mirror of https://github.com/open-mmlab/mmcv.git
34 lines
1.7 KiB
Markdown
34 lines
1.7 KiB
Markdown
## Introduction
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<div align="center">
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<img src="https://raw.githubusercontent.com/open-mmlab/mmcv/master/docs/mmcv-logo.png" width="300"/>
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</div>
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MMCV is a foundational library for computer vision research and supports many
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research projects as below:
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- [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab image classification toolbox and benchmark.
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- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab detection toolbox and benchmark.
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- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab's next-generation platform for general 3D object detection.
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- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark.
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- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab's next-generation action understanding toolbox and benchmark.
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- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark.
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- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark.
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- [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab image and video editing toolbox.
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- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition and understanding toolbox.
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- [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab image and video generative models toolbox.
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It provides the following functionalities.
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- Universal IO APIs
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- Image/Video processing
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- Image and annotation visualization
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- Useful utilities (progress bar, timer, ...)
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- PyTorch runner with hooking mechanism
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- Various CNN architectures
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- High-quality implementation of common CUDA ops
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```{note}
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MMCV requires Python 3.6+.
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```
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