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modules/README.md
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...@@ -21,14 +21,14 @@ English | [简体中文](README_ch.md) ...@@ -21,14 +21,14 @@ English | [简体中文](README_ch.md)
|module|Network|Dataset|Introduction| |module|Network|Dataset|Introduction|
|--|--|--|--| |--|--|--|--|
|[DriverStatusRecognition](image/classification/DriverStatusRecognition)|MobileNetV3_small_ssld|分心司机检测数据集|| |[DriverStatusRecognition](image/classification/DriverStatusRecognition)|MobileNetV3_small_ssld|Drivers||
|[mobilenet_v2_animals](image/classification/mobilenet_v2_animals)|MobileNet_v2|百度自建动物数据集|| |[mobilenet_v2_animals](image/classification/mobilenet_v2_animals)|MobileNet_v2|Animals||
|[repvgg_a1_imagenet](image/classification/repvgg_a1_imagenet)|RepVGG|ImageNet-2012|| |[repvgg_a1_imagenet](image/classification/repvgg_a1_imagenet)|RepVGG|ImageNet-2012||
|[repvgg_a0_imagenet](image/classification/repvgg_a0_imagenet)|RepVGG|ImageNet-2012|| |[repvgg_a0_imagenet](image/classification/repvgg_a0_imagenet)|RepVGG|ImageNet-2012||
|[resnext152_32x4d_imagenet](image/classification/resnext152_32x4d_imagenet)|ResNeXt|ImageNet-2012|| |[resnext152_32x4d_imagenet](image/classification/resnext152_32x4d_imagenet)|ResNeXt|ImageNet-2012||
|[resnet_v2_152_imagenet](image/classification/resnet_v2_152_imagenet)|ResNet V2|ImageNet-2012|| |[resnet_v2_152_imagenet](image/classification/resnet_v2_152_imagenet)|ResNet V2|ImageNet-2012||
|[resnet50_vd_animals](image/classification/resnet50_vd_animals)|ResNet50_vd|百度自建动物数据集|| |[resnet50_vd_animals](image/classification/resnet50_vd_animals)|ResNet50_vd|Animals||
|[food_classification](image/classification/food_classification)|ResNet50_vd_ssld|美食数据集|| |[food_classification](image/classification/food_classification)|ResNet50_vd_ssld|dishes||
|[mobilenet_v3_large_imagenet_ssld](image/classification/mobilenet_v3_large_imagenet_ssld)|Mobilenet_v3_large|ImageNet-2012|| |[mobilenet_v3_large_imagenet_ssld](image/classification/mobilenet_v3_large_imagenet_ssld)|Mobilenet_v3_large|ImageNet-2012||
|[resnext152_vd_32x4d_imagenet](image/classification/resnext152_vd_32x4d_imagenet)|||| |[resnext152_vd_32x4d_imagenet](image/classification/resnext152_vd_32x4d_imagenet)||||
|[ghostnet_x1_3_imagenet_ssld](image/classification/ghostnet_x1_3_imagenet_ssld)|GhostNet|ImageNet-2012|| |[ghostnet_x1_3_imagenet_ssld](image/classification/ghostnet_x1_3_imagenet_ssld)|GhostNet|ImageNet-2012||
...@@ -38,13 +38,13 @@ English | [简体中文](README_ch.md) ...@@ -38,13 +38,13 @@ English | [简体中文](README_ch.md)
|[efficientnetb0_imagenet](image/classification/efficientnetb0_imagenet)|EfficientNet|ImageNet-2012|| |[efficientnetb0_imagenet](image/classification/efficientnetb0_imagenet)|EfficientNet|ImageNet-2012||
|[efficientnetb1_imagenet](image/classification/efficientnetb1_imagenet)|EfficientNet|ImageNet-2012|| |[efficientnetb1_imagenet](image/classification/efficientnetb1_imagenet)|EfficientNet|ImageNet-2012||
|[mobilenet_v2_imagenet_ssld](image/classification/mobilenet_v2_imagenet_ssld)|Mobilenet_v2|ImageNet-2012|| |[mobilenet_v2_imagenet_ssld](image/classification/mobilenet_v2_imagenet_ssld)|Mobilenet_v2|ImageNet-2012||
|[resnet50_vd_dishes](image/classification/resnet50_vd_dishes)|ResNet50_vd|百度自建菜品数据集|| |[resnet50_vd_dishes](image/classification/resnet50_vd_dishes)|ResNet50_vd|dishes||
|[pnasnet_imagenet](image/classification/pnasnet_imagenet)|PNASNet|ImageNet-2012|| |[pnasnet_imagenet](image/classification/pnasnet_imagenet)|PNASNet|ImageNet-2012||
|[rexnet_2_0_imagenet](image/classification/rexnet_2_0_imagenet)|ReXNet|ImageNet-2012|| |[rexnet_2_0_imagenet](image/classification/rexnet_2_0_imagenet)|ReXNet|ImageNet-2012||
|[SnakeIdentification](image/classification/SnakeIdentification)|ResNet50_vd_ssld|蛇种数据集|| |[SnakeIdentification](image/classification/SnakeIdentification)|ResNet50_vd_ssld|snakes||
|[hrnet40_imagenet](image/classification/hrnet40_imagenet)|HRNet|ImageNet-2012|| |[hrnet40_imagenet](image/classification/hrnet40_imagenet)|HRNet|ImageNet-2012||
|[resnet_v2_34_imagenet](image/classification/resnet_v2_34_imagenet)|ResNet V2|ImageNet-2012|| |[resnet_v2_34_imagenet](image/classification/resnet_v2_34_imagenet)|ResNet V2|ImageNet-2012||
|[mobilenet_v2_dishes](image/classification/mobilenet_v2_dishes)|MobileNet_v2|百度自建菜品数据集|| |[mobilenet_v2_dishes](image/classification/mobilenet_v2_dishes)|MobileNet_v2|dishes||
|[resnext101_vd_32x4d_imagenet](image/classification/resnext101_vd_32x4d_imagenet)|ResNeXt|ImageNet-2012|| |[resnext101_vd_32x4d_imagenet](image/classification/resnext101_vd_32x4d_imagenet)|ResNeXt|ImageNet-2012||
|[repvgg_b2g4_imagenet](image/classification/repvgg_b2g4_imagenet)|RepVGG|ImageNet-2012|| |[repvgg_b2g4_imagenet](image/classification/repvgg_b2g4_imagenet)|RepVGG|ImageNet-2012||
|[fix_resnext101_32x48d_wsl_imagenet](image/classification/fix_resnext101_32x48d_wsl_imagenet)|ResNeXt|ImageNet-2012|| |[fix_resnext101_32x48d_wsl_imagenet](image/classification/fix_resnext101_32x48d_wsl_imagenet)|ResNeXt|ImageNet-2012||
...@@ -56,7 +56,7 @@ English | [简体中文](README_ch.md) ...@@ -56,7 +56,7 @@ English | [简体中文](README_ch.md)
|[densenet161_imagenet](image/classification/densenet161_imagenet)|DenseNet|ImageNet-2012|| |[densenet161_imagenet](image/classification/densenet161_imagenet)|DenseNet|ImageNet-2012||
|[vgg19_imagenet](image/classification/vgg19_imagenet)|vgg19_imagenet|ImageNet-2012|| |[vgg19_imagenet](image/classification/vgg19_imagenet)|vgg19_imagenet|ImageNet-2012||
|[mobilenet_v2_imagenet](image/classification/mobilenet_v2_imagenet)|Mobilenet_v2|ImageNet-2012|| |[mobilenet_v2_imagenet](image/classification/mobilenet_v2_imagenet)|Mobilenet_v2|ImageNet-2012||
