English | 简体中文
Image (212) | Text (130) | Audio (15) | Video (8) | Industrial Application (1) |
---|---|---|---|---|
Image Classification (108) | Text Generation (17) | Voice Cloning (2) | Video Classification (5) | Meter Detection (1) |
Image Generation (26) | Word Embedding (62) | Text to Speech (5) | Video Editing (1) | - |
Keypoint Detection (5) | Machine Translation (2) | Automatic Speech Recognition (5) | Multiple Object tracking (2) | - |
Semantic Segmentation (25) | Language Model (30) | Audio Classification (3) | - | - |
Face Detection (7) | Sentiment Analysis (7) | - | - | - |
Text Recognition (17) | Syntactic Analysis (1) | - | - | - |
Image Editing (8) | Simultaneous Translation (5) | - | - | - |
Instance Segmentation (1) | Lexical Analysis (2) | - | - | - |
Object Detection (13) | Punctuation Restoration (1) | - | - | - |
Depth Estimation (2) | Text Review (3) | - | - | - |
module | Network | Dataset | Introduction | Hugging Face Spaces |
---|---|---|---|---|
DriverStatusRecognition | MobileNetV3_small_ssld | 分心司机检测数据集 | ||
mobilenet_v2_animals | MobileNet_v2 | 百度自建动物数据集 | ||
repvgg_a1_imagenet | RepVGG | ImageNet-2012 | ||
repvgg_a0_imagenet | RepVGG | ImageNet-2012 | ||
resnext152_32x4d_imagenet | ResNeXt | ImageNet-2012 | ||
resnet_v2_152_imagenet | ResNet V2 | ImageNet-2012 | ||
resnet50_vd_animals | ResNet50_vd | 百度自建动物数据集 | ||
food_classification | ResNet50_vd_ssld | 美食数据集 | ||
mobilenet_v3_large_imagenet_ssld | Mobilenet_v3_large | ImageNet-2012 | ||
resnext152_vd_32x4d_imagenet | ||||
ghostnet_x1_3_imagenet_ssld | GhostNet | ImageNet-2012 | ||
rexnet_1_5_imagenet | ReXNet | ImageNet-2012 | ||
resnext50_64x4d_imagenet | ResNeXt | ImageNet-2012 | ||
resnext101_64x4d_imagenet | ResNeXt | ImageNet-2012 | ||
efficientnetb0_imagenet | EfficientNet | ImageNet-2012 | ||
efficientnetb1_imagenet | EfficientNet | ImageNet-2012 | ||
mobilenet_v2_imagenet_ssld | Mobilenet_v2 | ImageNet-2012 | ||
resnet50_vd_dishes | ResNet50_vd | 百度自建菜品数据集 | ||
pnasnet_imagenet | PNASNet | ImageNet-2012 | ||
rexnet_2_0_imagenet | ReXNet | ImageNet-2012 | ||
SnakeIdentification | ResNet50_vd_ssld | 蛇种数据集 | ||
hrnet40_imagenet | HRNet | ImageNet-2012 | ||
resnet_v2_34_imagenet | ResNet V2 | ImageNet-2012 | ||
mobilenet_v2_dishes | MobileNet_v2 | 百度自建菜品数据集 | ||
resnext101_vd_32x4d_imagenet | ResNeXt | ImageNet-2012 | ||
repvgg_b2g4_imagenet | RepVGG | ImageNet-2012 | ||
fix_resnext101_32x48d_wsl_imagenet | ResNeXt | ImageNet-2012 | ||
vgg13_imagenet | VGG | ImageNet-2012 | ||
se_resnext101_32x4d_imagenet | SE_ResNeXt | ImageNet-2012 | ||
hrnet30_imagenet | HRNet | ImageNet-2012 | ||
ghostnet_x1_3_imagenet | GhostNet | ImageNet-2012 | ||
dpn107_imagenet | DPN | ImageNet-2012 | ||
densenet161_imagenet | DenseNet | ImageNet-2012 | ||
