版权声明:本文为博主原创文章,未经博主允许不得转载。 https://blog.csdn.net/wyansai/article/details/81043636
一、编译opencv
1、依赖安装
sudo apt-get install build-essential
sudo apt-get install cmake git libgtk2.0-dev pkg-config
sudo apt-get install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev
sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev liblapacke-dev
sudo apt-get install libxvidcore-dev libx264-dev
sudo apt-get install libatlas-base-dev gfortran
sudo apt-get install ffmpeg
2、源码下载
wget https://github.com/opencv/opencv/archive/3.2.0.zip
wget https://github.com/opencv/opencv_contrib/archive/3.2.0.zip
3、解压,并编译
cd opencv-3.2.0
mkdir build
cd build
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/home/php/opencvLib -D INSTALL_PYTHON_EXAMPLES=ON -D INSTALL_C_EXAMPLES=OFF -D OPENCV_EXTRA_MODULES_PATH=/home/php/opencv_contrib-3.2.0/modules -D PYTHON_EXCUTABLE=/home/php/opencvLib/bin/python -D WITH_TBB=ON -D WITH_V4L=ON -D WITH_GTK=ON -D WITH_OPENGL=ON -D BUILD_EXAMPLES=ON ..
make -j4
sudo make install
sudo /bin/bash -c 'echo "/home/php/opencvLib" > /etc/ld.so.conf.d/opencv.conf'
sudo ldconfig
PS:也可以直接使用下面的apt-get安装,不需要编译
sudo apt-get install libopencv-dev python-opencv
二、编写测试文件
1、编译命令:
g++ main.cpp -I /home/php/opencvLib/include -L /home/php/opencvLib/lib -lopencv_core -lopencv_highgui -lopencv_imgproc -lopencv_imgcodecs -o main
2、源码如下:
#include <iostream>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace cv;
using namespace std;
bool blurDetect(Mat srcImage);
int VideoBlurDetect(const cv::Mat &srcimg);
int aHash(Mat matSrc1, Mat matSrc2);
int main(int argc, char* argv[])
{
//图片模糊度检测
Mat img1 = imread("/home/php/setup/7.jpg");
double time = (double)getTickCount();
int flag = VideoBlurDetect(img1);
time = ((double)getTickCount() - time) / getTickFrequency();
cout << "模糊度:" << flag << "\n所用时间为:" << time << "s" << endl;
return 0;
/* Mat img1 = imread("D:/1.jpg");
Mat img2 = imread("D:/3.jpg");
int flag = aHash(img1, img2);
cout << "差别度:" << flag << endl;
system("pause");
return 0;*/
}
/*检测模糊度
返回值为模糊度,值越大越模糊,越小越清晰,范围在0到几十,10以下相对较清晰,一般为5。
调用时可在外部设定一个阀值,具体阈值根据实际情况决定,返回值超过阀值当作是模糊图片。
算法所耗时间在1毫秒内
*/
int VideoBlurDetect(const cv::Mat &srcimg)
{
cv::Mat img;
cv::cvtColor(srcimg, img, CV_BGR2GRAY); // 将输入的图片转为灰度图,使用灰度图检测模糊度
//图片每行字节数及高
int width = img.cols;
int height = img.rows;
ushort* sobelTable = new ushort[width*height];
memset(sobelTable, 0, width*height*sizeof(ushort));
int i, j, mul;
//指向图像首地址
uchar* udata = img.data;
for (i = 1, mul = i*width; i < height - 1; i++, mul += width)
for (j = 1; j < width - 1; j++)
sobelTable[mul + j] = abs(udata[mul + j - width - 1] + 2 * udata[mul + j - 1] + udata[mul + j - 1 + width] - \
udata[mul + j + 1 - width] - 2 * udata[mul + j + 1] - udata[mul + j + width + 1]);
for (i = 1, mul = i*width; i < height - 1; i++, mul += width)
for (j = 1; j < width - 1; j++)
if (sobelTable[mul + j] < 50 || sobelTable[mul + j] <= sobelTable[mul + j - 1] || \
sobelTable[mul + j] <= sobelTable[mul + j + 1]) sobelTable[mul + j] = 0;
int totLen = 0;
int totCount = 1;
uchar suddenThre = 50;
uchar sameThre = 3;
//遍历图片
for (i = 1, mul = i*width; i < height - 1; i++, mul += width)
{
for (j = 1; j < width - 1; j++)
{
if (sobelTable[mul + j])
{
int count = 0;
uchar tmpThre = 5;
uchar max = udata[mul + j] > udata[mul + j - 1] ? 0 : 1;
for (int t = j; t > 0; t--)
{
count++;
if (abs(udata[mul + t] - udata[mul + t - 1]) > suddenThre)
break;
if (max && udata[mul + t] > udata[mul + t - 1])
break;
if (!max && udata[mul + t] < udata[mul + t - 1])
break;
int tmp = 0;
for (int s = t; s > 0; s--)
{
if (abs(udata[mul + t] - udata[mul + s]) < sameThre)
{
tmp++;
if (tmp > tmpThre) break;
}
else break;
}
if (tmp > tmpThre) break;
}
max = udata[mul + j] > udata[mul + j + 1] ? 0 : 1;
for (int t = j; t < width; t++)
{
count++;
if (abs(udata[mul + t] - udata[mul + t + 1]) > suddenThre)
break;
if (max && udata[mul + t] > udata[mul + t + 1])
break;
if (!max && udata[mul + t] < udata[mul + t + 1])
break;
int tmp = 0;
for (int s = t; s < width; s++)
{
if (abs(udata[mul + t] - udata[mul + s]) < sameThre)
{
tmp++;
if (tmp > tmpThre) break;
}
else break;
}
if (tmp > tmpThre) break;
}
count--;
totCount++;
totLen += count;
}
}
}
//模糊度
float result = (float)totLen / totCount;
delete[] sobelTable;
sobelTable = NULL;
return result;
}
int aHash(Mat matSrc1, Mat matSrc2)
{
Mat matDst1, matDst2;
cv::resize(matSrc1, matDst1, cv::Size(8, 8), 0, 0, cv::INTER_CUBIC);
cv::resize(matSrc2, matDst2, cv::Size(8, 8), 0, 0, cv::INTER_CUBIC);
cv::cvtColor(matDst1, matDst1, CV_BGR2GRAY);
cv::cvtColor(matDst2, matDst2, CV_BGR2GRAY);
int iAvg1 = 0, iAvg2 = 0;
int arr1[64], arr2[64];
for (int i = 0; i < 8; i++)
{
uchar* data1 = matDst1.ptr<uchar>(i);
uchar* data2 = matDst2.ptr<uchar>(i);
int tmp = i * 8;
for (int j = 0; j < 8; j++)
{
int tmp1 = tmp + j;
arr1[tmp1] = data1[j] / 4 * 4;
arr2[tmp1] = data2[j] / 4 * 4;
iAvg1 += arr1[tmp1];
iAvg2 += arr2[tmp1];
}
}
iAvg1 /= 64;
iAvg2 /= 64;
for (int i = 0; i < 64; i++)
{
arr1[i] = (arr1[i] >= iAvg1) ? 1 : 0;
arr2[i] = (arr2[i] >= iAvg2) ? 1 : 0;
}
int iDiffNum = 0;
for (int i = 0; i < 64; i++)
if (arr1[i] != arr2[i])
++iDiffNum;
return iDiffNum;
}