|[resnet50_vd_10w](image/classification/resnet50_vd_10w)|ResNet_vd|百度自建数据集|| |[resnet50_vd_10w](image/classification/resnet50_vd_10w)|ResNet_vd|private||
|[resnet_v2_101_imagenet](image/classification/resnet_v2_101_imagenet)|ResNet V2 101|ImageNet-2012|| |[resnet_v2_101_imagenet](image/classification/resnet_v2_101_imagenet)|ResNet V2 101|ImageNet-2012||
|[darknet53_imagenet](image/classification/darknet53_imagenet)|DarkNet|ImageNet-2012|| |[darknet53_imagenet](image/classification/darknet53_imagenet)|DarkNet|ImageNet-2012||
|[se_resnext50_32x4d_imagenet](image/classification/se_resnext50_32x4d_imagenet)|SE_ResNeXt|ImageNet-2012|| |[se_resnext50_32x4d_imagenet](image/classification/se_resnext50_32x4d_imagenet)|SE_ResNeXt|ImageNet-2012||
...@@ -108,7 +108,7 @@ English | [简体中文](README_ch.md) ...@@ -108,7 +108,7 @@ English | [简体中文](README_ch.md)
|[efficientnetb5_imagenet](image/classification/efficientnetb5_imagenet)|EfficientNet|ImageNet-2012|| |[efficientnetb5_imagenet](image/classification/efficientnetb5_imagenet)|EfficientNet|ImageNet-2012||
|[repvgg_b1g2_imagenet](image/classification/repvgg_b1g2_imagenet)|RepVGG|ImageNet-2012|| |[repvgg_b1g2_imagenet](image/classification/repvgg_b1g2_imagenet)|RepVGG|ImageNet-2012||
|[resnext101_32x48d_wsl](image/classification/resnext101_32x48d_wsl)|ResNeXt_wsl|ImageNet-2012|| |[resnext101_32x48d_wsl](image/classification/resnext101_32x48d_wsl)|ResNeXt_wsl|ImageNet-2012||
|[resnet50_vd_wildanimals](image/classification/resnet50_vd_wildanimals)|ResNet_vd|IFAW 自建野生动物数据集|| |[resnet50_vd_wildanimals](image/classification/resnet50_vd_wildanimals)|ResNet_vd|IFAW wild animals||
|[nasnet_imagenet](image/classification/nasnet_imagenet)|NASNet|ImageNet-2012|| |[nasnet_imagenet](image/classification/nasnet_imagenet)|NASNet|ImageNet-2012||
|[se_resnet18_vd_imagenet](image/classification/se_resnet18_vd_imagenet)|||| |[se_resnet18_vd_imagenet](image/classification/se_resnet18_vd_imagenet)||||
|[spinalnet_res50_gemstone](image/classification/spinalnet_res50_gemstone)|resnet50|gemstone|| |[spinalnet_res50_gemstone](image/classification/spinalnet_res50_gemstone)|resnet50|gemstone||
...@@ -137,61 +137,61 @@ English | [简体中文](README_ch.md) ...@@ -137,61 +137,61 @@ English | [简体中文](README_ch.md)
|module|Network|Dataset|Introduction| Huggingface Spaces Demo| |module|Network|Dataset|Introduction| Huggingface Spaces Demo|
|--|--|--|--|--| |--|--|--|--|--|
|[pixel2style2pixel](image/Image_gan/gan/pixel2style2pixel/)|Pixel2Style2Pixel|-|人脸转正| |[pixel2style2pixel](image/Image_gan/gan/pixel2style2pixel/)|Pixel2Style2Pixel|-|human face|
|[stgan_bald](image/Image_gan/gan/stgan_bald/)|STGAN|CelebA|秃头生成器| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/stgan_bald) | |[stgan_bald](image/Image_gan/gan/stgan_bald/)|STGAN|CelebA|stgan_bald| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/stgan_bald) |
|[styleganv2_editing](image/Image_gan/gan/styleganv2_editing)|StyleGAN V2|-|人脸编辑| |[styleganv2_editing](image/Image_gan/gan/styleganv2_editing)|StyleGAN V2|-|human face editing|
|[wav2lip](image/Image_gan/gan/wav2lip)|wav2lip|LRS2|唇形生成| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/wav2lip) | |[wav2lip](image/Image_gan/gan/wav2lip)|wav2lip|LRS2|wav2lip| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/wav2lip) |
|[attgan_celeba](image/Image_gan/attgan_celeba/)|AttGAN|Celeba|人脸编辑| |[attgan_celeba](image/Image_gan/attgan_celeba/)|AttGAN|Celeba|human face editing|
|[cyclegan_cityscapes](image/Image_gan/cyclegan_cityscapes)|CycleGAN|Cityscapes|实景图和语义分割结果互相转换| |[cyclegan_cityscapes](image/Image_gan/cyclegan_cityscapes)|CycleGAN|Cityscapes|cyclegan_cityscapes|
|[stargan_celeba](image/Image_gan/stargan_celeba)|StarGAN|Celeba|人脸编辑| |[stargan_celeba](image/Image_gan/stargan_celeba)|StarGAN|Celeba|human face editing|
|[stgan_celeba](image/Image_gan/stgan_celeba/)|STGAN|Celeba|人脸编辑| |[stgan_celeba](image/Image_gan/stgan_celeba/)|STGAN|Celeba|human face editing|
|[ID_Photo_GEN](image/Image_gan/style_transfer/ID_Photo_GEN)|HRNet_W18|-|证件照生成| |[ID_Photo_GEN](image/Image_gan/style_transfer/ID_Photo_GEN)|HRNet_W18|-|ID_Photo_GEN|
|[Photo2Cartoon](image/Image_gan/style_transfer/Photo2Cartoon)|U-GAT-IT|cartoon_data|人脸卡通化|[![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/photo2cartoon) | |[Photo2Cartoon](image/Image_gan/style_transfer/Photo2Cartoon)|U-GAT-IT|cartoon_data|cartoon|[![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/photo2cartoon) |
|[U2Net_Portrait](image/Image_gan/style_transfer/U2Net_Portrait)|U^2Net|-|人脸素描化| |[U2Net_Portrait](image/Image_gan/style_transfer/U2Net_Portrait)|U^2Net|-|Portrait|
|[UGATIT_100w](image/Image_gan/style_transfer/UGATIT_100w)|U-GAT-IT|selfie2anime|人脸动漫化| |[UGATIT_100w](image/Image_gan/style_transfer/UGATIT_100w)|U-GAT-IT|selfie2anime|selfie2anime|
|[UGATIT_83w](image/Image_gan/style_transfer/UGATIT_83w)|U-GAT-IT|selfie2anime|人脸动漫化| |[UGATIT_83w](image/Image_gan/style_transfer/UGATIT_83w)|U-GAT-IT|selfie2anime|selfie2anime|
|[UGATIT_92w](image/Image_gan/style_transfer/UGATIT_92w)| U-GAT-IT|selfie2anime|人脸动漫化| |[UGATIT_92w](image/Image_gan/style_transfer/UGATIT_92w)| U-GAT-IT|selfie2anime|selfie2anime|
|[animegan_v1_hayao_60](image/Image_gan/style_transfer/animegan_v1_hayao_60)|AnimeGAN|The Wind Rises|图像风格迁移-宫崎骏| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v1_hayao_60) | |[animegan_v1_hayao_60](image/Image_gan/style_transfer/animegan_v1_hayao_60)|AnimeGAN|The Wind Rises|animegan_v1_hayao| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v1_hayao_60) |