vgg19_imagenet | vgg19_imagenet | ImageNet-2012 | ||
mobilenet_v2_imagenet | Mobilenet_v2 | ImageNet-2012 | ||
resnet50_vd_10w | ResNet_vd | 百度自建数据集 | ||
resnet_v2_101_imagenet | ResNet V2 101 | ImageNet-2012 | ||
darknet53_imagenet | DarkNet | ImageNet-2012 | ||
se_resnext50_32x4d_imagenet | SE_ResNeXt | ImageNet-2012 | ||
se_hrnet64_imagenet_ssld | HRNet | ImageNet-2012 | ||
resnext101_32x16d_wsl | ResNeXt_wsl | ImageNet-2012 | ||
hrnet18_imagenet | HRNet | ImageNet-2012 | ||
spinalnet_res101_gemstone | resnet101 | gemstone | ||
densenet264_imagenet | DenseNet | ImageNet-2012 | ||
resnext50_vd_32x4d_imagenet | ResNeXt_vd | ImageNet-2012 | ||
SpinalNet_Gemstones | ||||
spinalnet_vgg16_gemstone | vgg16 | gemstone | ||
xception71_imagenet | Xception | ImageNet-2012 | ||
repvgg_b2_imagenet | RepVGG | ImageNet-2012 | ||
dpn68_imagenet | DPN | ImageNet-2012 | ||
alexnet_imagenet | AlexNet | ImageNet-2012 | ||
rexnet_1_3_imagenet | ReXNet | ImageNet-2012 | ||
hrnet64_imagenet | HRNet | ImageNet-2012 | ||
efficientnetb7_imagenet | EfficientNet | ImageNet-2012 | ||
efficientnetb0_small_imagenet | EfficientNet | ImageNet-2012 | ||
efficientnetb6_imagenet | EfficientNet | ImageNet-2012 | ||
hrnet48_imagenet | HRNet | ImageNet-2012 | ||
rexnet_3_0_imagenet | ReXNet | ImageNet-2012 | ||
shufflenet_v2_imagenet | ShuffleNet V2 | ImageNet-2012 | ||
ghostnet_x0_5_imagenet | GhostNet | ImageNet-2012 | ||
inception_v4_imagenet | Inception_V4 | ImageNet-2012 | ||
resnext101_vd_64x4d_imagenet | ResNeXt_vd | ImageNet-2012 | ||
densenet201_imagenet | DenseNet | ImageNet-2012 | ||
vgg16_imagenet | VGG | ImageNet-2012 | ||
mobilenet_v3_small_imagenet_ssld | Mobilenet_v3_Small | ImageNet-2012 | ||
hrnet18_imagenet_ssld | HRNet | ImageNet-2012 | ||
resnext152_64x4d_imagenet | ResNeXt | ImageNet-2012 | ||
efficientnetb3_imagenet | EfficientNet | ImageNet-2012 | ||
efficientnetb2_imagenet | EfficientNet | ImageNet-2012 | ||
repvgg_b1g4_imagenet | RepVGG | ImageNet-2012 | ||
resnext101_32x4d_imagenet | ResNeXt | ImageNet-2012 | ||
resnext50_32x4d_imagenet | ResNeXt | ImageNet-2012 | ||
repvgg_a2_imagenet | RepVGG | ImageNet-2012 | ||
resnext152_vd_64x4d_imagenet | ResNeXt_vd | ImageNet-2012 | ||
xception41_imagenet | Xception | ImageNet-2012 | ||
googlenet_imagenet | GoogleNet | ImageNet-2012 | ||
resnet50_vd_imagenet_ssld | ResNet_vd | ImageNet-2012 | ||
repvgg_b1_imagenet | RepVGG | ImageNet-2012 | ||
repvgg_b0_imagenet | RepVGG | ImageNet-2012 | ||
resnet_v2_50_imagenet | ResNet V2 | ImageNet-2012 | ||
rexnet_1_0_imagenet | ReXNet | ImageNet-2012 | ||
resnet_v2_18_imagenet | ResNet V2 | ImageNet-2012 | ||
resnext101_32x8d_wsl | ResNeXt_wsl | ImageNet-2012 | ||
efficientnetb4_imagenet | EfficientNet | ImageNet-2012 | ||
