mirror of https://github.com/open-mmlab/mmcv.git
fix docs (#440)
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## Introduction
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MMCV is a foundational python library for computer vision research and supports many
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research projects in MMLAB as below:
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research projects as below:
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- [MMDetection](https://github.com/open-mmlab/mmdetection): Detection toolbox and benchmark
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- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): General 3D object detection toolbox and benchmark
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@ -38,6 +38,8 @@ There are two versions of MMCV:
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- **mmcv**: lite, without CUDA ops but all other features, similar to mmcv<1.0.0. It is useful when you do not need those CUDA ops.
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- **mmcv-full**: comprehensive, with full features and various CUDA ops out of box. It takes longer time to build.
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**Note**: Do not install both versions in the same environment, otherwise you may encounter errors like `ModuleNotFound`. You need to uninstall one before installing the other.
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### Install with pip
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a. Install the lite version.
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b. Install the full version.
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We provide the pre-built mmcv package with different PyTorch and CUDA versions to simplify the building.
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Before installing mmcv-full, make sure that PyTorch has been successfully installed following the [official guide](https://pytorch.org/).
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We provide pre-built mmcv packages (recommended) with different PyTorch and CUDA versions to simplify the building.
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<table class="docutils"><tbody><tr><th width="80"> CUDA </th><th valign="bottom" align="left" width="100">torch 1.5</th><th valign="bottom" align="left" width="100">torch 1.4</th><th valign="bottom" align="left" width="100">torch 1.3</th></tr>
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<tr><td align="left">10.2</td><td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full==latest+torch1.5.0+cu102 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
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@ -12,6 +12,7 @@ which can be written in configs or specified via command line arguments.
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#### Usage
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A simplest example is
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```python
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cfg = dict(type='Conv3d')
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layer = build_norm_layer(cfg, in_channels=3, out_channels=8, kernel_size=3)
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@ -117,7 +118,7 @@ An example json file could be like:
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}
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```
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The default links of the pre-trained models hosted on Open-MMLab AWS could be found [here](../mmcv/model_zoo/open_mmlab.json).
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The default links of the pre-trained models hosted on OpenMMLab AWS could be found [here](https://github.com/open-mmlab/mmcv/blob/master/mmcv/model_zoo/open_mmlab.json).
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You may override default links by putting `open-mmlab.json` under `MMCV_HOME`. If `MMCV_HOME` is not find in the environment, `~/.cache/mmcv` will be used by default. You may `export MMCV_HOME=/your/path` to use your own path.
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