|[animegan_v2_hayao_64](image/Image_gan/style_transfer/animegan_v2_hayao_64)|AnimeGAN|The Wind Rises|图像风格迁移-宫崎骏| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_hayao_64) | |[animegan_v2_hayao_64](image/Image_gan/style_transfer/animegan_v2_hayao_64)|AnimeGAN|The Wind Rises|animegan_v1_hayao| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_hayao_64) |
|[animegan_v2_hayao_99](image/Image_gan/style_transfer/animegan_v2_hayao_99)|AnimeGAN|The Wind Rises|图像风格迁移-宫崎骏| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_hayao_99) | |[animegan_v2_hayao_99](image/Image_gan/style_transfer/animegan_v2_hayao_99)|AnimeGAN|The Wind Rises|animegan_v1_hayao| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_hayao_99) |
|[animegan_v2_paprika_54](image/Image_gan/style_transfer/animegan_v2_paprika_54)|AnimeGAN|Paprika|图像风格迁移-今敏| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_paprika_54) | |[animegan_v2_paprika_54](image/Image_gan/style_transfer/animegan_v2_paprika_54)|AnimeGAN|Paprika|animegan_v2_paprika| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_paprika_54) |
|[animegan_v2_paprika_74](image/Image_gan/style_transfer/animegan_v2_paprika_74)|AnimeGAN|Paprika|图像风格迁移-今敏| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_paprika_74) | |[animegan_v2_paprika_74](image/Image_gan/style_transfer/animegan_v2_paprika_74)|AnimeGAN|Paprika|animegan_v2_paprika| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_paprika_74) |
|[animegan_v2_paprika_97](image/Image_gan/style_transfer/animegan_v2_paprika_97)|AnimeGAN|Paprika|图像风格迁移-今敏| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_paprika_97) | |[animegan_v2_paprika_97](image/Image_gan/style_transfer/animegan_v2_paprika_97)|AnimeGAN|Paprika|animegan_v2_paprika| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_paprika_97) |
|[animegan_v2_paprika_98](image/Image_gan/style_transfer/animegan_v2_paprika_98)|AnimeGAN|Paprika|图像风格迁移-今敏| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_paprika_98) | |[animegan_v2_paprika_98](image/Image_gan/style_transfer/animegan_v2_paprika_98)|AnimeGAN|Paprika|animegan_v2_paprika| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_paprika_98) |
|[animegan_v2_shinkai_33](image/Image_gan/style_transfer/animegan_v2_shinkai_33)|AnimeGAN|Your Name, Weathering with you|图像风格迁移-新海诚| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_shinkai_33) | |[animegan_v2_shinkai_33](image/Image_gan/style_transfer/animegan_v2_shinkai_33)|AnimeGAN|Your Name, Weathering with you|animegan_v2_shinkai| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_shinkai_33) |
|[animegan_v2_shinkai_53](image/Image_gan/style_transfer/animegan_v2_shinkai_53)|AnimeGAN|Your Name, Weathering with you|图像风格迁移-新海诚| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_shinkai_53) | |[animegan_v2_shinkai_53](image/Image_gan/style_transfer/animegan_v2_shinkai_53)|AnimeGAN|Your Name, Weathering with you|animegan_v2_shinkai| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/animegan_v2_shinkai_53) |
|[msgnet](image/Image_gan/style_transfer/msgnet)|msgnet|COCO2014| |[![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/msgnet) | |[msgnet](image/Image_gan/style_transfer/msgnet)|msgnet|COCO2014| |[![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/msgnet) |
|[stylepro_artistic](image/Image_gan/style_transfer/stylepro_artistic)|StyleProNet|MS-COCO + WikiArt|艺术风格迁移| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/stylepro_artistic) | |[stylepro_artistic](image/Image_gan/style_transfer/stylepro_artistic)|StyleProNet|MS-COCO + WikiArt|stylepro_artistic| [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/PaddlePaddle/stylepro_artistic) |
|stylegan_ffhq|StyleGAN|FFHQ|图像风格迁移| |stylegan_ffhq|StyleGAN|FFHQ|stylepro_artistic|
- ### Keypoint Detection - ### Keypoint Detection
|module|Network|Dataset|Introduction| |module|Network|Dataset|Introduction|
|--|--|--|--| |--|--|--|--|
|[face_landmark_localization](image/keypoint_detection/face_landmark_localization)|Face_Landmark|AFW/AFLW|人脸关键点检测| |[face_landmark_localization](image/keypoint_detection/face_landmark_localization)|Face_Landmark|AFW/AFLW|Face_Landmark|
|[hand_pose_localization](image/keypoint_detection/hand_pose_localization)|-|MPII, NZSL|手部关键点检测| |[hand_pose_localization](image/keypoint_detection/hand_pose_localization)|-|MPII, NZSL|hand_pose_localization|
|[openpose_body_estimation](image/keypoint_detection/openpose_body_estimation)|two-branch multi-stage CNN|MPII, COCO 2016|肢体关键点检测| |[openpose_body_estimation](image/keypoint_detection/openpose_body_estimation)|two-branch multi-stage CNN|MPII, COCO 2016|openpose_body_estimation|
|[human_pose_estimation_resnet50_mpii](image/keypoint_detection/human_pose_estimation_resnet50_mpii)|Pose_Resnet50|MPII|人体骨骼关键点检测 |[human_pose_estimation_resnet50_mpii](image/keypoint_detection/human_pose_estimation_resnet50_mpii)|Pose_Resnet50|MPII|human_pose_estimation
|[openpose_hands_estimation](image/keypoint_detection/openpose_hands_estimation)|-|MPII, NZSL|手部关键点检测| |[openpose_hands_estimation](image/keypoint_detection/openpose_hands_estimation)|-|MPII, NZSL|openpose_hands_estimation|
- ### Semantic Segmentation - ### Semantic Segmentation
|module|Network|Dataset|Introduction| |module|Network|Dataset|Introduction|
|--|--|--|--| |--|--|--|--|
|[deeplabv3p_xception65_humanseg](image/semantic_segmentation/deeplabv3p_xception65_humanseg)|deeplabv3p|百度自建数据集|人像分割| |[deeplabv3p_xception65_humanseg](image/semantic_segmentation/deeplabv3p_xception65_humanseg)|deeplabv3p|-|humanseg|
|[humanseg_server](image/semantic_segmentation/humanseg_server)|deeplabv3p|百度自建数据集|人像分割| |[humanseg_server](image/semantic_segmentation/humanseg_server)|deeplabv3p|-|humanseg|
