English | 简体中文
- PaddleHub aims to provide developers with rich, high-quality, and directly usable pre-trained models.
- No need for deep learning background, you can use AI models quickly and enjoy the dividends of the artificial intelligence era.
- Covers 4 major categories of Image, Text, Audio, and Video, and supports one-click prediction, easy service deployment and transfer learning
- All models are OPEN SOURCE, FREE to download and use them in offline scenario.
- 2020.12.1: Release 2.0-beta1 version, migrate ERNIE, RoBERTa, BERT to dynamic graph mode. Add text classification fine-tune task based on large-scale pre-trained models.
- 2020.11.20: Release 2.0-beta version, fully migrate the dynamic graph programming mode, and upgrade the service deployment Serving capability; add 1 hand key point detection model, 12 image animation models, 3 image editing models, 3 speech synthesis models, syntax Analyzing one, the total number of pre-trained models reaches 【182】.
- 2020.10.09: Added 4 new OCR multi-language series models, 4 image editing models, and the total number of pre-trained models reached 【162】.
- 2020.09.27: 6 new text generation models and 1 image segmentation model were added, and the total number of pre-trained models reached 【154】.
- 2020.08.13: Released v1.8.1, added a segmentation model, and supports EMNLP2019-Sentence-BERT as a text matching task network. The total number of pre-training models reaches 【147】.
- 2020.07.29: Release v1.8.0, new AI couplets and AI writing poems, jieba word segmentation, LDA topic model, semantic similarity calculation, new target detection, short video classification model, ultra-lightweight Chinese and English OCR, new pedestrian detection, vehicle industrial-grade models such as detection and animal recognition support VisualDL visualization training, and the total number of pre-training models reaches 【135】.
- Abundant Pre-trained Models: 180+ pre-trained models covering the 4 major categories including Image, Text, Audio, and Video, all open source and free for download and offline usage.
- Quick Model Prediction: Model prediction can be realized through a few lines of scripts to quickly experience the model effect.
- Model As Service: A one-line command to build deep learning model API service deployment capabilities.
- Easy-to-use Transfer Learning: Just few lines of code you can complete the transfer-learning task like image classification and text classification based on high quality pre-trained models.
- Cross-platform: Can run on Linux, Windows, MacOS and other operating systems.
- Contain ultra-lightweight Chinese and English OCR models, high-precision Chinese and English, multilingual German, French, Japanese, Korean OCR recognition.
- Many thanks to CopyRight@PaddleOCR for the pre-trained models, you can try to train your models with PadddleOCR.
- Including face detection, mask face detection, multiple algorithms are optional.
- Many thanks to CopyRight@PaddleDetection for the pre-trained models, you can try to train your models with PadddleDetection.
- 4x super resolution effect, multiple super resolution models are optional.
- Colorization models can be used to repair old grayscale photos.
- Many thanks to CopyRight@PaddleGAN for the pre-trained models, you can try to train your models with PadddleGAN.
| SuperResolution | Restoration |
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- Pedestrian detection, vehicle detection, and more industrial-grade ultra-large-scale pretrained models are provided.
- Many thanks to CopyRight@PaddleDetection for the pre-trained models, you can try to train your models with PadddleDetection.
- Support body, face and hands key point detection for single or multiple person.
- Many thanks to CopyRight@openpose for the pre-trained models.
- High quality pixel-level portrait cutout model, ACE2P human body analysis world champion models are provided.
- Many thanks to CopyRight@PaddleSeg for the pre-trained models, you can try to train your models with PaddleSeg.
- Various models like animal classification, dish classification, wild animal product classification are available.
- Many thanks to CopyRight@PaddleClas for the pre-trained models, you can try to train your models with PadddleClas.
- AI poem writing, AI couplets, AI love words generation models are available.
- Many thanks to CopyRight@ERNIE for the pre-trained models, you can try to train your models with ERNIE.
- Excelent Chinese text segmentation, part-of-speech, named entity recognition model are provided by LAC@Baidu NLP.
- Leading Chinese syntactic analysis model are provided by DDParser@Baidu NLP.
- All SOTA Chinese sentiment analysis model released by Baidu NLP can be used just one-line of code.
- Text review model of Chinese pornographic text are available.
- TTS speech synthesis algorithm, multiple algorithms are available.
- Many thanks to CopyRight@Parakeet for the pre-trained models, you can try to train your models with Parakeet.
- Input:
Life was like a box of chocolates, you never know what you're gonna get. - The synthesis effect is as follows:
| deepvoice3 | fastspeech | transformer |
|---|---|---|
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- Short video classification trained via large-scale video datasets, supports 3000+ tag types prediction for short Form Videos.
- Many thanks to CopyRight@PaddleVideo for the pre-trained model, you can try to train your models with PaddleVideo.
Example: Input a short video of swimming, the algorithm can output the result of "swimming"
- All the above pre-trained models are all open source and free, and the number of models is continuously updated. Welcome ⭐Star⭐ to pay attention.
If you have any questions during the use of the model, you can join the official WeChat group to get more efficient questions and answers, and fully communicate with developers from all walks of life. We look forward to your joining.
- PIP Installation
- Quick Start
- Rich Pre-trained Models 182
- Boutique Featured Models
- Computer Vision 126
- Natural Language Processing 48
- Audio 3
- Video 5
- Deploy
- Advanced documentation
- Community
- License
- Contribution
The release of this project is certified by the Apache 2.0 license.
We welcome you to contribute code to PaddleHub, and thank you for your feedback.
- Many thanks to Austendeng for fixing the SequenceLabelReader
- Many thanks to cclauss optimizing travis-ci check
- Many thanks to 奇想天外，Contributed a demo of mask detection
- Many thanks to mhlwsk，Contributed the repair sequence annotation prediction demo
- Many thanks to zbp-xxxp，Contributed modules for viewing pictures and writing poems
- Many thanks to zbp-xxxp and 七年期限,Jointly contributed to the Mid-Autumn Festival Special Edition Module
- Many thanks to livingbody，Contributed models for style transfer based on PaddleHub's capabilities and Mid-Autumn Festival WeChat Mini Program