2021-07-07 13:10:04 +08:00
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## 安装 MMCV
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2021-07-20 17:18:28 +08:00
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MMCV 有两个版本：
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2022-10-17 17:10:03 +08:00
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- **mmcv-full**: 完整版，包含所有的特性以及丰富的开箱即用的 CPU 和 CUDA 算子。注意，完整版本可能需要更长时间来编译。
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- **mmcv**: 精简版，不包含 CPU 和 CUDA 算子但包含其余所有特性和功能，类似 MMCV 1.0 之前的版本。如果你不需要使用算子的话，精简版可以作为一个考虑选项。
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2021-07-20 17:18:28 +08:00
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2021-11-02 23:37:56 +08:00
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```{warning}
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请不要在同一个环境中安装两个版本，否则可能会遇到类似 `ModuleNotFound` 的错误。在安装一个版本之前，需要先卸载另一个。`如果CUDA可用，强烈推荐安装mmcv-full`。
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```
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2021-07-20 17:18:28 +08:00
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2022-10-17 17:10:03 +08:00
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### 安装 mmcv-full
|
2021-07-20 17:18:28 +08:00
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2022-10-17 17:10:03 +08:00
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```{note}
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2022-10-26 17:31:48 +08:00
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- 如需编译 ONNX Runtime 自定义算子，请参考[如何编译ONNX Runtime自定义算子](../deployment/onnxruntime_op.md#如何编译onnx-runtime自定义算子)
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- 如需编译 TensorRT 自定义，请参考[如何编译MMCV中的TensorRT插件](../deployment/tensorrt_plugin.md#如何编译mmcv中的tensorrt插件)
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2022-10-17 17:10:03 +08:00
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```
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在安装 mmcv-full 之前，请确保 PyTorch 已经成功安装在环境中，可以参考 [PyTorch 官方安装文档](https://pytorch.org/get-started/locally/#start-locally)。可使用以下命令验证
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```bash
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python -c 'import torch;print(torch.__version__)'
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```
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2021-07-20 17:18:28 +08:00
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2022-10-17 17:10:03 +08:00
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如果输出版本信息，则表示 PyTorch 已安装。
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2021-07-20 17:18:28 +08:00
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2022-10-17 17:10:03 +08:00
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#### 使用 mim 安装（推荐）
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2021-07-20 17:18:28 +08:00
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2022-10-17 17:10:03 +08:00
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[mim](https://github.com/open-mmlab/mim) 是 OpenMMLab 项目的包管理工具，使用它可以很方便地安装 mmcv-full。
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2021-07-20 17:18:28 +08:00
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|
2022-10-17 17:10:03 +08:00
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```bash
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pip install -U openmim
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mim install mmcv-full
|
2021-07-20 17:18:28 +08:00
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```
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2022-10-17 17:10:03 +08:00
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如果发现上述的安装命令没有使用预编译包（以 `.whl` 结尾）而是使用源码包（以 `.tar.gz` 结尾）安装，则有可能是我们没有提供和当前环境的 PyTorch 版本、CUDA 版本相匹配的 mmcv-full 预编译包，此时，你可以[源码安装 mmcv-full](build.md)。
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<details>
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<summary>使用预编译包的安装日志</summary>
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Looking in links: https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/index.html<br />
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Collecting mmcv-full<br />
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<b>Downloading https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/mmcv_full-1.6.1-cp38-cp38-manylinux1_x86_64.whl</b>
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</details>
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<details>
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<summary>使用源码包的安装日志</summary>
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Looking in links: https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/index.html<br />
