From 02a5b86ea3bc581113a2eb1a59b69e90bc1cb3c8 Mon Sep 17 00:00:00 2001 From: cuicheng01 <45199522+cuicheng01@users.noreply.github.com> Date: Thu, 9 Jan 2020 12:06:19 +0800 Subject: [PATCH] Add Res2Net101_vd and Res2Net200_vd pretrained model (#4180) --- PaddleCV/image_classification/README.md | 5 ++++- PaddleCV/image_classification/README_en.md | 11 +++++++++++ .../scripts/train/Res2Net101_vd_26w_4s.sh | 15 +++++++++++++++ .../scripts/train/Res2Net200_vd_26w_4s.sh | 15 +++++++++++++++ 4 files changed, 45 insertions(+), 1 deletion(-) create mode 100644 PaddleCV/image_classification/scripts/train/Res2Net101_vd_26w_4s.sh create mode 100644 PaddleCV/image_classification/scripts/train/Res2Net200_vd_26w_4s.sh diff --git a/PaddleCV/image_classification/README.md b/PaddleCV/image_classification/README.md index 9c5e5a09..f6901ffb 100644 --- a/PaddleCV/image_classification/README.md +++ b/PaddleCV/image_classification/README.md @@ -634,6 +634,8 @@ python -m paddle.distributed.launch train.py \ |[Res2Net50_26w_4s](https://paddle-imagenet-models-name.bj.bcebos.com/Res2Net50_26w_4s_pretrained.tar) | 79.33% | 94.57% | 10.731 | 8.274 | |[Res2Net50_vd_26w_4s](https://paddle-imagenet-models-name.bj.bcebos.com/Res2Net50_vd_26w_4s_pretrained.tar) | 79.75% | 94.91% | 11.012 | 8.493 | |[Res2Net50_14w_8s](https://paddle-imagenet-models-name.bj.bcebos.com/Res2Net50_14w_8s_pretrained.tar) | 79.46% | 94.70% | 16.937 | 10.205 | +|[Res2Net101_vd_26w_4s](https://paddle-imagenet-models-name.bj.bcebos.com/Res2Net101_vd_26w_4s_pretrained.tar) | 80.64% | 95.22% | 19.612 | 14.651 | +|[Res2Net200_vd_26w_4s](https://paddle-imagenet-models-name.bj.bcebos.com/Res2Net200_vd_26w_4s_pretrained.tar) | 81.21% | 95.71% | 35.809 | 26.479 | ### ResNeXt Series |Model | Top-1 | Top-5 | Paddle Fluid inference time(ms) | Paddle TensorRT inference time(ms) | @@ -789,7 +791,8 @@ python -m paddle.distributed.launch train.py \ - 2019/09/11 **Stage8**: 更新ResNet18_vd，ResNet34_vd，MobileNetV1_x0_25，MobileNetV1_x0_5，MobileNetV1_x0_75，MobileNetV2_x0_75，MobilenNetV3_small_x1_0，DPN68，DPN92，DPN98，DPN107，DPN131，ResNeXt101_vd_32x4d，ResNeXt152_vd_64x4d，Xception65，Xception71，Xception41_deeplab，Xception65_deeplab，SE_ResNet50_vd - 2019/09/20 更新EfficientNet - 2019/11/28 **Stage9**: 更新SE_ResNet18_vd，SE_ResNet34_vd，SE_ResNeXt50_vd_32x4d，ResNeXt152_vd_32x4d，Res2Net50_26w_4s，Res2Net50_14w_8s，Res2Net50_vd_26w_4s，HRNet_W18_C，HRNet_W30_C，HRNet_W32_C，HRNet_W40_C，HRNet_W44_C，HRNet_W48_C，HRNet_W64_C -- 2020/1/7 **Stage10**: 添加AutoDL Series +- 2020/01/07 **Stage10**: 更新AutoDL Series +- 2020/01/09 **Stage11**: 更新Res2Net101_vd_26w_4s, Res2Net200_vd_26w_4s ## 如何贡献代码 diff --git a/PaddleCV/image_classification/README_en.md b/PaddleCV/image_classification/README_en.md index 2ebea91d..1f1cbbf3 100644 --- a/PaddleCV/image_classification/README_en.md +++ b/PaddleCV/image_classification/README_en.md @@ -471,6 +471,13 @@ Pretrained models can be downloaded by clicking related model names. |[ShuffleNetV2_x2_0](https://paddle-imagenet-models-name.bj.bcebos.com/ShuffleNetV2_x2_0_pretrained.tar) | 73.15% | 91.20% | 6.430 | 3.954 | |[ShuffleNetV2_swish](https://paddle-imagenet-models-name.bj.bcebos.com/ShuffleNetV2_swish_pretrained.tar) | 70.03% | 89.17% | 6.078 | 4.976 | +### AutoDL Series +|Model | Top-1 | Top-5 | Paddle Fluid inference time(ms) | Paddle TensorRT inference time(ms) | +|- |:-: |:-: |:-: |:-: | +|[DARTS_4M](https://paddle-imagenet-models-name.bj.bcebos.com/DARTS_GS_4M_pretrained.tar) | 75.23% | 92.15% | 13.572 | 6.335 | +|[DARTS_6M](https://paddle-imagenet-models-name.bj.bcebos.com/DARTS_GS_6M_pretrained.tar) | 76.03% | 92.79% | 16.406 | 6.864 | +- AutoDL is improved based on DARTS, Local Rademacher Complexity is introduced to control overfitting, and model size is flexibly adjusted through Resource Constraining. + ### ResNet Series |Model | Top-1 | Top-5 | Paddle Fluid inference time(ms) | Paddle TensorRT inference time(ms) | |- |:-: |:-: |:-: |:-: | @@ -496,6 +503,8 @@ Pretrained models can be downloaded by clicking related model names. |[Res2Net50_26w_4s](https://paddle-imagenet-models-name.bj.bcebos.com/Res2Net50_26w_4s_pretrained.tar) | 79.33% | 94.57% | 10.731 | 8.274 | |[Res2Net50_vd_26w_4s](https://paddle-imagenet-models-name.bj.bcebos.com/Res2Net50_vd_26w_4s_pretrained.tar) | 79.75% | 94.91% | 11.012 | 8.493 | |[Res2Net50_14w_8s](https://paddle-imagenet-models-name.bj.bcebos.com/Res2Net50_14w_8s_pretrained.tar) | 79.46% | 94.70% | 16.937 | 10.205 | +|[Res2Net101_vd_26w_4s](https://paddle-imagenet-models-name.bj.bcebos.com/Res2Net101_vd_26w_4s_pretrained.tar) | 80.64% | 95.22% | 19.612 | 14.651 | +|[Res2Net200_vd_26w_4s](https://paddle-imagenet-models-name.bj.bcebos.com/Res2Net200_vd_26w_4s_pretrained.tar) | 81.21% | 95.71% | 35.809 | 26.479 | ### ResNeXt Series |Model | Top-1 | Top-5 | Paddle Fluid inference time(ms) | Paddle TensorRT inference time(ms) | @@ -652,6 +661,8 @@ Enforce failed. Expected x_dims[1] == labels_dims[1], but received x_dims[1]:100 - 2019/09/11 **Stage8**: Update ResNet18_vd，ResNet34_vd，MobileNetV1_x0_25，MobileNetV1_x0_5，MobileNetV1_x0_75，MobileNetV2_x0_75，MobilenNetV3_small_x1_0，DPN68，DPN92，DPN98，DPN107，DPN131，ResNeXt101_vd_32x4d，ResNeXt152_vd_64x4d，Xception65，Xception71，Xception41_deeplab，Xception65_deeplab，SE_ResNet50_vd - 2019/09/20 Update EfficientNet - 2019/11/28 **Stage9**: Update SE_ResNet18_vd，SE_ResNet34_vd，SE_ResNeXt50_vd_32x4d，ResNeXt152_vd_32x4d，Res2Net50_26w_4s，Res2Net50_14w_8s，Res2Net50_vd_26w_4s，HRNet_W18_C，HRNet_W30_C，HRNet_W32_C，HRNet_W40_C，HRNet_W44_C，HRNet_W48_C，HRNet_W64_C +- 2020/01/07 **Stage10**: Update AutoDL Series +- 2020/01/09 **Stage11**: Update Res2Net101_vd_26w_4s, Res2Net200_vd_26w_4s ## Contribute diff --git a/PaddleCV/image_classification/scripts/train/Res2Net101_vd_26w_4s.sh b/PaddleCV/image_classification/scripts/train/Res2Net101_vd_26w_4s.sh new file mode 100644 index 00000000..572b8ce1 --- /dev/null +++ b/PaddleCV/image_classification/scripts/train/Res2Net101_vd_26w_4s.sh @@ -0,0 +1,15 @@ +#Res2Net101_vd_26w_4s + +python train.py \ + --model=Res2Net101_vd_26w_4s \ + --batch_size=256 \ + --total_images=1281167 \ + --class_dim=1000 \ + --lr_strategy=cosine_decay \ + --lr=0.1 \ + --num_epochs=200 \ + --model_save_dir=output/ \ + --l2_decay=1e-4 \ + --use_mixup=True \ + --use_label_smoothing=True \ + --label_smoothing_epsilon=0.1 diff --git a/PaddleCV/image_classification/scripts/train/Res2Net200_vd_26w_4s.sh b/PaddleCV/image_classification/scripts/train/Res2Net200_vd_26w_4s.sh new file mode 100644 index 00000000..8048e79b --- /dev/null +++ b/PaddleCV/image_classification/scripts/train/Res2Net200_vd_26w_4s.sh @@ -0,0 +1,15 @@ +#Res2Net200_vd_26w_4s + +python train.py \ + --model=Res2Net200_vd_26w_4s \ + --batch_size=256 \ + --total_images=1281167 \ + --class_dim=1000 \ + --lr_strategy=cosine_decay \ + --lr=0.1 \ + --num_epochs=200 \ + --model_save_dir=output/ \ + --l2_decay=1e-4 \ + --use_mixup=True \ + --use_label_smoothing=True \ + --label_smoothing_epsilon=0.1 -- GitLab