git a/ACL_PyTorch/contrib/cv/detection/EAST_ResNet50_vd/README.md b/ACL_PyTorch/contrib/cv/detection/EAST_ResNet50_vd/README.md index 89b4401097..e0f50bcdca 100644 --- a/ACL_PyTorch/contrib/cv/detection/EAST_ResNet50_vd/README.md +++ b/ACL_PyTorch/contrib/cv/detection/EAST_ResNet50_vd/README.md @@ -5,8 +5,6 @@ - [输入输出数据](#section540883920406) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -15,7 +13,7 @@ - [模型推理性能&精度](#ZH-CN_TOPIC_0000001172201573) - ****** +****** # 概述 @@ -48,20 +46,6 @@ EAST是一个高效准确的场景文本检测器，通过两步进行文本检 | output2 | FLOAT32 | batchsize x 8 x 176 x 320 | NCHW | -# 推理环境准备\[所有版本\] - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - -| 配套 | 版本 | 环境准备指导 | -| ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | -| 固件与驱动 | 1.0.17 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | -| CANN | 6.0.RC1 | - | -| Python | 3.7.5 | - | -| paddlepaddle | 2.3.2 | - | -| 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/EfficientDetD0/README.md b/ACL_PyTorch/contrib/cv/detection/EfficientDetD0/README.md index 50cbf513a8..469b7d71e0 100755 --- a/ACL_PyTorch/contrib/cv/detection/EfficientDetD0/README.md +++ b/ACL_PyTorch/contrib/cv/detection/EfficientDetD0/README.md @@ -5,10 +5,6 @@ - [输入输出数据](#section540883920406) - - -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -17,7 +13,7 @@ - [模型推理性能&精度](#ZH-CN_TOPIC_0000001172201573) - ****** +****** @@ -66,24 +62,6 @@ EfficientDet是在EfficientNet基础上提出来的目标检测模型，它将Ef -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | - | 固件与驱动 | 22.0.2 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - | PyTorch | 1.8.0 | - | - | 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - - - - - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/EfficientDetD0/public_address_statement.md b/ACL_PyTorch/contrib/cv/detection/EfficientDetD0/public_address_statement.md new file mode 100644 index 0000000000..144f0301f8 --- /dev/null +++ b/ACL_PyTorch/contrib/cv/detection/EfficientDetD0/public_address_statement.md @@ -0,0 +1,28 @@ +| 类型 | 开源代码地址 | 文件名 | 公网IP地址/公网URL地址/域名/邮箱地址 | 用途说明 | +| ---- | ------------ | ------ | ------------------------------------ | -------- | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/efficientdet_d0-f3276ba8.pth | 权重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/efficientdet_d1-bb7e98fe.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/resdet50_416-08676892.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/cspresdet50b-386da277.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/cspresdext50pan-92fdd094.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/cspdarkdet53m-79062b2d.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/efficientdet_q0-bdf1bdb5.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/efficientdet_q1b-d0612140.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/efficientdet_q2-0f7564e5.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d0_34-f153e0cf.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d1_40-a30f94af.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d2_43-8107aa99.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d3_47-0b525f35.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d4_49-f56376d9.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d5_51-c79f9be6.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d6_52-4eda3773.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d7_53-6d1d7a95.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d7x-f390b87c.