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简体中文 | English

Installation

This tutorial introduces how to install ArcFace-paddle and its requirements.

1. Install PaddlePaddle

PaddlePaddle 2.1 or later is required for ArcFace-paddle. You can use the following steps to install PaddlePaddle.

1.1 Environment requirements

  • python 3.x
  • cuda >= 10.1 (necessary if you want to use paddlepaddle-gpu)
  • cudnn >= 7.6.4 (necessary if you want to use paddlepaddle-gpu)
  • nccl >= 2.1.2 (necessary if you want the use distributed training/eval)
  • gcc >= 8.2

Docker is recomended to run ArcFace-paddle, for more detailed information about docker and nvidia-docker, you can refer to the tutorial.

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.

If you do not want to use docker, you can skip section 1.2 and go into section 1.3 directly.

1.2 (Recommended) Prepare for a docker environment. The first time you use this docker image, it will be downloaded automatically. Please be patient.

# Switch to the working directory
cd /home/Projects
# 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
# Create a docker container named face_paddle and map the current directory to the /paddle directory of the container
# It is recommended to set a shared memory greater than or equal to 8G through the --shm-size parameter
sudo docker run --name face_paddle -v $PWD:/paddle --shm-size=8G --network=host -it paddlepaddle/paddle:2.1.0 /bin/bash

# Use the following command to create a container if you want to use GPU in the container
sudo nvidia-docker run --name face_paddle -v $PWD:/paddle --shm-size=8G --network=host -it paddlepaddle/paddle:2.1.0-gpu-cuda10.2-cudnn7 /bin/bash

You can also visit DockerHub to get more docker images.

# use ctrl+P+Q to exit docker, to re-enter docker using the following command:
sudo docker exec -it face_paddle /bin/bash

1.3 Install PaddlePaddle using pip

If you want to use PaddlePaddle on GPU, you can use the following command to install PaddlePaddle.

pip3 install paddlepaddle-gpu --upgrade -i https://mirror.baidu.com/pypi/simple

If you want to use PaddlePaddle on CPU, you can use the following command to install PaddlePaddle.

pip3 install paddlepaddle --upgrade -i https://mirror.baidu.com/pypi/simple

Note:

  • 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.
  • You can also compile PaddlePaddle from source code, please refer to PaddlePaddle Installation tutorial to more compilation options.

1.4 Verify Installation process

import paddle
paddle.utils.run_check()

Check PaddlePaddle version：

python3 -c "import paddle; print(paddle.__version__)"

Note:

  • Make sure the compiled source code is later than PaddlePaddle2.0.
  • If you want to enable distribution ability, you should assign WITH_DISTRIBUTE=ON when compiling. For more compilation options, please refer to Instruction for more details.
  • 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.
  • 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.

2. Prepare for the environment of recognition

Run the following command to install requiremnts.

pip3 install -r requirement.txt

3. Prepare for the environment of detection

The detection module depends on PaddleDetection. You need to download PaddleDetection and install requiremnts, the command is as follows.

# clone PaddleDetection repo
cd <path/to/clone/PaddleDetection>
git clone https://github.com/PaddlePaddle/PaddleDetection.git

cd PaddleDetection
# install requiremnts
pip3 install -r requirements.txt

For more installation tutorials, please refer to Install tutorial.