② Capstone 컴퓨터 세팅

우선 YOLO를 사용하기 전에 컴퓨터를 세팅해보겠습니다.

• 현재 Ubuntu 18.04 와 CUDA 10.1는 설치되어 있습니다.

• cuDNN 7.5.0

  CUDA 10.1에서는 cuDNN 7.5.0만 사용가능합니다. (아래 링크에서 다운받으면 됩니다.)

 https://developer.nvidia.com/rdp/cudnn-download

  

   

$ cd "다운경로"
$ sudo tar -xzvf cudnn-10.1-linux-x64-v7.5.0.56.tgz
$ cd cuda
$ sudo cp include/cudnn.h /usr/local/cuda/include
$ sudo cp lib64/libcudnn* /usr/local/cuda/lib64
$ sudo chmod a+r /usr/local/cuda/lib64/libcudnn*
$ cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2

• openCV 3.2.0

1. 리눅스를 최신 상태로 업데이트

# Ubuntu 18.04에서 libjasper-dev 패기지를 설치하기 위해 저장소를 추가
$ sudo add-apt-repository "deb http://security.ubuntu.com/ubuntu xenial-security main"
$ sudo apt update
$ sudo apt upgrade
 
# Ubuntu 18.04 설치 후 추가적으로 필요한 코덱, 미디어 라이브러리를 설치
$ sudo apt install ubuntu-restricted-extras

2. 필요한 패키치 설치

# Build tools & required
$ sudo apt install build-essential cmake git pkg-config
 
# For still image
$ sudo apt install libjpeg-dev libtiff5-dev libjasper-dev libpng-dev
 
# For videos
$ sudo apt install libavcodec-dev libavformat-dev libswscale-dev 
$ sudo apt install libdc1394-22-dev libxvidcore-dev libx264-dev x264
$ sudo apt install libxine2-dev libv4l-dev v4l-utils
$ sudo apt install libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev
 
#GUI
$ sudo apt install libgtk-3-dev
 
# Optimization, Python3, etc.
$ sudo apt install libatlas-base-dev libeigen3-dev gfortran
$ sudo apt install python3-dev python3-numpy libtbb2 libtbb-dev

3.  OpenCV 3.2.0 소스 코드를 다운로드

# Create a working directory named opencv
$ cd ~
$ mkdir opencv
$ cd opencv
 
# Download sources
$ wget -O opencv-3.2.0.zip https://github.com/opencv/opencv/archive/3.2.0.zip
$ wget -O opencv_contrib-3.2.0.zip https://github.com/opencv/opencv_contrib/archive/3.2.0.zip
 
# Unpack
$ unzip opencv-3.2.0.zip
$ unzip opencv_contrib-3.2.0.zip

4. CMake를 이용해 Markfile을 생성

# Create a build directory
$ mkdir build && cd build
 
# Run CMake
$ cmake \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_INSTALL_PREFIX=/usr/local \
-D BUILD_WITH_DEBUG_INFO=OFF \
-D BUILD_EXAMPLES=ON \
-D BUILD_opencv_cudacodec=OFF \
-D BUILD_opencv_python2=OFF \
-D BUILD_opencv_python3=ON \
-D INSTALL_PYTHON_EXAMPLES=ON \
-D OPENCV_EXTRA_MODULES_PATH=../opencv_contrib-3.2.0/modules \
-D WITH_TBB=ON \
-D WITH_V4L=ON \
../opencv-3.2.0/ 2>&1 | tee cmake_messages.txt

5. 컴파일과 설치를 진행

# find out the number of CPU cores in your machine
$ nproc
 
# substitute 2 after -j by the output of nproc
$ make -j2 2>&1 | tee build_messages.txt
$ sudo make install
$ sudo ldconfig
 
# Package opencv was not found in the pkg-config search path라는 에러가 뜬 경우
$ sudo apt install apt-file
$ sudo apt-get install libopencv-dev
 
# If the output of next command is '3.2.0' then it's ok!
$ pkg-config --modversion opencv