efficientnetb5_imagenet | EfficientNet | ImageNet-2012 | ||
repvgg_b1g2_imagenet | RepVGG | ImageNet-2012 | ||
resnext101_32x48d_wsl | ResNeXt_wsl | ImageNet-2012 | ||
resnet50_vd_wildanimals | ResNet_vd | IFAW 自建野生动物数据集 | ||
nasnet_imagenet | NASNet | ImageNet-2012 | ||
se_resnet18_vd_imagenet | ||||
spinalnet_res50_gemstone | resnet50 | gemstone | ||
resnext50_vd_64x4d_imagenet | ResNeXt_vd | ImageNet-2012 | ||
resnext101_32x32d_wsl | ResNeXt_wsl | ImageNet-2012 | ||
dpn131_imagenet | DPN | ImageNet-2012 | ||
xception65_imagenet | Xception | ImageNet-2012 | ||
repvgg_b3g4_imagenet | RepVGG | ImageNet-2012 | ||
marine_biometrics | ResNet50_vd_ssld | Fish4Knowledge | ||
res2net101_vd_26w_4s_imagenet | Res2Net | ImageNet-2012 | ||
dpn98_imagenet | DPN | ImageNet-2012 | ||
resnet18_vd_imagenet | ResNet_vd | ImageNet-2012 | ||
densenet121_imagenet | DenseNet | ImageNet-2012 | ||
vgg11_imagenet | VGG | ImageNet-2012 | ||
hrnet44_imagenet | HRNet | ImageNet-2012 | ||
densenet169_imagenet | DenseNet | ImageNet-2012 | ||
hrnet32_imagenet | HRNet | ImageNet-2012 | ||
dpn92_imagenet | DPN | ImageNet-2012 | ||
ghostnet_x1_0_imagenet | GhostNet | ImageNet-2012 | ||
hrnet48_imagenet_ssld | HRNet | ImageNet-2012 |
module | Network | Dataset | Introduction | Huggingface Spaces Demo |
---|---|---|---|---|
pixel2style2pixel | Pixel2Style2Pixel | - | 人脸转正 | |
stgan_bald | STGAN | CelebA | 秃头生成器 | |
styleganv2_editing | StyleGAN V2 | - | 人脸编辑 | |
wav2lip | wav2lip | LRS2 | 唇形生成 | |
attgan_celeba | AttGAN | Celeba | 人脸编辑 | |
cyclegan_cityscapes | CycleGAN | Cityscapes | 实景图和语义分割结果互相转换 | |
stargan_celeba | StarGAN | Celeba | 人脸编辑 | |
stgan_celeba | STGAN | Celeba | 人脸编辑 | |
ID_Photo_GEN | HRNet_W18 | - | 证件照生成 | |
Photo2Cartoon | U-GAT-IT | cartoon_data | 人脸卡通化 | |
U2Net_Portrait | U^2Net | - | 人脸素描化 | |
UGATIT_100w | U-GAT-IT | selfie2anime | 人脸动漫化 | |
UGATIT_83w | U-GAT-IT | selfie2anime | 人脸动漫化 | |
UGATIT_92w | U-GAT-IT | selfie2anime | 人脸动漫化 | |
animegan_v1_hayao_60 | AnimeGAN | The Wind Rises | 图像风格迁移-宫崎骏 | |
animegan_v2_hayao_64 | AnimeGAN | The Wind Rises | 图像风格迁移-宫崎骏 | |
animegan_v2_hayao_99 | AnimeGAN | The Wind Rises | 图像风格迁移-宫崎骏 | |
animegan_v2_paprika_54 | AnimeGAN | Paprika | 图像风格迁移-今敏 | |
animegan_v2_paprika_74 | AnimeGAN | Paprika | 图像风格迁移-今敏 | |
animegan_v2_paprika_97 | AnimeGAN | Paprika | 图像风格迁移-今敏 | |
animegan_v2_paprika_98 | AnimeGAN | Paprika | 图像风格迁移-今敏 | |
animegan_v2_shinkai_33 | AnimeGAN | Your Name, Weathering with you | 图像风格迁移-新海诚 | |
animegan_v2_shinkai_53 | AnimeGAN | Your Name, Weathering with you | 图像风格迁移-新海诚 | |
msgnet | msgnet | COCO2014 | ||
stylepro_artistic | StyleProNet | MS-COCO + WikiArt | 艺术风格迁移 | |
stylegan_ffhq | StyleGAN | FFHQ | 图像风格迁移 |
module | Network | Dataset | Introduction |
