88 lines
2.9 KiB
Markdown
88 lines
2.9 KiB
Markdown
## Installation
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### Requirements
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- Python 3.6+
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- PyTorch 1.3+
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- [MMCV](https://github.com/open-mmlab/mmcv)
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The compatible MMClassification and MMCV versions are as below. Please install the correct version of MMCV to avoid installation issues.
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| MMClassification version | MMCV version |
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|:-------------------:|:-------------------:|
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| master | mmcv>=1.3.1, <=1.5.0 |
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| 0.12.0 | mmcv>=1.3.1, <=1.5.0 |
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| 0.11.1 | mmcv>=1.3.1, <=1.5.0 |
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| 0.11.0 | mmcv>=1.3.0 |
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| 0.10.0 | mmcv>=1.3.0 |
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| 0.9.0 | mmcv>=1.1.4 |
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| 0.8.0 | mmcv>=1.1.4 |
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| 0.7.0 | mmcv>=1.1.4 |
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| 0.6.0 | mmcv>=1.1.4 |
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### Install MMClassification
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a. Create a conda virtual environment and activate it.
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```shell
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conda create -n open-mmlab python=3.7 -y
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conda activate open-mmlab
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```
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b. Install PyTorch and torchvision following the [official instructions](https://pytorch.org/), e.g.,
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```shell
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conda install pytorch torchvision -c pytorch
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```
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Note: Make sure that your compilation CUDA version and runtime CUDA version match.
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You can check the supported CUDA version for precompiled packages on the [PyTorch website](https://pytorch.org/).
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`E.g.1` If you have CUDA 10.1 installed under `/usr/local/cuda` and would like to install
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PyTorch 1.5, you need to install the prebuilt PyTorch with CUDA 10.1.
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```shell
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conda install pytorch cudatoolkit=10.1 torchvision -c pytorch
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```
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`E.g.2` If you have CUDA 9.2 installed under `/usr/local/cuda` and would like to install
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PyTorch 1.3.1., you need to install the prebuilt PyTorch with CUDA 9.2.
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```shell
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conda install pytorch=1.3.1 cudatoolkit=9.2 torchvision=0.4.2 -c pytorch
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```
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If you build PyTorch from source instead of installing the prebuilt pacakge,
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you can use more CUDA versions such as 9.0.
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c. Clone the mmclassification repository.
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```shell
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git clone https://github.com/open-mmlab/mmclassification.git
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cd mmclassification
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```
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d. Install build requirements and then install mmclassification.
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```shell
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pip install -e . # or "python setup.py develop"
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```
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Note:
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1. Following the above instructions, mmclassification is installed on `dev` mode, any local modifications made to the code will take effect without the need to reinstall it (unless you submit some commits and want to update the version number).
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2. If you would like to use `opencv-python-headless` instead of `opencv-python`,
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you can install it before installing [mmcv](https://github.com/open-mmlab/mmcv).
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### Using multiple MMClassification versions
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The train and test scripts already modify the `PYTHONPATH` to ensure the script use the MMClassification in the current directory.
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To use the default MMClassification installed in the environment rather than that you are working with, you can remove the following line in those scripts
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```shell
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PYTHONPATH="$(dirname $0)/..":$PYTHONPATH
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```
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