/PaddleX

PaddlePaddle End-to-End Development Toolkit（『飞桨』深度学习全流程开发工具）

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PaddleX

PaddleX -- PaddlePaddle End-to-End Development Toolkit, enables developers to implement real industry projects in a low-code form quickly

License Version python version support os QQGroup

🤗 PaddleX integrated the abilities of Image classification, Object detection, Semantic segmentation, and Instance segmentation in the Paddle CV toolkits, and get through the whole-process development from Data preparation and Model training and optimization to Multi-end deployment. At the same time, PaddleX provides Succinct APIs and a Graphical Ueser Interface. Developers can quickly complete the end-to-end process development of the Paddle in a form of low-code without installing different libraries.

🏭 PaddleX has been validated in a dozen of industry application scenarios such as Quality Inspection, Security, Patrol Inspection, Remote Sensing, Retail, Medical etc.. In addition, it provides a wealth of case practice tutorials, to help developer could apply to actual cases easily.

❤️ You can go to Complete PaddleX Online Documentation Contents for complete tutorial with the format of Read the Doc and better reading experience​ ❤️

Installation

PaddleX has two development modes to meet different needs of users:

1.Python development mode:

The design of PaddleX Python API taking into account of comprehensive functions, development flexibility, and integration convenience, giving developers the smoothest deep learning development experience.

Pre-dependence

  • paddlepaddle >= 1.8.4
  • python >= 3.6
  • cython
  • pycocotools
pip install paddlex -i https://mirror.baidu.com/pypi/simple

Please refer to the PaddleX installation for detailed installation method.

  1. Padlde GUI(Graphical Ueser Interface) mode:

It's a all-in-one client enable develops could implement deep learning projects without code.

Product Module Description

  • Data preparation: Compatible with common data protocols such as ImageNet, VOC, COCO, and seamlessly interconnecting with Labelme, Colabeler, and EasyData intelligent data service platform, to help developers to quickly complete data preparations.
  • Data pre-processing and enhancement: Provides a minimalist image pre-processing and enhancement method--Transforms. Adapts imgaug which is a powerful image enhancement library, so that PaddleX could supports Hundreds of data enhancement strategies, which makes developers quickly alleviate the situation of traing with small sample dataset.
  • Model training: PaddleX integrates PaddleClas, PaddleDetection, and PaddleSeg etcs. So it provides a large number of selected, industry-proven, high-quality pre-trained models, enabling developers to achieve the industry requirements much more quickly.
  • Model tuning: Model-interpretability module and VisualDL visual analysis tool are integrated as well. It allows developers to understand the model's feature extraction region and the change of the training process parameters more intuitively , so as to quickly optimize the model.
  • Multi-End Secure Deployment: The built-in model compression tool-- PaddleSlim and Model Encryption Deployment Module, are seamlessly interconnected with native prediction library Paddle Inference and Multi-platform high performance deep learning inference engine-- Paddle Lite , to enable developers to quickly implement multi-end, high-performance, secure deployments of the model.

Full Documentation and API Description

Examples of Online Projects

To get developers up to speed with the PaddleX API, we've created a complete series of sample tutorials that you can run PaddleX projects online through the AIStudio quickly.

Full Process Industry Applications:star:

（continue to be updated）

❓FAQ❓

Communication and Feedback

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Release Note

Complete Release Note

  • 2020.12.20 v1.3.0
  • 2020.09.05 v1.2.0
  • 2020.07.13 v1.1.0
  • 2020.07.12 v1.0.8
  • 2020.05.20 v1.0.0

🤗 Contribution 🤗

You are welcomed to contribute codes to PaddleX or provide suggestions. If you can fix an issue or add a new feature, please feel free to submit Pull Requests.