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- PaddlePaddle 2.2
- OS: 64-bit
- Python 3(3.5.1+/3.6/3.7/3.8/3.9)，64-bit version
- pip/pip3(9.0.1+)，64-bit version
- CUDA >= 10.1
- cuDNN >= 7.6
Please refer to the installation doc to install PaddlePaddle (the version >= 2.2).
Highly recommend you install the GPU version of PaddlePaddle, due to the large overhead of segmentation models, otherwise, it could be out of memory while running the models.
For example, run the following command to install Paddle with pip for Linux, CUDA 10.1.
python -m pip install paddlepaddle-gpu==2.2.2.post101 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
In Python interpreter, run the following command to confirm whether PaddlePaddle is installed successfully
>>> import paddle
>>> paddle.utils.run_check()
# If the following prompt appears on the command line, the PaddlePaddle installation is successful.
# PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now.
# Confirm PaddlePaddle version
>>> print(paddle.__version__)
Clone the PaddleSeg repo from Github.
git clone https://github.com/PaddlePaddle/PaddleSeg
cd PaddleSeg
pip install -r requirements.txt
If a version error occurs during installation, you can try to delete the old version and re-run the script.
In the root of PaddleSeg, run the following command. If there are no error in terminal log, you can use PaddleSeg to train, validate, test and export models with config method.
cd PaddleSeg
sh tests/run_check_install.sh
Besides, PaddleSeg also supports api method for flexible development, which requires the PaddleSeg is installed in python libs.
Run the following command to compile and install PaddleSeg from source code.
cd PaddleSeg
python setup.py install
Or, you can install the release PaddleSeg.
pip install paddleseg