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Collecting mmcv-full==1.6.0<br />
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<b>Downloading mmcv-full-1.6.0.tar.gz</b>
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2021-07-20 17:18:28 +08:00
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2022-10-17 17:10:03 +08:00
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</details>
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|
2022-11-11 15:40:50 +08:00
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如需安装指定版本的 mmcv-full，例如安装 1.7.0 版本的 mmcv-full，可使用以下命令
|
2022-10-17 17:10:03 +08:00
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```bash
|
2022-11-11 15:40:50 +08:00
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mim install mmcv-full==1.7.0
|
2021-07-20 17:18:28 +08:00
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```
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|
2022-10-17 17:10:03 +08:00
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:::{note}
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如果你打算使用 `opencv-python-headless` 而不是 `opencv-python`，例如在一个很小的容器环境或者没有图形用户界面的服务器中，你可以先安装 `opencv-python-headless`，这样在安装 mmcv 依赖的过程中会跳过 `opencv-python`。
|
2021-10-13 20:25:49 +08:00
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|
2022-10-17 17:10:03 +08:00
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另外，如果安装依赖库的时间过长，可以指定 pypi 源
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```bash
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mim install mmcv-full -i https://pypi.tuna.tsinghua.edu.cn/simple
|
2021-10-13 20:25:49 +08:00
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```
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|
2022-10-17 17:10:03 +08:00
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:::
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安装完成后可以运行 [check_installation.py](https://github.com/open-mmlab/mmcv/.dev_scripts/check_installation.py) 脚本检查 mmcv-full 是否安装成功。
|
2021-07-20 17:18:28 +08:00
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|
2022-10-17 17:10:03 +08:00
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#### 使用 pip 安装
|
2021-07-20 17:18:28 +08:00
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|
2022-10-17 17:10:03 +08:00
|
|
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|
使用以下命令查看 CUDA 和 PyTorch 的版本
|
2021-07-20 17:18:28 +08:00
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|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
```bash
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|
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|
|
python -c 'import torch;print(torch.__version__);print(torch.version.cuda)'
|
2021-07-20 17:18:28 +08:00
|
|
|
|
```
|
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|
2022-10-17 17:10:03 +08:00
|
|
|
|
根据系统的类型、CUDA 版本、PyTorch 版本以及 MMCV 版本选择相应的安装命令
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<html>
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<body>
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<style>
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select {
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z-index: 1000;
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position: absolute;
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top: 10px;
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width: 6.7rem;
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}
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#select-container {
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position: relative;
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height: 30px;
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}
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#select-cmd {
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background-color: #f5f6f7;
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font-size: 14px;
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margin-top: 20px;
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}
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/* 让每一个都间隔1.3rem */
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#select-os {
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/* left: 1.375rem; */
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left: 0;
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}
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#select-cuda {
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/* left: 9.375rem; 9.375 = 1.375 + 6.7 + 1.3 */
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left: 8rem;
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}
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#select-torch {
