虽然Ubuntu 18.04可以通过apt安装caffe,但是为了使用最新的代码,还是值得从源码安装一遍的。
安装环境
- OS: Ubuntu 18.04 64 bit
- 显卡: NVidia GTX 1080
- CUDA: 10.0
- cuDNN: 7.4
- Python: 3.6
任务:从源码编译安装caffe
安装OpenCV
参考[笔记] Ubuntu 18.04源码编译安装OpenCV 4.0流程,安装OpenCV。
安装依赖
$ apt install -y libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
$ apt install -y --no-install-recommends libboost-all-dev
$ apt install -y libatlas-base-dev
$ apt install -y libgflags-dev libgoogle-glog-dev liblmdb-dev
下载源码
$ git clone https://github.com/BVLC/caffe.git
$ cd caffe
$ cp Makefile.config.example Makefile.config
更新代码
因为使用OpenCV 4.0
的版本,所以有些常量需要更新:
CV_LOAD_IMAGE_GRAYSCALE -> cv::ImreadModes::IMREAD_GRAYSCALE
CV_LOAD_IMAGE_COLOR -> cv::IMREAD_COLOR
替换命令如下:
sed -i 's/CV_LOAD_IMAGE_COLOR/cv::IMREAD_COLOR/g' src/caffe/layers/window_data_layer.cpp
sed -i 's/CV_LOAD_IMAGE_COLOR/cv::IMREAD_COLOR/g' src/caffe/util/io.cpp
sed -i 's/CV_LOAD_IMAGE_GRAYSCALE/cv::ImreadModes::IMREAD_GRAYSCALE/g' src/caffe/util/io.cpp
修改配置
为了使用OpenCV 4.0 + CUDA 10 + cuDNN + python 3.6
,修改Makefile.config
如下:
...
USE_CUDNN := 1
...
OPENCV_VERSION := 3
...
CUDA_DIR := /usr/local/cuda-10.0
...
CUDA_ARCH := \
-gencode arch=compute_30,code=sm_30 \
-gencode arch=compute_35,code=sm_35 \
-gencode arch=compute_50,code=sm_50 \
-gencode arch=compute_52,code=sm_52 \
-gencode arch=compute_60,code=sm_60 \
-gencode arch=compute_61,code=sm_61 \
-gencode arch=compute_61,code=compute_61
...
# Uncomment to use Python 3 (default is Python 2)
PYTHON_LIBRARIES := boost_python3 python3.6m
PYTHON_INCLUDE := /usr/include/python3.6m \
/usr/local/lib/python3.6/dist-packages/numpy/core/include
...
WITH_PYTHON_LAYER := 1
...
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial /usr/local/cuda/include /usr/local/include/opencv4
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu /usr/lib/x86_64-linux-gnu/hdf5/serial
编译caffe
$ make -j8
$ make pycaffe
一切顺利的话,生成的工具在build/tools
目录下。
错误处理
如果报错如下:
/usr/local/lib/libopencv_imgcodecs.so: undefined reference to `TIFFReadDirectory@LIBTIFF_4.0'
解决方案:
$ conda uninstall libtiff
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