---|---|---|---|
face_landmark_localization | Face_Landmark | AFW/AFLW | 人脸关键点检测 |
hand_pose_localization | - | MPII, NZSL | 手部关键点检测 |
openpose_body_estimation | two-branch multi-stage CNN | MPII, COCO 2016 | 肢体关键点检测 |
human_pose_estimation_resnet50_mpii | Pose_Resnet50 | MPII | 人体骨骼关键点检测 |
openpose_hands_estimation | - | MPII, NZSL | 手部关键点检测 |
module | Network | Dataset | Introduction |
---|---|---|---|
deeplabv3p_xception65_humanseg | deeplabv3p | 百度自建数据集 | 人像分割 |
humanseg_server | deeplabv3p | 百度自建数据集 | 人像分割 |
humanseg_mobile | hrnet | 百度自建数据集 | 人像分割-移动端前置摄像头 |
humanseg_lite | shufflenet | 百度自建数据集 | 轻量级人像分割-移动端实时 |
ExtremeC3_Portrait_Segmentation | ExtremeC3 | EG1800, Baidu fashion dataset | 轻量化人像分割 |
SINet_Portrait_Segmentation | SINet | EG1800, Baidu fashion dataset | 轻量化人像分割 |
FCN_HRNet_W18_Face_Seg | FCN_HRNet_W18 | - | 人像分割 |
ace2p | ACE2P | LIP | 人体解析 |
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_lung | U-NET+ | 连心医疗授权脱敏数据集 | 肺炎CT影像分析 |
ocrnet_hrnetw18_voc | ocrnet, hrnet | PascalVoc2012 | |
U2Net | U^2Net | - | 图像前景背景分割 |
U2Netp | U^2Net | - | 图像前景背景分割 |
Extract_Line_Draft | UNet | Pixiv | 线稿提取 |
unet_cityscapes | UNet | cityscapes | |
ocrnet_hrnetw18_cityscapes | ocrnet_hrnetw18 | cityscapes | |
hardnet_cityscapes | hardnet | cityscapes | |
fcn_hrnetw48_voc | fcn_hrnetw48 | PascalVoc2012 | |
fcn_hrnetw48_cityscapes | fcn_hrnetw48 | cityscapes | |
fcn_hrnetw18_voc | fcn_hrnetw18 | PascalVoc2012 | |
fcn_hrnetw18_cityscapes | fcn_hrnetw18 | cityscapes | |
fastscnn_cityscapes | fastscnn | cityscapes | |
deeplabv3p_resnet50_voc | deeplabv3p, resnet50 | PascalVoc2012 | |
deeplabv3p_resnet50_cityscapes | deeplabv3p, resnet50 | cityscapes | |
bisenetv2_cityscapes | bisenetv2 | cityscapes |
module | Network | Dataset | Introduction |
---|---|---|---|
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_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_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 |
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_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 |
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_face_detection | PyramidBox | WIDER FACE数据集 | 人脸检测 |
module | Network | Dataset | Introduction | Huggingface Spaces Demo |
---|---|---|---|---|
chinese_ocr_db_crnn_mobile | Differentiable Binarization+RCNN | icdar2015数据集 | 中文文字识别 | |
chinese_text_detection_db_server | Differentiable Binarization | icdar2015数据集 | 中文文本检测 | |
chinese_ocr_db_crnn_server | Differentiable Binarization+RCNN | icdar2015数据集 | 中文文字识别 | |
Vehicle_License_Plate_Recognition | - | CCPD | 车牌识别 | |
chinese_cht_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 繁体中文文字识别 | |
japan_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 日文文字识别 | |
