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mmcv/docs/get_started/introduction.md
Zaida Zhou 1216e5fe7f
[Docs] Use PyTorch sphinx theme (#1321) 
* [Docs] Use PyTorch sphinx theme

* add sphinx-copybutton

* add twitter and zhihu link

* remove shpinx_rtd_theme from doc.xtx

* update docs.txt

* update conf.py
2021-09-14 16:35:41 +08:00

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Introduction

MMCV is a foundational library for computer vision research and supports many research projects as below:

  • MMClassification: OpenMMLab image classification toolbox and benchmark.
  • MMDetection: OpenMMLab detection toolbox and benchmark.
  • MMDetection3D: OpenMMLab's next-generation platform for general 3D object detection.
  • MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark.
  • MMAction2: OpenMMLab's next-generation action understanding toolbox and benchmark.
  • MMTracking: OpenMMLab video perception toolbox and benchmark.
  • MMPose: OpenMMLab pose estimation toolbox and benchmark.
  • MMEditing: OpenMMLab image and video editing toolbox.
  • MMOCR: OpenMMLab text detection, recognition and understanding toolbox.
  • MMGeneration: OpenMMLab image and video generative models toolbox.

It provides the following functionalities.

  • Universal IO APIs
  • Image/Video processing
  • Image and annotation visualization
  • Useful utilities (progress bar, timer, ...)
  • PyTorch runner with hooking mechanism
  • Various CNN architectures
  • High-quality implementation of common CUDA ops
MMCV requires Python 3.6+.