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/* left: 17.375rem; 17.375 = 9.375 + 6.7 + 1.3 */
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left: 16rem;
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}
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#select-mmcv {
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/* left: 25.375rem; 25.375 = 17.375 + 6.7 + 1.3 */
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left: 24rem;
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}
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</style>
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|
<div id="select-container">
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<select
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onmousedown="handleSelectMouseDown(this.id)"
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onblur="handleSelectBlur(this.id)"
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onchange="changeOS(this.value)"
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id="select-os">
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</select>
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<select
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onmousedown="handleSelectMouseDown(this.id)"
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onblur="handleSelectBlur(this.id)"
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onchange="changeCUDA(this.value)"
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id="select-cuda">
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</select>
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<select
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onmousedown="handleSelectMouseDown(this.id)"
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onblur="handleSelectBlur(this.id)"
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onchange="changeTorch(this.value)"
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id="select-torch">
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|
</select>
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<select
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onmousedown="handleSelectMouseDown(this.id)"
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onblur="handleSelectBlur(this.id)"
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onchange="changeMMCV(this.value)"
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id="select-mmcv">
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</select>
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</div>
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|
<pre id="select-cmd"></pre>
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|
</body>
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|
|
<script>
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|
|
// 各个select当前的值
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|
let osVal, cudaVal, torchVal, mmcvVal;
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function changeMMCV(val) {
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|
mmcvVal = val;
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change("select-mmcv");
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}
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|
function changeTorch(val) {
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torchVal = val;
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change("select-torch");
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|
}
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function changeCUDA(val) {
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cudaVal = val;
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|
change("select-cuda");
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|
}
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function changeOS(val) {
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osVal = val;
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change("select-os");
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}
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|
// 控制size大小相关的几个方法
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function handleSelectMouseDown(id) {
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|
const dom = document.getElementById(id);
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|
if (!dom) return;
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|
const len = dom?.options?.length;
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|
if (len >= 9) {
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dom.size = 10;
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dom.style.zIndex = 100;
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}