korean_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 韩文文字识别 | |
german_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 德文文字识别 | |
french_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 法文文字识别 | |
latin_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 拉丁文文字识别 | |
cyrillic_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 斯拉夫文文字识别 | |
multi_languages_ocr_db_crnn | Differentiable Binarization+RCNN | icdar2015数据集 | 多语言文字识别 | |
kannada_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 卡纳达文文字识别 | |
arabic_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 阿拉伯文文字识别 | |
telugu_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 泰卢固文文字识别 | |
devanagari_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 梵文文字识别 | |
tamil_ocr_db_crnn_mobile | Differentiable Binarization+CRNN | icdar2015数据集 | 泰米尔文文字识别 |
module | Network | Dataset | Introduction | Huggingface Spaces Demo |
---|---|---|---|---|
realsr | LP-KPN | RealSR dataset | 图像/视频超分-4倍 | |
deoldify | GAN | ILSVRC 2012 | 黑白照片/视频着色 | |
photo_restoration | 基于deoldify和realsr模型 | - | 老照片修复 | |
user_guided_colorization | siggraph | ILSVRC 2012 | 图像着色 | |
falsr_c | falsr_c | DIV2k | 轻量化超分-2倍 | |
dcscn | dcscn | DIV2k | 轻量化超分-2倍 | |
falsr_a | falsr_a | DIV2k | 轻量化超分-2倍 | |
falsr_b | falsr_b | DIV2k | 轻量化超分-2倍 |
module | Network | Dataset | Introduction |
---|---|---|---|
solov2 | - | COCO2014 | 实例分割 |
module | Network | Dataset | Introduction |
---|---|---|---|
faster_rcnn_resnet50_coco2017 | faster_rcnn | COCO2017 | |
ssd_vgg16_512_coco2017 | SSD | COCO2017 | |
faster_rcnn_resnet50_fpn_venus | faster_rcnn | 百度自建数据集 | 大规模通用目标检测 |
ssd_vgg16_300_coco2017 | |||
yolov3_resnet34_coco2017 | YOLOv3 | COCO2017 | |
yolov3_darknet53_pedestrian | YOLOv3 | 百度自建大规模行人数据集 | 行人检测 |
yolov3_mobilenet_v1_coco2017 | YOLOv3 | COCO2017 | |
ssd_mobilenet_v1_pascal | SSD | PASCAL VOC | |
faster_rcnn_resnet50_fpn_coco2017 | faster_rcnn | COCO2017 | |
yolov3_darknet53_coco2017 | YOLOv3 | COCO2017 | |
yolov3_darknet53_vehicles | YOLOv3 | 百度自建大规模车辆数据集 | 车辆检测 |
yolov3_darknet53_venus | YOLOv3 | 百度自建数据集 | 大规模通用检测 |
yolov3_resnet50_vd_coco2017 | YOLOv3 | COCO2017 |
module | Network | Dataset | Introduction | Huggingface Spaces Demo |
---|---|---|---|---|
MiDaS_Large | - | 3D Movies, WSVD, ReDWeb, MegaDepth | ||
MiDaS_Small | - | 3D Movies, WSVD, ReDWeb, MegaDepth, etc. |
module | Network | Dataset | Introduction |
---|---|---|---|
ernie_gen | ERNIE-GEN | - | 面向生成任务的预训练-微调框架 |
ernie_gen_poetry | ERNIE-GEN | 开源诗歌数据集 | 诗歌生成 |
ernie_gen_couplet | ERNIE-GEN | 开源对联数据集 | 对联生成 |
ernie_gen_lover_words | ERNIE-GEN | 网络情诗、情话数据 | 情话生成 |
ernie_tiny_couplet | Eernie_tiny | 开源对联数据集 | 对联生成 |
ernie_gen_acrostic_poetry | ERNIE-GEN | 开源诗歌数据集 | 藏头诗生成 |
Rumor_prediction | - | 新浪微博中文谣言数据 | 谣言预测 |