|[humanseg_mobile](image/semantic_segmentation/humanseg_mobile)|hrnet|百度自建数据集|人像分割-移动端前置摄像头| |[humanseg_mobile](image/semantic_segmentation/humanseg_mobile)|hrnet|-|humanseg|
|[humanseg_lite](image/semantic_segmentation/umanseg_lite)|shufflenet|百度自建数据集|轻量级人像分割-移动端实时| |[humanseg_lite](image/semantic_segmentation/umanseg_lite)|shufflenet|-|humanseg|
|[ExtremeC3_Portrait_Segmentation](image/semantic_segmentation/ExtremeC3_Portrait_Segmentation)|ExtremeC3|EG1800, Baidu fashion dataset|轻量化人像分割| |[ExtremeC3_Portrait_Segmentation](image/semantic_segmentation/ExtremeC3_Portrait_Segmentation)|ExtremeC3|EG1800, Baidu fashion dataset|humanseg|
|[SINet_Portrait_Segmentation](image/semantic_segmentation/SINet_Portrait_Segmentation)|SINet|EG1800, Baidu fashion dataset|轻量化人像分割| |[SINet_Portrait_Segmentation](image/semantic_segmentation/SINet_Portrait_Segmentation)|SINet|EG1800, Baidu fashion dataset|humanseg|
|[FCN_HRNet_W18_Face_Seg](image/semantic_segmentation/FCN_HRNet_W18_Face_Seg)|FCN_HRNet_W18|-|人像分割| |[FCN_HRNet_W18_Face_Seg](image/semantic_segmentation/FCN_HRNet_W18_Face_Seg)|FCN_HRNet_W18|-|humanseg|
|[ace2p](image/semantic_segmentation/ace2p)|ACE2P|LIP|人体解析| |[ace2p](image/semantic_segmentation/ace2p)|ACE2P|LIP|ACE2P|
|[Pneumonia_CT_LKM_PP](image/semantic_segmentation/Pneumonia_CT_LKM_PP)|U-NET+|连心医疗授权脱敏数据集|肺炎CT影像分析| |[Pneumonia_CT_LKM_PP](image/semantic_segmentation/Pneumonia_CT_LKM_PP)|U-NET+|-|Pneumonia_CT|
|[Pneumonia_CT_LKM_PP_lung](image/semantic_segmentation/Pneumonia_CT_LKM_PP_lung)|U-NET+|连心医疗授权脱敏数据集|肺炎CT影像分析| |[Pneumonia_CT_LKM_PP_lung](image/semantic_segmentation/Pneumonia_CT_LKM_PP_lung)|U-NET+|-|Pneumonia_CT|
|[ocrnet_hrnetw18_voc](image/semantic_segmentation/ocrnet_hrnetw18_voc)|ocrnet, hrnet|PascalVoc2012| |[ocrnet_hrnetw18_voc](image/semantic_segmentation/ocrnet_hrnetw18_voc)|ocrnet, hrnet|PascalVoc2012|
|[U2Net](image/semantic_segmentation/U2Net)|U^2Net|-|图像前景背景分割| |[U2Net](image/semantic_segmentation/U2Net)|U^2Net|-|U2Net|
|[U2Netp](image/semantic_segmentation/U2Netp)|U^2Net|-|图像前景背景分割| |[U2Netp](image/semantic_segmentation/U2Netp)|U^2Net|-|U2Net|
|[Extract_Line_Draft](image/semantic_segmentation/Extract_Line_Draft)|UNet|Pixiv|线稿提取| |[Extract_Line_Draft](image/semantic_segmentation/Extract_Line_Draft)|UNet|Pixiv|Extract_Line_Draft|
|[unet_cityscapes](image/semantic_segmentation/unet_cityscapes)|UNet|cityscapes| |[unet_cityscapes](image/semantic_segmentation/unet_cityscapes)|UNet|cityscapes|
|[ocrnet_hrnetw18_cityscapes](image/semantic_segmentation/ocrnet_hrnetw18_cityscapes)|ocrnet_hrnetw18|cityscapes| |[ocrnet_hrnetw18_cityscapes](image/semantic_segmentation/ocrnet_hrnetw18_cityscapes)|ocrnet_hrnetw18|cityscapes|
|[hardnet_cityscapes](image/semantic_segmentation/hardnet_cityscapes)|hardnet|cityscapes| |[hardnet_cityscapes](image/semantic_segmentation/hardnet_cityscapes)|hardnet|cityscapes|
...@@ -210,13 +210,13 @@ English | [简体中文](README_ch.md) ...@@ -210,13 +210,13 @@ English | [简体中文](README_ch.md)
|module|Network|Dataset|Introduction| |module|Network|Dataset|Introduction|
|--|--|--|--| |--|--|--|--|
|[pyramidbox_lite_mobile](image/face_detection/pyramidbox_lite_mobile)|PyramidBox|WIDER FACE数据集 + 百度自采人脸数据集|轻量级人脸检测-移动端| |[pyramidbox_lite_mobile](image/face_detection/pyramidbox_lite_mobile)|PyramidBox|WIDER FACE|face_detection|
|[pyramidbox_lite_mobile_mask](image/face_detection/pyramidbox_lite_mobile_mask)|PyramidBox|WIDER FACE数据集 + 百度自采人脸数据集|轻量级人脸口罩检测-移动端| |[pyramidbox_lite_mobile_mask](image/face_detection/pyramidbox_lite_mobile_mask)|PyramidBox|WIDER FACE|face_detection|
|[pyramidbox_lite_server_mask](image/face_detection/pyramidbox_lite_server_mask)|PyramidBox|WIDER FACE数据集 + 百度自采人脸数据集|轻量级人脸口罩检测| |[pyramidbox_lite_server_mask](image/face_detection/pyramidbox_lite_server_mask)|PyramidBox|WIDER FACE|face_detection|
|[ultra_light_fast_generic_face_detector_1mb_640](image/face_detection/ultra_light_fast_generic_face_detector_1mb_640)|Ultra-Light-Fast-Generic-Face-Detector-1MB|WIDER FACE数据集|轻量级通用人脸检测-低算力设备| |[ultra_light_fast_generic_face_detector_1mb_640](image/face_detection/ultra_light_fast_generic_face_detector_1mb_640)|Ultra-Light-Fast-Generic-Face-Detector-1MB|WIDER FACE|face_detection|
|[ultra_light_fast_generic_face_detector_1mb_320](image/face_detection/ultra_light_fast_generic_face_detector_1mb_320)|Ultra-Light-Fast-Generic-Face-Detector-1MB|WIDER FACE数据集|轻量级通用人脸检测-低算力设备| |[ultra_light_fast_generic_face_detector_1mb_320](image/face_detection/ultra_light_fast_generic_face_detector_1mb_320)|Ultra-Light-Fast-Generic-Face-Detector-1MB|WIDER FACE|face_detection|
|[pyramidbox_lite_server](image/face_detection/pyramidbox_lite_server)|PyramidBox|WIDER FACE数据集 + 百度自采人脸数据集|轻量级人脸检测| |[pyramidbox_lite_server](image/face_detection/pyramidbox_lite_server)|PyramidBox|WIDER FACE|face_detection|
|[pyramidbox_face_detection](image/face_detection/pyramidbox_face_detection)|PyramidBox|WIDER FACE数据集|人脸检测| |[pyramidbox_face_detection](image/face_detection/pyramidbox_face_detection)|PyramidBox|WIDER FACE|face_detection|
- ### Text Recognition - ### Text Recognition
......
modules/image/object_detection/faster_rcnn_resnet50_coco2017/README.md
浏览文件 @ 0b8f5660
...@@ -59,7 +59,7 @@ ...@@ -59,7 +59,7 @@
object_detector = hub.Module(name="faster_rcnn_resnet50_coco2017") object_detector = hub.Module(name="faster_rcnn_resnet50_coco2017")
result = object_detector.object_detection(images=[cv2.imread('/PATH/TO/IMAGE')]) result = object_detector.object_detection(images=[cv2.imread('/PATH/TO/IMAGE')])
# or # or
# result = object_detector.object_detection((paths=['/PATH/TO/IMAGE']) # result = object_detector.object_detection(paths=['/PATH/TO/IMAGE'])
``` ```
- ### 3、API - ### 3、API
......
