未验证 提交 3031a7c7 编写于 作者: Z Zeyu Chen 提交者: GitHub

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## Introduction ## Introduction
- PaddleHub aims to provide developers with rich, high-quality, and directly usable pre-trained models. - PaddleHub aims to provide developers with rich, high-quality, and directly usable pre-trained models.
- **【No need for deep learning background, no data and training process】**,you can use AI models quickly and enjoy the dividends of the artificial intelligence era. - **【No need for deep learning background, no data and training process】**,you can use AI models quickly and enjoy the dividends of the artificial intelligence era.
- Covers the four major categories of CV, NLP, Audio, and Video, and supports **one-click prediction**, **one-click service deployment** and **migration learning** - Covers 4 major categories of CV, NLP, Audio, and Video, and supports **one-click prediction**, **one-click service deployment** and **transfer learning**
- All models are open source download, **offline can run**. - All models are **OPEN SOURCE**, **FREE** for download and use in **offline scenario**.
**Recent updates** **Recent updates**
- 2020.12.1: Release 2.0-beta-1 version, migrate ERNIE, RoBERTa, BERT to dynamic graph mode. Add text classification fine-tuen task based on large-scale pre-trained models. - 2020.12.1: Release 2.0-beta-1 version, migrate ERNIE, RoBERTa, BERT to dynamic graph mode. Add text classification fine-tuen task based on large-scale pre-trained models.
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- 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】**. - 2020.10.09: 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】**. - 2020.09.27: 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】**. - 2020.08.13: 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 cutting, text data LDA, 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】**. - 2020.07.29: Release v1.8.0, new AI couplets and AI writing poems, jieba word cutting, text data LDA, 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](https://github.com/PaddlePaddle/VisualDL) visualization training, and the total number of pre-training models reaches **【135】**.
## Features ## Features
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- **【PIP installation 】**: Support PIP quick installation and use. - **【PIP installation 】**: Support PIP quick installation and use.
- **【Cross-platform Compatibility】**: Can run on Linux, Windows, MacOS and other operating systems. - **【Cross-platform Compatibility】**: Can run on Linux, Windows, MacOS and other operating systems.
## Visualization ## Visualization Demo
### Text Recognition ### Text Recognition
- Contains ultra-lightweight Chinese and English OCR models, high-precision Chinese and English, multilingual German, French, Japanese, Korean OCR recognition. - Contains ultra-lightweight Chinese and English OCR models, high-precision Chinese and English, multilingual German, French, Japanese, Korean OCR recognition.
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### Image Editing ### Image Editing
- 4 times super resolution effect, multiple super resolution models are optional. - 4x super resolution effect, multiple super resolution models are optional.
- Colorization models can be used to repair old grayscale photos. - Colorization models can be used to repair old grayscale photos.
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### Object Detection ### Object Detection
- Including pedestrian detection, vehicle detection, and more industrial-grade ultra-large-scale pretrained models are optional. - Pedestrian detection, vehicle detection, and more industrial-grade ultra-large-scale pretrained models are provided.
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<img src="./docs/imgs/Readme_Related/Image_ObjectDetection_Pedestrian_Vehicle.gif" width = "642" height = "400" /> <img src="./docs/imgs/Readme_Related/Image_ObjectDetection_Pedestrian_Vehicle.gif" width = "642" height = "400" />
</div> </div>
### Key Point Detection ### Key Point Detection
- Supports body, face and hands key point detection in single or multiple person. - Supports body, face and hands key point detection for single or multiple person.
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<img src="./docs/imgs/Readme_Related/Image_keypoint.gif" width = "458" height = "400" /> <img src="./docs/imgs/Readme_Related/Image_keypoint.gif" width = "458" height = "400" />
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</div> </div>
### Video Classification ### Video Classification
- Contains short video classification, supports 3000+ tag types, can output TOP-K tags, and multiple algorithms are optional. - Short video classification trained via large-scale video dataset, supports 3000+ tag types prediction.
- `Example: Input a short video of swimming, the algorithm can output the result of "swimming"` - `Example: Input a short video of swimming, the algorithm can output the result of "swimming"`
<div align="center"> <div align="center">
<img src="./docs/imgs/Readme_Related/Text_Video.gif" width = "400" height = "400" /> <img src="./docs/imgs/Readme_Related/Text_Video.gif" width = "400" height = "400" />
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- Quick Start - Quick Start
- [Command Line](./docs/docs_en/quick_experience/cmd_quick_run_en.md) - [Command Line](./docs/docs_en/quick_experience/cmd_quick_run_en.md)
- [Python API](./docs/docs_en/quick_experience/python_use_hub_en.md) - [Python API](./docs/docs_en/quick_experience/python_use_hub_en.md)
- [More_Demos](./docs/docs_en/quick_experience/more_demos_en.md) - [More Demos](./docs/docs_en/quick_experience/more_demos_en.md)
- Rich Pre-trained Models 182 - Rich Pre-trained Models 182
- [Boutique Featured Models](./docs/docs_en/figures_en.md) - [Boutique Featured Models](./docs/docs_en/figures_en.md)
- Computer Vision 126 - Computer Vision 126
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- Deploy - Deploy
- [Local Inference Deployment](./docs/docs_en/quick_experience/python_use_hub_en.md) - [Local Inference Deployment](./docs/docs_en/quick_experience/python_use_hub_en.md)
- [One Line of Code Service deployment](./docs/docs_en/tutorial/serving_en.md) - [One Line of Code Service deployment](./docs/docs_en/tutorial/serving_en.md)
- [Mobile Lite Deployment (link to Lite tutorial)](https://paddle-lite.readthedocs.io/zh/latest/quick_start/tutorial.html) - [Mobile Device Deployment](https://paddle-lite.readthedocs.io/zh/latest/quick_start/tutorial.html)
- Advanced documentation - Advanced documentation
- [Command_Line](./docs/docs_en/tutorial/cmdintro_en.md) - [Command Line Interface Usage](./docs/docs_en/tutorial/cmdintro_en.md)
- [How to Load Data](./docs/docs_en/tutorial/how_to_load_data_en.md) - [How to Load Customized Dataset](./docs/docs_en/tutorial/how_to_load_data_en.md)
- Community - Community
- [Join the technical group](#Welcome_joinus) - [Join Technical Group](#Welcome_joinus)
- [Contribute pre-trained models](./docs/docs_en/contribution/contri_pretrained_model_en.md) - [Contribute Pre-trained Models](./docs/docs_en/contribution/contri_pretrained_model_en.md)
- [Contribute code](./docs/docs_en/contribution/contri_pr_en.md) - [Contribute Code](./docs/docs_en/contribution/contri_pr_en.md)
- [License](#License) - [License](#License)
- [Contribution](#Contribution) - [Contribution](#Contribution)
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