plato-mini | Unified Transformer | 十亿级别的中文对话数据 | 中文对话 |
plato2_en_large | plato2 | 开放域多轮数据集 | 超大规模生成式对话 |
plato2_en_base | plato2 | 开放域多轮数据集 | 超大规模生成式对话 |
CPM_LM | GPT-2 | 自建数据集 | 中文文本生成 |
unified_transformer-12L-cn | Unified Transformer | 千万级别中文会话数据 | 人机多轮对话 |
unified_transformer-12L-cn-luge | Unified Transformer | 千言对话数据集 | 人机多轮对话 |
reading_pictures_writing_poems | 多网络级联 | - | 看图写诗 |
GPT2_CPM_LM | 问答类文本生成 | ||
GPT2_Base_CN | 问答类文本生成 |
expand
module | Network | Dataset | Introduction |
---|---|---|---|
transformer_zh-en | Transformer | CWMT2021 | 中文译英文 |
transformer_en-de | Transformer | WMT14 EN-DE | 英文译德文 |
expand
module | Network | Dataset | Introduction |
---|---|---|---|
chinese_electra_small | |||
chinese_electra_base | |||
roberta-wwm-ext-large | roberta-wwm-ext-large | 百度自建数据集 | |
chinese-bert-wwm-ext | chinese-bert-wwm-ext | 百度自建数据集 | |
lda_webpage | LDA | 百度自建网页领域数据集 | |
lda_novel | |||
bert-base-multilingual-uncased | |||
rbt3 | |||
ernie_v2_eng_base | ernie_v2_eng_base | 百度自建数据集 | |
bert-base-multilingual-cased | |||
rbtl3 | |||
chinese-bert-wwm | chinese-bert-wwm | 百度自建数据集 | |
bert-large-uncased | |||
slda_novel | |||
slda_news | |||
electra_small | |||
slda_webpage | |||
bert-base-cased | |||
slda_weibo | |||
roberta-wwm-ext | roberta-wwm-ext | 百度自建数据集 | |
bert-base-uncased | |||
electra_large | |||
ernie | ernie-1.0 | 百度自建数据集 | |
simnet_bow | BOW | 百度自建数据集 | |
ernie_tiny | ernie_tiny | 百度自建数据集 | |
bert-base-chinese | bert-base-chinese | 百度自建数据集 | |
lda_news | LDA | 百度自建新闻领域数据集 | |
electra_base | |||
ernie_v2_eng_large | ernie_v2_eng_large | 百度自建数据集 | |
bert-large-cased |
module | Network | Dataset | Introduction | Huggingface Spaces Demo |
---|---|---|---|---|
ernie_skep_sentiment_analysis | SKEP | 百度自建数据集 | 句子级情感分析 | |
emotion_detection_textcnn | TextCNN | 百度自建数据集 | 对话情绪识别 | |
senta_bilstm | BiLSTM | 百度自建数据集 | 中文情感倾向分析 | |
senta_bow | BOW | 百度自建数据集 | 中文情感倾向分析 | |
senta_gru | GRU | 百度自建数据集 | 中文情感倾向分析 | |
senta_lstm | LSTM | 百度自建数据集 | 中文情感倾向分析 | |
senta_cnn | CNN | 百度自建数据集 | 中文情感倾向分析 |
module | Network | Dataset | Introduction |
---|---|---|---|
DDParser | Deep Biaffine Attention | 搜索query、网页文本、语音输入等数据 | 句法分析 |
module | Network | Dataset | Introduction |
---|---|---|---|
transformer_nist_wait_1 | transformer | NIST 2008-中英翻译数据集 | 中译英-wait-1策略 |
transformer_nist_wait_3 | transformer | NIST 2008-中英翻译数据集 | 中译英-wait-3策略 |
transformer_nist_wait_5 | transformer | NIST 2008-中英翻译数据集 | 中译英-wait-5策略 |
transformer_nist_wait_7 | transformer | NIST 2008-中英翻译数据集 | 中译英-wait-7策略 |
transformer_nist_wait_all | transformer | NIST 2008-中英翻译数据集 | 中译英-waitk=-1策略 |
module | Network | Dataset | Introduction | Huggingface Spaces Demo |
---|---|---|---|---|