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/google/automl/blob/master/efficientdet/Det-AdvProp.md | 引用原网址 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d0_ap-d0cdbd0a.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d1_ap-7721d075.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d2_ap-a2995c19.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d3_ap-e4a2feab.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d4_ap-f601a5fc.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_d5_ap-3673ae5d.pth | 重下载链接 | +| 开源代码引入 |https://github.com/rwightman/efficientdet-pytorch/| ACL_PyTorch/contrib/cv/detection/EfficientDetD0/effdet.patch | https://github.com/rwightman/efficientdet-pytorch/releases/download/v0.1/tf_efficientdet_lite0-f5f303a9.pth | 重下载链接 | \ No newline at end of file diff --git a/ACL_PyTorch/contrib/cv/detection/EfficientDetD7/README.md b/ACL_PyTorch/contrib/cv/detection/EfficientDetD7/README.md index ea2836d7a8..ea0d8df9ab 100644 --- a/ACL_PyTorch/contrib/cv/detection/EfficientDetD7/README.md +++ b/ACL_PyTorch/contrib/cv/detection/EfficientDetD7/README.md @@ -4,7 +4,6 @@ - [概述](#概述) - [输入输出数据](#输入输出数据) -- [推理环境准备](#推理环境准备) - [快速上手](#快速上手) - [获取源码](#获取源码) @@ -56,21 +55,6 @@ EfficientDet该论文首先提出了一种加权双向特征金字塔网络（Bi | boxout5 | batchsize x 36 x 12 x 12 | FLOAT32 | NCHW | -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | - | 固件与驱动 | 22.0.2 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - | PyTorch | 1.8.0 | - | - | 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - - # 快速上手 diff --git a/ACL_PyTorch/contrib/cv/detection/FCENet/public_address_statement.md b/ACL_PyTorch/contrib/cv/detection/FCENet/public_address_statement.md index a5e4591f24..7ff4d9b172 100644 --- a/ACL_PyTorch/contrib/cv/detection/FCENet/public_address_statement.md +++ b/ACL_PyTorch/contrib/cv/detection/FCENet/public_address_statement.md @@ -1,4 +1,3 @@ - | 类型 | 开源代码地址 | 文件名 | 公网IP地址/公网URL地址/域名/邮箱地址 | 用途说明 | | ---- | ------------ | ------ | ------------------------------------ | -------- | |开发引入|/|FCENet/url.ini|https://download.openmmlab.com/mmocr/textdet/|下载数据集| diff --git a/ACL_PyTorch/contrib/cv/detection/FCENet/readme.md b/ACL_PyTorch/contrib/cv/detection/FCENet/readme.md index a93f2c0121..75c9496706 100644 --- a/ACL_PyTorch/contrib/cv/detection/FCENet/readme.md +++ b/ACL_PyTorch/contrib/cv/detection/FCENet/readme.md @@ -2,7 +2,6 @@ - [概述](#概述) - [输入输出数据](#输入输出数据) -- [推理环境](#推理环境) - [快速上手](#快速上手) - [获取源码](#获取源码) - [准备数据集](#准备数据集) @@ -40,19 +39,6 @@ FCENet，使用傅里叶变换来得到文本的包围框，该方法在弯曲 | output5 | FLOAT32 | ND | bs x 4 x 40 x 71 | | output6 | FLOAT32 | ND | bs x 22 x 40 x 71 | ----- -# 推理环境 - -- 该模型推理所需配套的软件如下： - - | 配套 | 版本 | 环境准备指导 | - | --------- | ------- | ---------- | - | 固件与驱动 | 1.0.17 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - - 说明：请根据推理卡型号与 CANN 版本选择相匹配的固件与驱动版本。 - ---- # 快速上手 diff --git a/ACL_PyTorch/contrib/cv/detection/FairMOT/README.md b/ACL_PyTorch/contrib/cv/detection/FairMOT/README.md index aad8081f4d..28cc9fec68 100644 --- a/ACL_PyTorch/contrib/cv/detection/FairMOT/README.md +++ b/ACL_PyTorch/contrib/cv/detection/FairMOT/README.md @@ -5,8 +5,6 @@ - [输入输出数据](#section540883920406) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -15,7 +13,7 @@ - [模型推理性能&精度](#ZH-CN_TOPIC_0000001172201573) - ****** +****** # 概述 @@ -50,24 +48,6 @@ FairMOT用于目标跟踪，它使用基于CenterNet的方法进行目标检测 - - -# 推理环境准备 - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | - | 固件与驱动 | 22.0.3 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 6.0.RC1 | - | - | Python | 3.7.5 | - | - | PyTorch | 1.6.0 | - | - | 