更新高性能版本的依赖库,升级高性能处理库pillow。注意此操作仅支持x86架构。
apt-get install libtiff5-dev libjpeg8-dev libopenjp2-7-dev zlib1g-dev libfreetype6-dev liblcms2-dev libwebp-dev tcl8.6-dev tk8.6-dev python3-tk libharfbuzz-dev libfribidi-dev libxcb1-dev
yum install libtiff-devel libjpeg-devel openjpeg2-devel zlib-devel freetype-devel lcms2-devel libwebp-devel tcl-devel tk-devel harfbuzz-devel fribidi-devel libraqm-devel libimagequant-devel libxcb-devel
pip3.7 uninstall -y pillow
pip3.7 install pillow-simd
CC="cc -mavx2" pip3.7 install -U --force-reinstall pillow-simd
#PyTorch 1.8.1需安装0.9.1版本,PyTorch 1.11.0需安装0.12.0版本。以下以PyTorch 1.8.1安装0.9.1版本为例。 pip3 install torchvision==0.9.1
try: from PIL import Image, ImageOps, ImageEnhance,PILLOW_VERSION except: from PIL import Image, ImageOps, ImageEnhance PILLOW_VERSION="7.0.0"
在某些对host侧CPU要求较高的模型中,例如目标检测类模型,需要进行较为复杂的图像预处理。为获得更好的图像处理性能,可采用编译安装opencv的方式。
编译安装opencv的步骤如下:
export GIT_SSL_NO_VERIFY=true
git clone https://github.com/opencv/opencv.git cd opencv mkdir -p build
cd build cmake -D BUILD_opencv_python3=yes -D BUILD_opencv_python2=no -D PYTHON3_EXECUTABLE=/usr/local/python3.7.5/bin/python3.7m -D PYTHON3_INCLUDE_DIR=/usr/local/python3.7.5/include/python3.7m -D PYTHON3_LIBRARY=/usr/local/python3.7.5/lib/libpython3.7m.so -D PYTHON3_NUMPY_INCLUDE_DIRS=/usr/local/python3.7.5/lib/python3.7/site-packages/numpy/core/include -D PYTHON3_PACKAGES_PATH=/usr/local/python3.7.5/lib/python3.7/site-packages -D PYTHON3_DEFAULT_EXECUTABLE=/usr/local/python3.7.5/bin/python3.7m .. make -j$nproc make install