jieba_paddle | BiGRU+CRF | 百度自建数据集 | jieba使用Paddle搭建的切词网络(双向GRU)。同时支持jieba的传统切词方法,如精确模式、全模式、搜索引擎模式等切词模式。 | |
lac | BiGRU+CRF | 百度自建数据集 | 百度自研联合的词法分析模型,能整体性地完成中文分词、词性标注、专名识别任务。在百度自建数据集上评测,LAC效果:Precision=88.0%,Recall=88.7%,F1-Score=88.4%。 |
module | Network | Dataset | Introduction |
---|---|---|---|
auto_punc | Ernie-1.0 | WuDaoCorpora 2.0 | 自动添加7种标点符号 |
module | Network | Dataset | Introduction |
---|---|---|---|
porn_detection_cnn | CNN | 百度自建数据集 | 色情检测,自动判别文本是否涉黄并给出相应的置信度,对文本中的色情描述、低俗交友、污秽文案进行识别 |
porn_detection_gru | GRU | 百度自建数据集 | 色情检测,自动判别文本是否涉黄并给出相应的置信度,对文本中的色情描述、低俗交友、污秽文案进行识别 |
porn_detection_lstm | LSTM | 百度自建数据集 | 色情检测,自动判别文本是否涉黄并给出相应的置信度,对文本中的色情描述、低俗交友、污秽文案进行识别 |
module | Network | Dataset | Introduction |
---|---|---|---|
ge2e_fastspeech2_pwgan | FastSpeech2 | AISHELL-3 | 中文语音克隆 |
lstm_tacotron2 | LSTM、Tacotron2、WaveFlow | AISHELL-3 | 中文语音克隆 |
module | Network | Dataset | Introduction |
---|---|---|---|
transformer_tts_ljspeech | Transformer | LJSpeech-1.1 | 英文语音合成 |
fastspeech_ljspeech | FastSpeech | LJSpeech-1.1 | 英文语音合成 |
fastspeech2_baker | FastSpeech2 | Chinese Standard Mandarin Speech Copus | 中文语音合成 |
fastspeech2_ljspeech | FastSpeech2 | LJSpeech-1.1 | 英文语音合成 |
deepvoice3_ljspeech | DeepVoice3 | LJSpeech-1.1 | 英文语音合成 |
module | Network | Dataset | Introduction |
---|---|---|---|
deepspeech2_aishell | DeepSpeech2 | AISHELL-1 | 中文语音识别 |
deepspeech2_librispeech | DeepSpeech2 | LibriSpeech | 英文语音识别 |
u2_conformer_aishell | Conformer | AISHELL-1 | 中文语音识别 |
u2_conformer_wenetspeech | Conformer | WenetSpeech | 中文语音识别 |
u2_conformer_librispeech | Conformer | LibriSpeech | 英文语音识别 |
module | Network | Dataset | Introduction |
---|---|---|---|
panns_cnn6 | PANNs | Google Audioset | 主要包含4个卷积层和2个全连接层,模型参数为4.5M。经过预训练后,可以用于提取音频的embbedding,维度是512 |
panns_cnn14 | PANNs | Google Audioset | 主要包含12个卷积层和2个全连接层,模型参数为79.6M。经过预训练后,可以用于提取音频的embbedding,维度是2048 |
panns_cnn10 | PANNs | Google Audioset | 主要包含8个卷积层和2个全连接层,模型参数为4.9M。经过预训练后,可以用于提取音频的embbedding,维度是512 |
module | Network | Dataset | Introduction |
---|---|---|---|
videotag_tsn_lstm | TSN + AttentionLSTM | 百度自建数据集 | 大规模短视频分类打标签 |
tsn_kinetics400 | TSN | Kinetics-400 | 视频分类 |
tsm_kinetics400 | TSM | Kinetics-400 | 视频分类 |
stnet_kinetics400 | StNet | Kinetics-400 | 视频分类 |
nonlocal_kinetics400 | Non-local | Kinetics-400 | 视频分类 |
module | Network | Dataset | Introduction |
---|---|---|---|
SkyAR | UNet | UNet | 视频换天 |
module | Network | Dataset | Introduction |
---|---|---|---|
fairmot_dla34 | CenterNet | Caltech Pedestrian+CityPersons+CUHK-SYSU+PRW+ETHZ+MOT17 | 实时多目标跟踪 |
jde_darknet53 | YOLOv3 | Caltech Pedestrian+CityPersons+CUHK-SYSU+PRW+ETHZ+MOT17 | 多目标跟踪-兼顾精度和速度 |
module | Network | Dataset | Introduction |
---|---|---|---|
WatermeterSegmentation | DeepLabV3 | 水表的数字表盘分割数据集 | 水表的数字表盘分割 |