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110 lines
4.7 KiB
Markdown
110 lines
4.7 KiB
Markdown
[简体中文](install_cn.md) | English
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# Installation
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---
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This tutorial introduces how to install ArcFace-paddle and its requirements.
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## 1. Install PaddlePaddle
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`PaddlePaddle 2.2.0rc0` or later is required for ArcFace-paddle. You can use the following steps to install PaddlePaddle.
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### 1.1 Environment requirements
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- python 3.x
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- cuda >= 10.1 (necessary if you want to use paddlepaddle-gpu)
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- cudnn >= 7.6.4 (necessary if you want to use paddlepaddle-gpu)
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- nccl >= 2.1.2 (necessary if you want the use distributed training/eval)
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- gcc >= 8.2
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Docker is recomended to run ArcFace-paddle, for more detailed information about docker and nvidia-docker, you can refer to the [tutorial](https://www.runoob.com/docker/docker-tutorial.html).
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When you use cuda10.1, the driver version needs to be larger or equal than 418.39. When you use cuda10.2, the driver version needs to be larger or equal than 440.33. For more cuda versions and specific driver versions, you can refer to the [link](https://docs.nvidia.com/deploy/cuda-compatibility/index.html).
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If you do not want to use docker, you can skip section 1.2 and go into section 1.3 directly.
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### 1.2 (Recommended) Prepare for a docker environment. The first time you use this docker image, it will be downloaded automatically. Please be patient.
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```
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# Switch to the working directory
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cd /home/Projects
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# You need to create a docker container for the first run, and do not need to run the current command when you run it again
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# Create a docker container named face_paddle and map the current directory to the /paddle directory of the container
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# It is recommended to set a shared memory greater than or equal to 8G through the --shm-size parameter
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sudo docker run --name face_paddle -v $PWD:/paddle --shm-size=8G --network=host -it paddlepaddle/paddle:2.2.0rc0 /bin/bash
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# Use the following command to create a container if you want to use GPU in the container
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sudo nvidia-docker run --name face_paddle -v $PWD:/paddle --shm-size=8G --network=host -it paddlepaddle/paddle:2.2.0rc0-gpu-cuda11.2-cudnn8 /bin/bash
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```
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You can also visit [DockerHub](https://hub.docker.com/r/paddlepaddle/paddle/tags/) to get more docker images.
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```
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# use ctrl+P+Q to exit docker, to re-enter docker using the following command:
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sudo docker exec -it face_paddle /bin/bash
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```
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### 1.3 Install PaddlePaddle using pip
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If you want to use PaddlePaddle on GPU, you can use the following command to install PaddlePaddle.
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```bash
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pip3 install paddlepaddle-gpu==2.2.0rc0 --upgrade -i https://mirror.baidu.com/pypi/simple
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```
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If you want to use PaddlePaddle on CPU, you can use the following command to install PaddlePaddle.
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```bash
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pip3 install paddlepaddle==2.2.0rc0 --upgrade -i https://mirror.baidu.com/pypi/simple
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```
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**Note:**
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* If you have already installed CPU version of PaddlePaddle and want to use GPU version now, you should uninstall CPU version of PaddlePaddle and then install GPU version to avoid package confusion.
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* You can also compile PaddlePaddle from source code, please refer to [PaddlePaddle Installation tutorial](http://www.paddlepaddle.org.cn/install/quick) to more compilation options.
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### 1.4 Verify Installation process
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```python
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import paddle
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paddle.utils.run_check()
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```
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Check PaddlePaddle version：
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```bash
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python3 -c "import paddle; print(paddle.__version__)"
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```
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Note:
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- Make sure the compiled source code is later than PaddlePaddle2.0.
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- If you want to enable distribution ability, you should assign **WITH_DISTRIBUTE=ON** when compiling. For more compilation options, please refer to [Instruction](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/install/Tables.html#id3) for more details.
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- When running in docker, in order to ensure that the container has enough shared memory for dataloader acceleration of Paddle, please set the parameter `--shm_size=8g` at creating a docker container, if conditions permit, you can set it to a larger value.
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- If you just want to use recognition module, you can skip section 3. If you just want to use detection module, you can skip section 2.
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## 2. Prepare for the environment of recognition
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Run the following command to install `requiremnts`.
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```shell
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pip3 install -r requirement.txt
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```
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## 3. Prepare for the environment of detection
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The detection module depends on PaddleDetection. You need to download PaddleDetection and install `requiremnts`, the command is as follows.
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```bash
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# clone PaddleDetection repo
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cd <path/to/clone/PaddleDetection>
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git clone https://github.com/PaddlePaddle/PaddleDetection.git
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cd PaddleDetection
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# install requiremnts
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pip3 install -r requirements.txt
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```
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For more installation tutorials, please refer to [Install tutorial](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/docs/tutorials/INSTALL.md).
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