modules/image/object_detection/faster_rcnn_resnet50_coco2017/README_en.md
浏览文件 @ 0b8f5660
...@@ -60,7 +60,7 @@ ...@@ -60,7 +60,7 @@
object_detector = hub.Module(name="faster_rcnn_resnet50_coco2017") object_detector = hub.Module(name="faster_rcnn_resnet50_coco2017")
result = object_detector.object_detection(images=[cv2.imread('/PATH/TO/IMAGE')]) result = object_detector.object_detection(images=[cv2.imread('/PATH/TO/IMAGE')])
# or # or
# result = object_detector.object_detection((paths=['/PATH/TO/IMAGE']) # result = object_detector.object_detection(paths=['/PATH/TO/IMAGE'])
``` ```
- ### 3、API - ### 3、API
......
modules/text/language_model/rbt3/README.md
浏览文件 @ 0b8f5660
```shell ```shell
$ hub install rtb3==2.0.1 $ hub install rtb3==2.0.2
``` ```
<p align="center"> <p align="center">
<img src="https://bj.bcebos.com/paddlehub/paddlehub-img/bert_network.png" hspace='10'/> <br /> <img src="https://bj.bcebos.com/paddlehub/paddlehub-img/bert_network.png" hspace='10'/> <br />
...@@ -85,7 +85,7 @@ label_map = {0: 'negative', 1: 'positive'} ...@@ -85,7 +85,7 @@ label_map = {0: 'negative', 1: 'positive'}
model = hub.Module( model = hub.Module(
name='rtb3', name='rtb3',
version='2.0.1', version='2.0.2',
task='seq-cls', task='seq-cls',
load_checkpoint='/path/to/parameters', load_checkpoint='/path/to/parameters',
label_map=label_map) label_map=label_map)
...@@ -163,3 +163,7 @@ paddlehub >= 2.0.0 ...@@ -163,3 +163,7 @@ paddlehub >= 2.0.0
* 2.0.1 * 2.0.1
增加文本匹配任务`text-matching` 增加文本匹配任务`text-matching`
* 2.0.2
更新预训练模型调用方法
modules/text/language_model/rbt3/module.py
浏览文件 @ 0b8f5660
...@@ -11,17 +11,19 @@ ...@@ -11,17 +11,19 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
from typing import Dict
import os
import math import math
import os
from typing import Dict
import paddle import paddle
import paddle.nn as nn import paddle.nn as nn
import paddle.nn.functional as F import paddle.nn.functional as F
from paddlenlp.transformers.roberta.modeling import RobertaForSequenceClassification, RobertaForTokenClassification, RobertaModel
from paddlenlp.transformers.roberta.tokenizer import RobertaTokenizer
from paddlenlp.metrics import ChunkEvaluator from paddlenlp.metrics import ChunkEvaluator
from paddlenlp.transformers import AutoModel
from paddlenlp.transformers import AutoModelForSequenceClassification
from paddlenlp.transformers import AutoModelForTokenClassification
from paddlenlp.transformers import AutoTokenizer
from paddlehub.module.module import moduleinfo from paddlehub.module.module import moduleinfo
from paddlehub.module.nlp_module import TransformerModule from paddlehub.module.nlp_module import TransformerModule
from paddlehub.utils.log import logger from paddlehub.utils.log import logger
...@@ -29,7 +31,7 @@ from paddlehub.utils.log import logger ...@@ -29,7 +31,7 @@ from paddlehub.utils.log import logger
@moduleinfo( @moduleinfo(
name="rbt3", name="rbt3",
version="2.0.1", version="2.0.2",
summary="rbt3, 3-layer, 768-hidden, 12-heads, 38M parameters ", summary="rbt3, 3-layer, 768-hidden, 12-heads, 38M parameters ",
author="ymcui", author="ymcui",
author_email="ymcui@ir.hit.edu.cn", author_email="ymcui@ir.hit.edu.cn",
...@@ -42,13 +44,13 @@ class Roberta(nn.Layer): ...@@ -42,13 +44,13 @@ class Roberta(nn.Layer):
""" """
def __init__( def __init__(
self, self,
task: str = None, task: str = None,
load_checkpoint: str = None, load_checkpoint: str = None,
label_map: Dict = None, label_map: Dict = None,
num_classes: int = 2, num_classes: int = 2,
suffix: bool = False, suffix: bool = False,
**kwargs, **kwargs,
): ):
super(Roberta, self).__init__() super(Roberta, self).__init__()
if label_map: if label_map:
...@@ -63,23 +65,26 @@ class Roberta(nn.Layer): ...@@ -63,23 +65,26 @@ class Roberta(nn.Layer):
"current task name 'sequence_classification' was renamed to 'seq-cls', " "current task name 'sequence_classification' was renamed to 'seq-cls', "
"'sequence_classification' has been deprecated and will be removed in the future.", ) "'sequence_classification' has been deprecated and will be removed in the future.", )
if task == 'seq-cls': if task == 'seq-cls':
self.model = RobertaForSequenceClassification.from_pretrained( self.model = AutoModelForSequenceClassification.from_pretrained(pretrained_model_name_or_path='hfl/rbt3',
pretrained_model_name_or_path='rbt3', num_classes=self.num_classes, **kwargs) num_classes=self.num_classes,
**kwargs)
self.criterion = paddle.nn.loss.CrossEntropyLoss() self.criterion = paddle.nn.loss.CrossEntropyLoss()
self.metric = paddle.metric.Accuracy() self.metric = paddle.metric.Accuracy()
elif task == 'token-cls': elif task == 'token-cls':
self.model = RobertaForTokenClassification.from_pretrained( self.model = AutoModelForTokenClassification.from_pretrained(pretrained_model_name_or_path='hfl/rbt3',
pretrained_model_name_or_path='rbt3', num_classes=self.num_classes, **kwargs) num_classes=self.num_classes,
**kwargs)
self.criterion = paddle.nn.loss.CrossEntropyLoss() self.criterion = paddle.nn.loss.CrossEntropyLoss()
self.metric = ChunkEvaluator(label_list=[self.label_map[i] for i in sorted(self.label_map.keys())], suffix=suffix) self.metric = ChunkEvaluator(label_list=[self.label_map[i] for i in sorted(self.label_map.keys())],
suffix=suffix)
elif task == 'text-matching': elif task == 'text-matching':
self.model = RobertaModel.from_pretrained(pretrained_model_name_or_path='rbt3', **kwargs) self.model = AutoModel.from_pretrained(pretrained_model_name_or_path='hfl/rbt3', **kwargs)
self.dropout = paddle.nn.Dropout(0.1) self.dropout = paddle.nn.Dropout(0.1)
self.classifier = paddle.nn.Linear(self.model.config['hidden_size'] * 3, 2) self.classifier = paddle.nn.Linear(self.model.config['hidden_size'] * 3, 2)
self.criterion = paddle.nn.loss.CrossEntropyLoss() self.criterion = paddle.nn.loss.CrossEntropyLoss()
self.metric = paddle.metric.Accuracy() self.metric = paddle.metric.Accuracy()
elif task is None: elif task is None:
self.model = RobertaModel.from_pretrained(pretrained_model_name_or_path='rbt3', **kwargs) self.model = AutoModel.from_pretrained(pretrained_model_name_or_path='hfl/rbt3', **kwargs)
else: else:
raise RuntimeError("Unknown task {}, task should be one in {}".format(task, self._tasks_supported)) raise RuntimeError("Unknown task {}, task should be one in {}".format(task, self._tasks_supported))
...@@ -171,4 +176,4 @@ class Roberta(nn.Layer): ...@@ -171,4 +176,4 @@ class Roberta(nn.Layer):
""" """
Gets the tokenizer that is customized for this module. Gets the tokenizer that is customized for this module.