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}
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|
function handleSelectClick() {
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|
const selects = Array.from(document.getElementsByTagName("select"));
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selects.forEach(select => {
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select.size = 1;
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});
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}
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function handleSelectBlur(id) {
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|
const dom = document.getElementById(id);
|
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|
if (!dom) {
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|
|
// 如果没有指定特定的id，那就直接把所有的select都设置成size = 1
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|
|
handleSelectClick();
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|
return;
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|
}
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|
|
dom.size = 1;
|
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|
|
|
|
dom.style.zIndex = 1;
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|
|
|
}
|
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|
|
function changeCmd() {
|
|
|
|
|
|
const cmd = document.getElementById("select-cmd");
|
|
|
|
|
|
let cmdString = "pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html";
|
|
|
|
|
|
// e.g: pip install mmcv-full==1.6.0 -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9/index.html
|
2022-11-11 15:40:50 +08:00
|
|
|
|
let cudaVersion;
|
|
|
|
|
|
if (cudaVal === "cpu" || cudaVal === "mps") {
|
|
|
|
|
|
cudaVersion = "cpu";
|
|
|
|
|
|
} else {
|
|
|
|
|
|
cudaVersion = `cu${cudaVal.split(".").join("")}`;
|
|
|
|
|
|
}
|
2022-10-17 17:10:03 +08:00
|
|
|
|
const torchVersion = `torch${torchVal.substring(0, torchVal.length - 2)}`;
|
|
|
|
|
|
cmdString = cmdString.replace("{cu_version}", cudaVersion).replace("{mmcv_version}", mmcvVal).replace("{torch_version}", torchVersion);
|
|
|
|
|
|
cmd.textContent = cmdString;
|
|
|
|
|
|
}
|
|
|
|
|
|
// string数组去重
|
|
|
|
|
|
function unique(arr) {
|
|
|
|
|
|
if (!arr || !Array.isArray(arr)) return [];
|
|
|
|
|
|
return [...new Set(arr)];
|
|
|
|
|
|
}
|
|
|
|
|
|
// 根据string数组生成option的DocumentFragment
|
|
|
|
|
|
function genOptionFragment(data, id) {
|
|
|
|
|
|
const name = id.includes("-")? id.split("-")[1] : id;
|
|
|
|
|
|
const fragment = new DocumentFragment();
|
|
|
|
|
|
data.forEach(option => {
|
|
|
|
|
|
const ele = document.createElement("option");
|
|
|
|
|
|
let text = `${name} ${option}`;
|
2022-11-11 15:40:50 +08:00
|
|
|
|
if (name === "os" || option.toUpperCase() === "CPU" || option.toUpperCase() === "MPS") {
|
2022-10-17 17:10:03 +08:00
|
|
|
|
text = `${option}`;
|
|
|
|
|
|
}
|
|
|
|
|
|
ele.textContent = text;
|
|
|
|
|
|
// 添加value属性，方便下拉框选择时直接读到数据
|
|
|
|
|
|
ele.value = option;
|
|
|
|
|
|
// 添加点击事件监听
|
|
|
|
|
|
ele.addEventListener('click', handleSelectClick);
|
|
|
|
|
|
fragment.appendChild(ele);
|
|
|
|
|
|
});
|
|
|
|
|
|
return fragment;
|
|
|
|
|
|
}
|
|
|
|
|
|
// 在dom树中找到id对应的dom（select元素），并将生成的options添加到元素内
|
|
|
|
|
|
function findAndAppend(data, id) {
|
|
|
|
|
|
const fragment = genOptionFragment(data, id);
|
|
|
|
|
|
const dom = document.getElementById(id);
|
|
|
|
|
|
if (dom) dom.replaceChildren(fragment);
|
|
|
|
|
|
}
|
|
|
|
|
|
/**
|
|
|
|
|
|
* change方法的重点在于
|
|
|
|
|
|
* 1. 各个下拉框数据的联动
|
|
|
|
|
|
* OS ==> cuda ==> torch ==> mmcv
|
|
|
|
|
|
* 2. 命令行的修改
|
|
|
|
|
|
*/
|
|
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|
|
function change(id) {
|
|
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|
|
const order = ["select-mmcv", "select-torch", "select-cuda", "select-os"];
|
|
|
|
|
|
const idx = order.indexOf(id);
|
|
|
|
|
|
if (idx === -1) return;
|
|
|
|
|
|
const versionDetail = version[osVal];
|
|
|
|
|
|
if (idx >= 3) {
|
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|
|
|
|
// 根据os修改cuda
|
|
|
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|
|
let cuda = [];
|
|
|
|
|
|
versionDetail.forEach(v => {
|
|
|
|
|
|
cuda.push(v.cuda);
|
|
|
|
|
|
});
|
|
|
|
|
|
cuda = unique(cuda);
|
|
|
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|
|
cudaVal = cuda[0];
|
|
|
|
|
|
findAndAppend(cuda, "select-cuda");
|
|
|
|
|
|
}
|
|
|
|
|
|
if (idx >= 2) {
|
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|
|
|
|
// 根据cuda修改torch
|
|
|
|
|
|
const torch = [];
|
|
|
|
|
|
versionDetail.forEach(v => {
|
|
|
|
|
|
if (v.cuda === cudaVal) torch.push(v.torch);
|
|
|
|
|
|
});
|
|
|
|
|
|
torchVal = torch[0];
|
|
|
|
|
|
findAndAppend(torch, "select-torch");