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - - - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/Faster_R-CNN_DCN_Res101/readme.md b/ACL_PyTorch/contrib/cv/detection/Faster_R-CNN_DCN_Res101/readme.md index 7bb5e4f6be..a71be6525d 100644 --- a/ACL_PyTorch/contrib/cv/detection/Faster_R-CNN_DCN_Res101/readme.md +++ b/ACL_PyTorch/contrib/cv/detection/Faster_R-CNN_DCN_Res101/readme.md @@ -3,8 +3,6 @@ - [概述](#ZH-CN_TOPIC_0000001172161501) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -13,10 +11,6 @@ - [模型推理性能](#ZH-CN_TOPIC_0000001172201573) -- [配套环境](#ZH-CN_TOPIC_0000001126121892) - - - # 概述 @@ -53,21 +47,6 @@ FasterRCNN-DCN是FasterRCNN与DCN可行变卷积相结合得到的网络模型 - -# 推理环境准备\[所有版本\] - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - -| 配套 | 版本 | 环境准备指导 | -| ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | -| 固件与驱动 | 1.0.17 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | -| CANN | 6.0.RC1 | - | -| Python | 3.7.5 | - | -| PyTorch | 1.8.0 | - | -| 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - # 快速上手 1. 下载本模型代码包，并上传至服务器解压至用户目录下 diff --git a/ACL_PyTorch/contrib/cv/detection/Faster_R-CNN_DCN_Res50/README.md b/ACL_PyTorch/contrib/cv/detection/Faster_R-CNN_DCN_Res50/README.md index 69917024ef..d397686526 100644 --- a/ACL_PyTorch/contrib/cv/detection/Faster_R-CNN_DCN_Res50/README.md +++ b/ACL_PyTorch/contrib/cv/detection/Faster_R-CNN_DCN_Res50/README.md @@ -3,8 +3,6 @@ - [概述](#ZH-CN_TOPIC_0000001172161501) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -13,7 +11,6 @@ - [模型推理性能](#ZH-CN_TOPIC_0000001172201573) -- [配套环境](#ZH-CN_TOPIC_0000001126121892) # 概述 @@ -47,21 +44,6 @@ FasterRCNN-DCN是FasterRCNN与DCN可行变卷积相结合得到的网络模型 | labels | 100 × 1 | INT64 | ND | - -# 推理环境准备\[所有版本\] - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - -| 配套 | 版本 | 环境准备指导 | -| ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | -| 固件与驱动 | 1.0.17 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | -| CANN | 6.0.RC1 | - | -| Python | 3.7.5 | - | -| PyTorch | 1.8.0 | - | -| 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - # 快速上手 1. 下载本模型代码包，并上传至服务器解压至用户目录下 diff --git a/ACL_PyTorch/contrib/cv/detection/Faster_R-CNN_ResNet50/README.md b/ACL_PyTorch/contrib/cv/detection/Faster_R-CNN_ResNet50/README.md index 4eef86588e..9b45475739 100644 --- a/ACL_PyTorch/contrib/cv/detection/Faster_R-CNN_ResNet50/README.md +++ b/ACL_PyTorch/contrib/cv/detection/Faster_R-CNN_ResNet50/README.md @@ -3,8 +3,6 @@ - [概述](#ZH-CN_TOPIC_0000001172161501) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -13,9 +11,7 @@ - [模型推理性能](#ZH-CN_TOPIC_0000001172201573) -- [配套环境](#ZH-CN_TOPIC_0000001126121892) - - ****** +****** @@ -53,18 +49,6 @@ Faster-R-CNN 在Fast RCNN的基础上使用RPN层代替Selective Search提取候 | labels | 100 | INT64 | ND | -# 推理环境准备 - -- 该模型需要以下插件与驱动 - -| 配套 | 版本 | 环境准备指导 | -| ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | -| 固件与驱动 | 22.0.3 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | -| CANN | 6.0.RC1 | - | -| Python | 3.7.5 | - | -| PyTorch | 1.8.1 | - | -| 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/ch_PP-OCRv2_det/README.md b/ACL_PyTorch/contrib/cv/detection/ch_PP-OCRv2_det/README.md index b8a4ac3bb5..73b07e2570 100644 --- a/ACL_PyTorch/contrib/cv/detection/ch_PP-OCRv2_det/README.md +++ b/ACL_PyTorch/contrib/cv/detection/ch_PP-OCRv2_det/README.md @@ -3,8 +3,6 @@ - [概述](#ZH-CN_TOPIC_0000001172161501) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -13,7 +11,6 @@ - [模型推理性能](#ZH-CN_TOPIC_0000001172201573) -- [配套环境](#ZH-CN_TOPIC_0000001126121892) # 