""" """
return RobertaTokenizer.from_pretrained(pretrained_model_name_or_path='rbt3', *args, **kwargs) return AutoTokenizer.from_pretrained(pretrained_model_name_or_path='hfl/rbt3', *args, **kwargs)
modules/text/language_model/rbtl3/README.md
浏览文件 @ 0b8f5660
```shell ```shell
$ hub install rbtl3==2.0.1 $ hub install rbtl3==2.0.2
``` ```
<p align="center"> <p align="center">
<img src="https://bj.bcebos.com/paddlehub/paddlehub-img/bert_network.png" hspace='10'/> <br /> <img src="https://bj.bcebos.com/paddlehub/paddlehub-img/bert_network.png" hspace='10'/> <br />
...@@ -85,7 +85,7 @@ label_map = {0: 'negative', 1: 'positive'} ...@@ -85,7 +85,7 @@ label_map = {0: 'negative', 1: 'positive'}
model = hub.Module( model = hub.Module(
name='rbtl3', name='rbtl3',
version='2.0.1', version='2.0.2',
task='seq-cls', task='seq-cls',
load_checkpoint='/path/to/parameters', load_checkpoint='/path/to/parameters',
label_map=label_map) label_map=label_map)
...@@ -163,3 +163,7 @@ paddlehub >= 2.0.0 ...@@ -163,3 +163,7 @@ paddlehub >= 2.0.0
* 2.0.1 * 2.0.1
增加文本匹配任务`text-matching` 增加文本匹配任务`text-matching`
* 2.0.2
更新预训练模型调用方法
modules/text/language_model/rbtl3/module.py
浏览文件 @ 0b8f5660
...@@ -11,17 +11,19 @@ ...@@ -11,17 +11,19 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
from typing import Dict
import os
import math import math
import os
from typing import Dict
import paddle import paddle
import paddle.nn as nn import paddle.nn as nn
import paddle.nn.functional as F import paddle.nn.functional as F
from paddlenlp.transformers.roberta.modeling import RobertaForSequenceClassification, RobertaForTokenClassification, RobertaModel
from paddlenlp.transformers.roberta.tokenizer import RobertaTokenizer
from paddlenlp.metrics import ChunkEvaluator from paddlenlp.metrics import ChunkEvaluator
from paddlenlp.transformers import AutoModel
from paddlenlp.transformers import AutoModelForSequenceClassification
from paddlenlp.transformers import AutoModelForTokenClassification
from paddlenlp.transformers import AutoTokenizer
from paddlehub.module.module import moduleinfo from paddlehub.module.module import moduleinfo
from paddlehub.module.nlp_module import TransformerModule from paddlehub.module.nlp_module import TransformerModule
from paddlehub.utils.log import logger from paddlehub.utils.log import logger
...@@ -29,7 +31,7 @@ from paddlehub.utils.log import logger ...@@ -29,7 +31,7 @@ from paddlehub.utils.log import logger
@moduleinfo( @moduleinfo(
name="rbtl3", name="rbtl3",
version="2.0.1", version="2.0.2",
summary="rbtl3, 3-layer, 1024-hidden, 16-heads, 61M parameters ", summary="rbtl3, 3-layer, 1024-hidden, 16-heads, 61M parameters ",
author="ymcui", author="ymcui",
author_email="ymcui@ir.hit.edu.cn", author_email="ymcui@ir.hit.edu.cn",
...@@ -42,13 +44,13 @@ class Roberta(nn.Layer): ...@@ -42,13 +44,13 @@ class Roberta(nn.Layer):
""" """
def __init__( def __init__(
self, self,
task: str = None, task: str = None,
load_checkpoint: str = None, load_checkpoint: str = None,
label_map: Dict = None, label_map: Dict = None,
num_classes: int = 2, num_classes: int = 2,
suffix: bool = False, suffix: bool = False,
**kwargs, **kwargs,
): ):
super(Roberta, self).__init__() super(Roberta, self).__init__()
if label_map: if label_map:
...@@ -63,23 +65,26 @@ class Roberta(nn.Layer): ...@@ -63,23 +65,26 @@ class Roberta(nn.Layer):
"current task name 'sequence_classification' was renamed to 'seq-cls', " "current task name 'sequence_classification' was renamed to 'seq-cls', "
"'sequence_classification' has been deprecated and will be removed in the future.", ) "'sequence_classification' has been deprecated and will be removed in the future.", )
if task == 'seq-cls': if task == 'seq-cls':
self.model = RobertaForSequenceClassification.from_pretrained( self.model = AutoModelForSequenceClassification.from_pretrained(pretrained_model_name_or_path='hfl/rbtl3',
pretrained_model_name_or_path='rbtl3', num_classes=self.num_classes, **kwargs) num_classes=self.num_classes,
**kwargs)
self.criterion = paddle.nn.loss.CrossEntropyLoss() self.criterion = paddle.nn.loss.CrossEntropyLoss()
self.metric = paddle.metric.Accuracy() self.metric = paddle.metric.Accuracy()
elif task == 'token-cls': elif task == 'token-cls':
self.model = RobertaForTokenClassification.from_pretrained( self.model = AutoModelForTokenClassification.from_pretrained(pretrained_model_name_or_path='hfl/rbtl3',
pretrained_model_name_or_path='rbtl3', num_classes=self.num_classes, **kwargs) num_classes=self.num_classes,
**kwargs)
self.criterion = paddle.nn.loss.CrossEntropyLoss() self.criterion = paddle.nn.loss.CrossEntropyLoss()
self.metric = ChunkEvaluator(label_list=[self.label_map[i] for i in sorted(self.label_map.keys())], suffix=suffix) self.metric = ChunkEvaluator(label_list=[self.label_map[i] for i in sorted(self.label_map.keys())],
suffix=suffix)
elif task == 'text-matching': elif task == 'text-matching':
self.model = RobertaModel.from_pretrained(pretrained_model_name_or_path='rbtl3', **kwargs) self.model = AutoModel.from_pretrained(pretrained_model_name_or_path='hfl/rbtl3', **kwargs)
self.dropout = paddle.nn.Dropout(0.1) self.dropout = paddle.nn.Dropout(0.1)
self.classifier = paddle.nn.Linear(self.model.config['hidden_size'] * 3, 2) self.classifier = paddle.nn.Linear(self.model.config['hidden_size'] * 3, 2)
self.criterion = paddle.nn.loss.CrossEntropyLoss() self.criterion = paddle.nn.loss.CrossEntropyLoss()
self.metric = paddle.metric.Accuracy() self.metric = paddle.metric.Accuracy()
elif task is None: elif task is None:
self.model = RobertaModel.from_pretrained(pretrained_model_name_or_path='rbtl3', **kwargs) self.model = AutoModel.from_pretrained(pretrained_model_name_or_path='hfl/rbtl3', **kwargs)
else: else:
raise RuntimeError("Unknown task {}, task should be one in {}".format(task, self._tasks_supported)) raise RuntimeError("Unknown task {}, task should be one in {}".format(task, self._tasks_supported))
...@@ -171,4 +176,4 @@ class Roberta(nn.Layer): ...@@ -171,4 +176,4 @@ class Roberta(nn.Layer):
""" """
Gets the tokenizer that is customized for this module. Gets the tokenizer that is customized for this module.
