8월12일 구글에서 이미지 크롤링, 우분투, opencv, yolo, yolo_mark 설치

내용 추가 예정입니다. 

 

파이썬 이미지 크롤링 하기

from google_images_download import google_images_download
 
from selenium import webdriver
 
path = "./chromedriver"
driver = webdriver.Chrome(path)
 
def imageCrawling(keyword, dir):
    response = google_images_download.googleimagesdownload()
 
    arguments ={"keywords":keyword,
                "limit":600,
                "print_urls":True,
                "no_directory":True,
                'output_directory':dir,
                'chromedriver':path
                }
 
    paths = response.download(arguments)
    print(paths)
 
if __name__ == "__main__":
    imageCrawling('cat','cat/') //키워드, 폴더명

 

우분투 18.04에서 opencv 설치에 여러가지 에러가 있어

우분투를 16.04 버전으로 다운그레이드했습니다.

 

ubuntu 16.04설치 후 아래 내용 실행

# ubuntu1604라는 문자열 생성

$ release="ubuntu"$(lsb_release -sr | sed -e "s/\.//g")

$ echo $release

 

#nvidia 드라이버를 위한 레포지터리 추가

$ sudo apt install sudo gnupg

$ sudo apt-key adv --fetch-keys "http://developer.download.nvidia.com/compute/cuda/repos/"$release"/x86_64/7fa2af80.pub"

$ sudo sh -c 'echo "deb http://developer.download.nvidia.com/compute/cuda/repos/'$release'/x86_64 /" > /etc/apt/sources.list.d/nvidia-cuda.list' $ sudo sh -c 'echo "deb http://developer.download.nvidia.com/compute/machine-learning/repos/'$release'/x86_64 /" > /etc/apt/sources.list.d/nvidia-machine-learning.list'

$ sudo apt update

 

$ apt-cache search nvidia

$ sudo apt-get install nvidia-418

 

#cuda 10.1설치

$ sudo apt-get install cuda-10-1

$ sudo apt-get install libcudnn7-dev

 

#cuda 10.1버전확인

$ cat /usr/local/cuda/version.txt

$reboot

 

#git vim패키지 설치

sudo apt-get install git vim

 

#darknet설치

git clone https://github.com/pjreddie/darknet

cd darknet

sudo vim Makefile

gpu=1

cudnn=1

opencv=1로 수정

 

vim ~/.bashrc에서 맨 아랫줄에 아래 내용 추가

export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}

export LD_LIBRARY_PATH=/usr/local/cuda/lib64\ {LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

source ~/.bashrc

sudo apt-get install libopencv-dev python-opencv ffmpeg

make

wget https://pjreddie.com/media/files/yolov3.weights

./darknet detect cfg/yolov3.cfg yolov3.weights data/dog.jpg

 

sudo apt-get update && sudo apt-get upgrade

sudo apt-get -y purge libopencv* python-opencv

sudo apt-get -y install build-essential cmake vim

sudo apt-get -y install pkg-config libjpeg-dev libtiff5-dev libjasper-dev libpng12-dev libavcodec-dev

sudo apt-get -y install libavformat-dev libswscale-dev libxvidcore-dev libx264-dev libxine2-dev libv4l-dev

sudo apt-get -y install v4l-utils libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libqt4-dev

sudo apt-get -y install libgtk2.0-dev libgtk-3-dev mesa-utils libgl1-mesa-dri libqt4-opengl-dev

sudo apt-get -y install libatlas-base-dev gfortran libeigen3-dev python3-dev python3-numpy python-dev python-numpy libatlas-base-dev gfortran

 

#opencv 설치

mkdir opencv-3.4.2

cd opencv-3.4.2

wget -O opencv.zip https://github.com/opencv/opencv/archive/3.4.2.zip

unzip opencv.zip

wget -O opencv_contrib.zip https://github.com/opencv/opencv_contrib/archive/3.4.2.zip

unzip opencv_contrib.zip

cd ~/opencv-3.4.2/

mkdir build

cd build

 

cmake -D CMAKE_BUILD_TYPE=RELEASE \ -D CMAKE_INSTALL_PREFIX=/usr/local \

-D WITH_TBB=OFF \

-D WITH_IPP=OFF \

-D WITH_1394=OFF \

-D BUILD_WITH_DEBUG_INFO=OFF \

-D BUILD_DOCS=OFF \

-D INSTALL_C_EXAMPLES=ON \

-D INSTALL_PYTHON_EXAMPLES=ON \

-D BUILD_EXAMPLES=OFF \

-D BUILD_TESTS=OFF \

-D BUILD_PERF_TESTS=OFF \

-D WITH_QT=OFF \

-D WITH_GTK=ON \

-D WITH_OPENGL=ON \

-D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib-3.4.2/modules \

-D WITH_V4L=ON \

-D WITH_FFMPEG=ON \

-D WITH_XINE=ON \

-D BUILD_NEW_PYTHON_SUPPORT=ON \

../

 

time make -j12

sudo make install

 

# YOLO mark설치

git clone https://github.com/AlexeyAB/Yolo_mark

cmake .

make

sudo chomd 777 linux_mark.sh

./linux_mark.sh

 

YOLO Mark에 관련된 추가 내용은 아래 블로그 참조 https://juni-94.tistory.com/10

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