|
|
|
|
|
|
}
|
|
|
|
|
|
if (idx >= 1) {
|
|
|
|
|
|
// 根据torch修改mmcv
|
|
|
|
|
|
let mmcv = [];
|
|
|
|
|
|
versionDetail.forEach(v => {
|
|
|
|
|
|
if (v.cuda === cudaVal && v.torch === torchVal) mmcv = v.mmcv;
|
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|
|
|
|
});
|
|
|
|
|
|
mmcvVal = mmcv[0];
|
|
|
|
|
|
findAndAppend(mmcv, "select-mmcv");
|
|
|
|
|
|
}
|
|
|
|
|
|
changeCmd();
|
|
|
|
|
|
}
|
|
|
|
|
|
// 初始化，处理version数据，并调用findAndAppend
|
|
|
|
|
|
function init() {
|
|
|
|
|
|
// 增加一个全局的click事件监听，作为select onBlur事件失效的兜底
|
|
|
|
|
|
document.addEventListener("click", handleSelectBlur);
|
|
|
|
|
|
const version = window.version;
|
|
|
|
|
|
// OS
|
|
|
|
|
|
const os = Object.keys(version);
|
|
|
|
|
|
osVal = os[0];
|
|
|
|
|
|
findAndAppend(os, "select-os");
|
|
|
|
|
|
change("select-os");
|
|
|
|
|
|
changeCmd();
|
|
|
|
|
|
}
|
|
|
|
|
|
// 利用xhr获取本地version数据，如果作为html直接浏览的话需要使用本地服务器打开，否则会有跨域问题
|
|
|
|
|
|
window.onload = function () {
|
|
|
|
|
|
const url = "../_static/version.json"
|
|
|
|
|
|
// 申明一个XMLHttpRequest
|
|
|
|
|
|
const request = new XMLHttpRequest();
|
|
|
|
|
|
// 设置请求方法与路径
|
|
|
|
|
|
request.open("get", url);
|
|
|
|
|
|
// 不发送数据到服务器
|
|
|
|
|
|
request.send(null);
|
|
|
|
|
|
//XHR对象获取到返回信息后执行
|
|
|
|
|
|
request.onload = function () {
|
|
|
|
|
|
// 返回状态为200，即为数据获取成功
|
|
|
|
|
|
if (request.status !== 200) return;
|
|
|
|
|
|
const data = JSON.parse(request.responseText);
|
|
|
|
|
|
window.version = data;
|
|
|
|
|
|
init();
|
|
|
|
|
|
}
|
|
|
|
|
|
}
|
|
|
|
|
|
</script>
|
|
|
|
|
|
</html>
|
|
|
|
|
|
|
|
|
|
|
|
如果在上面的下拉框中没有找到对应的版本，则可能是没有对应 PyTorch 或者 CUDA 或者 mmcv-full 版本的预编译包，此时，你可以[源码安装 mmcv-full](../faq.md)。
|
2021-07-20 17:18:28 +08:00
|
|
|
|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
:::{note}
|
|
|
|
|
|
PyTorch 在 1.x.0 和 1.x.1 之间通常是兼容的，故 mmcv-full 只提供 1.x.0 的编译包。如果你
|
|
|
|
|
|
的 PyTorch 版本是 1.x.1，你可以放心地安装在 1.x.0 版本编译的 mmcv-full。例如，如果你的
|
|
|
|
|
|
PyTorch 版本是 1.8.1，你可以放心选择 1.8.x。
|
|
|
|
|
|
:::
|
|
|
|
|
|
|
|
|
|
|
|
:::{note}
|
|
|
|
|
|
如果你打算使用 `opencv-python-headless` 而不是 `opencv-python`，例如在一个很小的容器环境或者没有图形用户界面的服务器中，你可以先安装 `opencv-python-headless`，这样在安装 mmcv 依赖的过程中会跳过 `opencv-python`。
|
|
|
|
|
|
|
|
|
|
|
|
另外，如果安装依赖库的时间过长，可以指定 pypi 源
|
|
|
|
|
|
|
|
|
|
|
|
```bash
|
|
|
|
|
|
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.html -i https://pypi.tuna.tsinghua.edu.cn/simple
|
2021-07-20 17:18:28 +08:00
|
|
|
|
```
|
|
|
|
|
|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
:::
|
2021-07-20 17:18:28 +08:00
|
|
|
|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
安装完成后可以运行 [check_installation.py](https://github.com/open-mmlab/mmcv/.dev_scripts/check_installation.py) 脚本检查 mmcv-full 是否安装成功。
|
|
|
|
|
|
|
|
|
|
|
|
#### 使用 docker 镜像
|
|
|
|
|
|
|
|
|
|
|
|
先将算法库克隆到本地再构建镜像
|
|
|
|
|
|
|
|
|
|
|
|
```bash
|
|
|
|
|
|
git clone https://github.com/open-mmlab/mmcv.git && cd mmcv
|
|
|
|
|
|
docker build -t mmcv -f docker/release/Dockerfile .
|
2021-11-02 23:37:56 +08:00
|
|
|
|
```
|
|
|
|
|
|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
也可以直接使用下面的命令构建镜像
|
|
|
|
|
|
|
|
|
|
|
|
```bash
|
|
|
|
|
|
docker build -t mmcv https://github.com/open-mmlab/mmcv.git#master:docker/release
|
2022-03-23 23:41:51 +08:00
|
|
|
|
```
|
|
|
|
|
|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
[Dockerfile](release/Dockerfile) 默认安装最新的 mmcv-full，如果你想要指定版本，可以使用下面的命令
|
2021-07-20 17:18:28 +08:00
|
|
|
|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
```bash
|
|
|
|
|
|
docker image build -t mmcv -f docker/release/Dockerfile --build-arg MMCV=1.5.0 .
|
2021-07-20 17:18:28 +08:00
|
|
|
|
```
|
|
|
|
|
|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
如果你想要使用其他版本的 PyTorch 和 CUDA，你可以在构建镜像时指定它们的版本。
|
2021-07-20 17:18:28 +08:00
|
|
|
|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
例如指定 PyTorch 的版本是 1.11，CUDA 的版本是 11.3
|
2021-07-20 17:18:28 +08:00
|
|
|
|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
```bash
|
|
|
|
|
|
docker build -t mmcv -f docker/release/Dockerfile \
|
|
|
|
|
|
--build-arg PYTORCH=1.11.0 \
|
|
|
|
|
|
--build-arg CUDA=11.3 \
|
|
|
|
|
|
--build-arg CUDNN=8 \
|
|
|
|
|
|
--build-arg MMCV=1.5.0 .
|
2021-07-20 17:18:28 +08:00
|
|
|
|
```
|
|
|
|
|
|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
更多 PyTorch 和 CUDA 镜像可以点击 [dockerhub/pytorch](https://hub.docker.com/r/pytorch/pytorch/tags) 查看。
|
2021-07-20 17:18:28 +08:00
|
|
|
|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
### 安装 mmcv
|
2021-07-20 17:18:28 +08:00
|
|
|
|
|
2022-10-17 17:10:03 +08:00
|
|
|
|
如果你需要使用和 PyTorch 相关的模块，请确保 PyTorch 已经成功安装在环境中，可以参考 [PyTorch 官方安装文档](https://pytorch.org/get-started/locally/#start-locally)。
|
|
|
|
|
|
|
|
|
|
|
|
```python
|
|
|
|
|
|
pip install mmcv
|
|
|
|
|
|
```
|