""" """
return RobertaTokenizer.from_pretrained(pretrained_model_name_or_path='rbtl3', *args, **kwargs) return AutoTokenizer.from_pretrained(pretrained_model_name_or_path='hfl/rbtl3', *args, **kwargs)
modules/text/language_model/roberta-wwm-ext-large/README.md
浏览文件 @ 0b8f5660
# roberta-wwm-ext-large # roberta-wwm-ext-large
|模型名称|roberta-wwm-ext-large| |模型名称|roberta-wwm-ext-large|
| :--- | :---: | | :--- | :---: |
|类别|文本-语义模型| |类别|文本-语义模型|
|网络|roberta-wwm-ext-large| |网络|roberta-wwm-ext-large|
|数据集|百度自建数据集| |数据集|百度自建数据集|
...@@ -51,7 +51,7 @@ label_map = {0: 'negative', 1: 'positive'} ...@@ -51,7 +51,7 @@ label_map = {0: 'negative', 1: 'positive'}
model = hub.Module( model = hub.Module(
name='roberta-wwm-ext-large', name='roberta-wwm-ext-large',
version='2.0.2', version='2.0.3',
task='seq-cls', task='seq-cls',
load_checkpoint='/path/to/parameters', load_checkpoint='/path/to/parameters',
label_map=label_map) label_map=label_map)
...@@ -181,6 +181,10 @@ for idx, text in enumerate(data): ...@@ -181,6 +181,10 @@ for idx, text in enumerate(data):
* 2.0.2 * 2.0.2
增加文本匹配任务`text-matching` 增加文本匹配任务`text-matching`
* 2.0.3
更新预训练模型调用方法
```shell ```shell
$ hub install roberta-wwm-ext-large==2.0.2 $ hub install roberta-wwm-ext==2.0.3
``` ```
modules/text/language_model/roberta-wwm-ext-large/module.py
浏览文件 @ 0b8f5660
...@@ -11,17 +11,19 @@ ...@@ -11,17 +11,19 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
from typing import Dict
import os
import math import math
import os
from typing import Dict
import paddle import paddle
import paddle.nn as nn import paddle.nn as nn
import paddle.nn.functional as F import paddle.nn.functional as F
from paddlenlp.transformers.roberta.modeling import RobertaForSequenceClassification, RobertaForTokenClassification, RobertaModel
from paddlenlp.transformers.roberta.tokenizer import RobertaTokenizer
from paddlenlp.metrics import ChunkEvaluator from paddlenlp.metrics import ChunkEvaluator
from paddlenlp.transformers import AutoModel
from paddlenlp.transformers import AutoModelForSequenceClassification
from paddlenlp.transformers import AutoModelForTokenClassification
from paddlenlp.transformers import AutoTokenizer
from paddlehub.module.module import moduleinfo from paddlehub.module.module import moduleinfo
from paddlehub.module.nlp_module import TransformerModule from paddlehub.module.nlp_module import TransformerModule
from paddlehub.utils.log import logger from paddlehub.utils.log import logger
...@@ -29,7 +31,7 @@ from paddlehub.utils.log import logger ...@@ -29,7 +31,7 @@ from paddlehub.utils.log import logger
@moduleinfo( @moduleinfo(
name="roberta-wwm-ext-large", name="roberta-wwm-ext-large",
version="2.0.2", version="2.0.3",
summary= summary=
"chinese-roberta-wwm-ext-large, 24-layer, 1024-hidden, 16-heads, 340M parameters. The module is executed as paddle.dygraph.", "chinese-roberta-wwm-ext-large, 24-layer, 1024-hidden, 16-heads, 340M parameters. The module is executed as paddle.dygraph.",
author="ymcui", author="ymcui",
...@@ -43,13 +45,13 @@ class Roberta(nn.Layer): ...@@ -43,13 +45,13 @@ class Roberta(nn.Layer):
""" """
def __init__( def __init__(
self, self,
task: str = None, task: str = None,
load_checkpoint: str = None, load_checkpoint: str = None,
label_map: Dict = None, label_map: Dict = None,
num_classes: int = 2, num_classes: int = 2,
suffix: bool = False, suffix: bool = False,
**kwargs, **kwargs,
): ):
super(Roberta, self).__init__() super(Roberta, self).__init__()
if label_map: if label_map:
...@@ -64,23 +66,24 @@ class Roberta(nn.Layer): ...@@ -64,23 +66,24 @@ class Roberta(nn.Layer):
"current task name 'sequence_classification' was renamed to 'seq-cls', " "current task name 'sequence_classification' was renamed to 'seq-cls', "
"'sequence_classification' has been deprecated and will be removed in the future.", ) "'sequence_classification' has been deprecated and will be removed in the future.", )
if task == 'seq-cls': if task == 'seq-cls':
self.model = RobertaForSequenceClassification.from_pretrained( self.model = AutoModelForSequenceClassification.from_pretrained(
pretrained_model_name_or_path='roberta-wwm-ext-large', num_classes=self.num_classes, **kwargs) pretrained_model_name_or_path='hfl/roberta-wwm-ext-large', num_classes=self.num_classes, **kwargs)
self.criterion = paddle.nn.loss.CrossEntropyLoss() self.criterion = paddle.nn.loss.CrossEntropyLoss()
self.metric = paddle.metric.Accuracy() self.metric = paddle.metric.Accuracy()
elif task == 'token-cls': elif task == 'token-cls':
self.model = RobertaForTokenClassification.from_pretrained( self.model = AutoModelForTokenClassification.from_pretrained(
pretrained_model_name_or_path='roberta-wwm-ext-large', num_classes=self.num_classes, **kwargs) pretrained_model_name_or_path='hfl/roberta-wwm-ext-large', num_classes=self.num_classes, **kwargs)
self.criterion = paddle.nn.loss.CrossEntropyLoss() self.criterion = paddle.nn.loss.CrossEntropyLoss()
self.metric = ChunkEvaluator(label_list=[self.label_map[i] for i in sorted(self.label_map.keys())], suffix=suffix) self.metric = ChunkEvaluator(label_list=[self.label_map[i] for i in sorted(self.label_map.keys())],
suffix=suffix)
elif task == 'text-matching': elif task == 'text-matching':
self.model = RobertaModel.from_pretrained(pretrained_model_name_or_path='roberta-wwm-ext-large', **kwargs) self.model = AutoModel.from_pretrained(pretrained_model_name_or_path='hfl/roberta-wwm-ext-large', **kwargs)
self.dropout = paddle.nn.Dropout(0.1) self.dropout = paddle.nn.Dropout(0.1)
self.classifier = paddle.nn.Linear(self.model.config['hidden_size'] * 3, 2) self.classifier = paddle.nn.Linear(self.model.config['hidden_size'] * 3, 2)
self.criterion = paddle.nn.loss.CrossEntropyLoss() self.criterion = paddle.nn.loss.CrossEntropyLoss()
self.metric = paddle.metric.Accuracy() self.metric = paddle.metric.Accuracy()
elif task is None: elif task is None:
self.model = RobertaModel.from_pretrained(pretrained_model_name_or_path='roberta-wwm-ext-large', **kwargs) self.model = AutoModel.from_pretrained(pretrained_model_name_or_path='hfl/roberta-wwm-ext-large', **kwargs)
else: else:
raise RuntimeError("Unknown task {}, task should be one in {}".format(task, self._tasks_supported)) raise RuntimeError("Unknown task {}, task should be one in {}".format(task, self._tasks_supported))
...@@ -172,4 +175,4 @@ class Roberta(nn.Layer): ...@@ -172,4 +175,4 @@ class Roberta(nn.Layer):
""" """
Gets the tokenizer that is customized for this module. Gets the tokenizer that is customized for this module.