概述 @@ -46,20 +43,6 @@ ch_PP-OCRv2_det是基于PP-OCRv2的中文文本检测模型，PP-OCRv2在PP-OCR | output1 | FLOAT32 | batchsize x 1 x imgH x imgW | NCHW | -# 推理环境准备\[所有版本\] - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - -| 配套 | 版本 | 环境准备指导 | -| ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | -| 固件与驱动 | 22.0.2 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | -| CANN | 5.1.RC2 | - | -| Python | 3.7.5 | - | -| paddlepaddle | 2.3.2 |仅支持x86服务器安装 | -| 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/ch_PP-OCRv3_det/README.md b/ACL_PyTorch/contrib/cv/detection/ch_PP-OCRv3_det/README.md index 280efa56f3..dbdd061808 100644 --- a/ACL_PyTorch/contrib/cv/detection/ch_PP-OCRv3_det/README.md +++ b/ACL_PyTorch/contrib/cv/detection/ch_PP-OCRv3_det/README.md @@ -2,7 +2,6 @@ - [概述](#ZH-CN_TOPIC_0000001172161501) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -42,20 +41,6 @@ ch_PP-OCRv3_det是基于PP-OCRv3的中文文本检测模型，PP-OCRv3在PP-OCR2 | output1 | FLOAT32 | batchsize x 1 x imgH x imgW | NCHW | -# 推理环境准备\[所有版本\] - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - -| 配套 | 版本 | 环境准备指导 | -| ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | -| 固件与驱动 | 1.0.17 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | -| CANN | 6.0.RC1 | - | -| Python | 3.7.5 | - | -| paddlepaddle | 2.3.1 | 仅支持x86服务器安装 | -| 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/ch_ppocr_server_v2.0_det/README.md b/ACL_PyTorch/contrib/cv/detection/ch_ppocr_server_v2.0_det/README.md index 031a72e643..54bd818850 100644 --- a/ACL_PyTorch/contrib/cv/detection/ch_ppocr_server_v2.0_det/README.md +++ b/ACL_PyTorch/contrib/cv/detection/ch_ppocr_server_v2.0_det/README.md @@ -5,8 +5,6 @@ - [输入输出数据](#section540883920406) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -47,20 +45,6 @@ ch_PP-OCRv2_det是基于PP-OCRv2的中文文本检测模型，PP-OCRv2在PP-OCR | output1 | FLOAT32 | batchsize x 1 x imgH x imgW | NCHW | -# 推理环境准备\[所有版本\] - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - - | 配套 | 版本 | 环境准备指导 | - | ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | - | 固件与驱动 | 22.0.2 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | - | CANN | 5.1.RC2 | - | - | Python | 3.7.5 | - | - | paddlepaddle | 2.3.2 | 仅支持x86服务器安装 | - | 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - # 快速上手 ## 获取源码 diff --git a/ACL_PyTorch/contrib/cv/detection/en_PP-OCRv3_det/README.md b/ACL_PyTorch/contrib/cv/detection/en_PP-OCRv3_det/README.md index d0405bbc47..0cb793c6ff 100644 --- a/ACL_PyTorch/contrib/cv/detection/en_PP-OCRv3_det/README.md +++ b/ACL_PyTorch/contrib/cv/detection/en_PP-OCRv3_det/README.md @@ -3,8 +3,6 @@ - [概述](#ZH-CN_TOPIC_0000001172161501) -- [推理环境准备](#ZH-CN_TOPIC_0000001126281702) - - [快速上手](#ZH-CN_TOPIC_0000001126281700) - [获取源码](#section4622531142816) @@ -13,7 +11,6 @@ - [模型推理性能](#ZH-CN_TOPIC_0000001172201573) -- [配套环境](#ZH-CN_TOPIC_0000001126121892) # 概述 @@ -46,20 +43,6 @@ en_PP-OCRv3_det是基于[[PP-OCRv3](https://github.com/PaddlePaddle/PaddleOCR/bl | output1 | FLOAT32 | batchsize x 1 x imgH x imgW | NCHW | -# 推理环境准备\[所有版本\] - -- 该模型需要以下插件与驱动 - - **表 1** 版本配套表 - -| 配套 | 版本 | 环境准备指导 | -| ------------------------------------------------------------ | ------- | ------------------------------------------------------------ | -| 固件与驱动 | 22.0.2 | [Pytorch框架推理环境准备](https://www.hiascend.com/document/detail/zh/ModelZoo/pytorchframework/pies) | -| CANN | 5.1.RC2 | - | -| Python | 3.7.5 | - | -| PaddlePaddle | 2.3.2 | 仅支持x86服务器安装 | -| 说明：Atlas 300I Duo 推理卡请以CANN版本选择实际固件与驱动版本。 | \ | \ | - # 快速上手 ## 获取源码 -- Gitee