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QUICK INSTALLATION

After testing, paddleocr can run on glibc 2.23. You can also test other glibc versions or install glic 2.23 for the best compatibility.

PaddleOCR working environment:

  • PaddlePaddle1.8+, Recommend PaddlePaddle 2.0.0.beta
  • python3.7
  • glibc 2.23

It is recommended to use the docker provided by us to run PaddleOCR, please refer to the use of docker link.

If you want to directly run the prediction code on mac or windows, you can start from step 2.

1. (Recommended) Prepare a docker environment. The first time you use this 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 ppocr and map the current directory to the /paddle directory of the container

# If using CPU, use docker instead of nvidia-docker to create docker
sudo docker run --name ppocr -v $PWD:/paddle --network=host -it hub.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda9.0-cudnn7-dev /bin/bash

If using CUDA9, please run the following command to create a container:

sudo nvidia-docker run --name ppocr -v $PWD:/paddle --network=host -it hub.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda9.0-cudnn7-dev /bin/bash

If using CUDA10, please run the following command to create a container:

sudo nvidia-docker run --name ppocr -v $PWD:/paddle --network=host -it hub.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda10.0-cudnn7-dev /bin/bash

You can also visit DockerHub to get the image that fits your machine.

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

Note: If the docker pull is too slow, you can download and load the docker image manually according to the following steps. Take cuda9 docker for example, you only need to change cuda9 to cuda10 to use cuda10 docker:

# Download the CUDA9 docker compressed file and unzip it
wget https://paddleocr.bj.bcebos.com/docker/docker_pdocr_cuda9.tar.gz
# To reduce download time, the uploaded docker image is compressed and needs to be decompressed
tar zxf docker_pdocr_cuda9.tar.gz
# Create image
docker load < docker_pdocr_cuda9.tar
# After completing the above steps, check whether the downloaded image is loaded through docker images
docker images
# If you have the following output after executing docker images, you can follow step 1 to create a docker environment.
hub.baidubce.com/paddlepaddle/paddle   latest-gpu-cuda9.0-cudnn7-dev    f56310dcc829

2. Install PaddlePaddle v2.0

python3 -m pip install --upgrade pip

# If you have cuda9 or cuda10 installed on your machine, please run the following command to install
python3 -m pip install paddlepaddle-gpu==2.0.0b0 -i https://mirror.baidu.com/pypi/simple

# If you only have cpu on your machine, please run the following command to install
python3 -m pip install paddlepaddle==2.0.0b0 -i https://mirror.baidu.com/pypi/simple

For more software version requirements, please refer to the instructions in Installation Document for operation.

3. Clone PaddleOCR repo

# Recommend
git clone https://github.com/PaddlePaddle/PaddleOCR

# If you cannot pull successfully due to network problems, you can also choose to use the code hosting on the cloud:

git clone https://gitee.com/paddlepaddle/PaddleOCR

# Note: The cloud-hosting code may not be able to synchronize the update with this GitHub project in real time. There might be a delay of 3-5 days. Please give priority to the recommended method.

4. Install third-party libraries

cd PaddleOCR
python3 -m pip install -r requirements.txt

If you getting this error OSError: [WinError 126] The specified module could not be found when you install shapely on windows.

Please try to download Shapely whl file using http://www.lfd.uci.edu/~gohlke/pythonlibs/#shapely.

Reference: Solve shapely installation on windows