""" """
return RobertaTokenizer.from_pretrained(pretrained_model_name_or_path='roberta-wwm-ext-large', *args, **kwargs) return AutoTokenizer.from_pretrained(pretrained_model_name_or_path='hfl/roberta-wwm-ext-large', *args, **kwargs)
modules/text/language_model/roberta-wwm-ext/README.md
浏览文件 @ 0b8f5660
# roberta-wwm-ext # roberta-wwm-ext
|模型名称|roberta-wwm-ext| |模型名称|roberta-wwm-ext|
| :--- | :---: | | :--- | :---: |
|类别|文本-语义模型| |类别|文本-语义模型|
|网络|roberta-wwm-ext| |网络|roberta-wwm-ext|
|数据集|百度自建数据集| |数据集|百度自建数据集|
...@@ -51,7 +51,7 @@ label_map = {0: 'negative', 1: 'positive'} ...@@ -51,7 +51,7 @@ label_map = {0: 'negative', 1: 'positive'}
model = hub.Module( model = hub.Module(
name='roberta-wwm-ext', name='roberta-wwm-ext',
version='2.0.2', version='2.0.3',
task='seq-cls', task='seq-cls',
load_checkpoint='/path/to/parameters', load_checkpoint='/path/to/parameters',
label_map=label_map) label_map=label_map)
...@@ -181,6 +181,10 @@ for idx, text in enumerate(data): ...@@ -181,6 +181,10 @@ for idx, text in enumerate(data):
* 2.0.2 * 2.0.2
增加文本匹配任务`text-matching` 增加文本匹配任务`text-matching`
* 2.0.3
更新预训练模型调用方法
```shell ```shell
$ hub install roberta-wwm-ext==2.0.2 $ hub install roberta-wwm-ext==2.0.3
``` ```
modules/text/language_model/roberta-wwm-ext/module.py
浏览文件 @ 0b8f5660
...@@ -11,17 +11,19 @@ ...@@ -11,17 +11,19 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
from typing import Dict
import os
import math import math
import os
from typing import Dict
import paddle import paddle
import paddle.nn as nn import paddle.nn as nn
import paddle.nn.functional as F import paddle.nn.functional as F
from paddlenlp.transformers.roberta.modeling import RobertaForSequenceClassification, RobertaForTokenClassification, RobertaModel
from paddlenlp.transformers.roberta.tokenizer import RobertaTokenizer
from paddlenlp.metrics import ChunkEvaluator from paddlenlp.metrics import ChunkEvaluator
from paddlenlp.transformers import AutoModel
from paddlenlp.transformers import AutoModelForSequenceClassification
from paddlenlp.transformers import AutoModelForTokenClassification
from paddlenlp.transformers import AutoTokenizer
from paddlehub.module.module import moduleinfo from paddlehub.module.module import moduleinfo
from paddlehub.module.nlp_module import TransformerModule from paddlehub.module.nlp_module import TransformerModule
from paddlehub.utils.log import logger from paddlehub.utils.log import logger
...@@ -29,7 +31,7 @@ from paddlehub.utils.log import logger ...@@ -29,7 +31,7 @@ from paddlehub.utils.log import logger
@moduleinfo( @moduleinfo(
name="roberta-wwm-ext", name="roberta-wwm-ext",
version="2.0.2", version="2.0.3",
summary= summary=
"chinese-roberta-wwm-ext, 12-layer, 768-hidden, 12-heads, 110M parameters. The module is executed as paddle.dygraph.", "chinese-roberta-wwm-ext, 12-layer, 768-hidden, 12-heads, 110M parameters. The module is executed as paddle.dygraph.",
author="ymcui", author="ymcui",
...@@ -43,13 +45,13 @@ class Roberta(nn.Layer): ...@@ -43,13 +45,13 @@ class Roberta(nn.Layer):
""" """
def __init__( def __init__(
self, self,
task: str = None, task: str = None,
load_checkpoint: str = None, load_checkpoint: str = None,
label_map: Dict = None, label_map: Dict = None,
num_classes: int = 2, num_classes: int = 2,
suffix: bool = False, suffix: bool = False,
**kwargs, **kwargs,
): ):
super(Roberta, self).__init__() super(Roberta, self).__init__()
if label_map: if label_map:
...@@ -64,23 +66,24 @@ class Roberta(nn.Layer): ...@@ -64,23 +66,24 @@ class Roberta(nn.Layer):
"current task name 'sequence_classification' was renamed to 'seq-cls', " "current task name 'sequence_classification' was renamed to 'seq-cls', "
"'sequence_classification' has been deprecated and will be removed in the future.", ) "'sequence_classification' has been deprecated and will be removed in the future.", )
if task == 'seq-cls': if task == 'seq-cls':
self.model = RobertaForSequenceClassification.from_pretrained( self.model = AutoModelForSequenceClassification.from_pretrained(
pretrained_model_name_or_path='roberta-wwm-ext', num_classes=self.num_classes, **kwargs) pretrained_model_name_or_path='hfl/roberta-wwm-ext', num_classes=self.num_classes, **kwargs)
self.criterion = paddle.nn.loss.CrossEntropyLoss() self.criterion = paddle.nn.loss.CrossEntropyLoss()
self.metric = paddle.metric.Accuracy() self.metric = paddle.metric.Accuracy()
elif task == 'token-cls': elif task == 'token-cls':
self.model = RobertaForTokenClassification.from_pretrained( self.model = AutoModelForTokenClassification.from_pretrained(
pretrained_model_name_or_path='roberta-wwm-ext', num_classes=self.num_classes, **kwargs) pretrained_model_name_or_path='hfl/roberta-wwm-ext', num_classes=self.num_classes, **kwargs)
self.criterion = paddle.nn.loss.CrossEntropyLoss() self.criterion = paddle.nn.loss.CrossEntropyLoss()
self.metric = ChunkEvaluator(label_list=[self.label_map[i] for i in sorted(self.label_map.keys())], suffix=suffix) self.metric = ChunkEvaluator(label_list=[self.label_map[i] for i in sorted(self.label_map.keys())],
suffix=suffix)
elif task == 'text-matching': elif task == 'text-matching':
self.model = RobertaModel.from_pretrained(pretrained_model_name_or_path='roberta-wwm-ext', **kwargs) self.model = AutoModel.from_pretrained(pretrained_model_name_or_path='hfl/roberta-wwm-ext', **kwargs)
self.dropout = paddle.nn.Dropout(0.1) self.dropout = paddle.nn.Dropout(0.1)
self.classifier = paddle.nn.Linear(self.model.config['hidden_size'] * 3, 2) self.classifier = paddle.nn.Linear(self.model.config['hidden_size'] * 3, 2)
self.criterion = paddle.nn.loss.CrossEntropyLoss() self.criterion = paddle.nn.loss.CrossEntropyLoss()
self.metric = paddle.metric.Accuracy() self.metric = paddle.metric.Accuracy()
elif task is None: elif task is None:
self.model = RobertaModel.from_pretrained(pretrained_model_name_or_path='roberta-wwm-ext', **kwargs) self.model = AutoModel.from_pretrained(pretrained_model_name_or_path='hfl/roberta-wwm-ext', **kwargs)
else: else:
raise RuntimeError("Unknown task {}, task should be one in {}".format(task, self._tasks_supported)) raise RuntimeError("Unknown task {}, task should be one in {}".format(task, self._tasks_supported))
...@@ -172,4 +175,4 @@ class Roberta(nn.Layer): ...@@ -172,4 +175,4 @@ class Roberta(nn.Layer):
""" """
Gets the tokenizer that is customized for this module. Gets the tokenizer that is customized for this module.
""" """
return RobertaTokenizer.from_pretrained(pretrained_model_name_or_path='roberta-wwm-ext', *args, **kwargs) return AutoTokenizer.from_pretrained(pretrained_model_name_or_path='hfl/roberta-wwm-ext', *args, **kwargs)
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