网站安全 扫描,怎么制作商城小程序,合肥房产网二手房出售,php网站后台忘记密码OpenCV基本数据类型实战 〇、实战内容1 OpenCV helloworld1.1 文件结构类型1.2 CMakeList.txt1.3 Helloworld 2. Image的基本操作3. OpenCV 基本数据类型4. 读取图片的像素 遍历图片4.1 获取制定像素4.2 遍历图片 5. 图片反色5.1 方法1 #xff1a;遍历5.2 方法2 #… OpenCV基本数据类型实战 〇、实战内容1 OpenCV helloworld1.1 文件结构类型1.2 CMakeList.txt1.3 Helloworld 2. Image的基本操作3. OpenCV 基本数据类型4. 读取图片的像素 遍历图片4.1 获取制定像素4.2 遍历图片 5. 图片反色5.1 方法1 遍历5.2 方法2 矩阵减法 6. 矩阵基本运算 〇、实战内容
OpenCV helloworldImage的基本操作OpenCV 基本数据类型遍历图片读取图片的像素图片反色矩阵基本操作
1 OpenCV helloworld
1.1 文件结构类型
assign_1build [cmake build所用]assign_1.cppCMakeLists.txtimg.webp图片地址
1.2 CMakeList.txt
cmake_minimum_required(VERSION 3.10)
set(CMAKE_CXX_STANDARD 11)
set(CMAKE_CXX_STANDARD_REQUIRED True)
project(assign1)
find_package(OpenCV 3 REQUIRED HINTS /usr/local/opt/opencv3)
add_executable(assign1 assign_1.cpp)
target_link_libraries(assign1 ${OpenCV_LIBS})cmake 3.10版本使用C 11project 名字为assign1find_package寻找opencv3库 1.3 Helloworld
assign_1.cpp
#include opencv2/opencv.hpp
#include iostream
#include vector
#include stringusing namespace cv;
using namespace std;int main(int argc, char *argv[])
{Mat image imread(/Users/..../computerphotography/course_zhengjiangdaxue/opencv-logo.png); // 载入名为 opencv-logo.png 的图片namedWindow(hello); // 创建一个标题为 hello 的窗口imshow(hello, result); // 在窗口 hello 中显示图片waitKey(0); // 等待用户按下键盘destroyWindow(hello); // 销毁窗口 helloreturn 0;
}2. Image的基本操作
#include opencv2/opencv.hpp
#include iostream
#include vector
#include string
using namespace cv;
using namespace std;int main(int argc, char *argv[])
{Mat image imread(/Users/..../computerphotography/course_zhengjiangdaxue/opencv-logo.png); // 载入名为 opencv-logo.png 的图片cout image size 1: image.size() endl;cout image 行数: image.rows endl;cout image 列数: image.cols endl;cout image 通道数: image.channels() endl;cout image type: image.type() endl;return 0;
}输出结果
image size 1: [200 x 200]
image 行数: 200
image 列数: 200
image 通道数: 3
image type: 163. OpenCV 基本数据类型
int main(int argc, char *argv[])
{cout CV_8UC1: CV_8UC1 endl;cout CV_8UC2: CV_8UC2 endl;cout CV_8UC3: CV_8UC3 endl;cout CV_8UC4: CV_8UC4 endl;cout CV_8UC5: CV_8UC(5) endl;cout CV_8SC1: CV_8SC1 endl;cout CV_8SC2: CV_8SC2 endl;cout CV_8SC3: CV_8SC3 endl;cout CV_8SC4: CV_8SC4 endl;cout CV_8SC5: CV_8SC(5) endl;cout CV_16UC1: CV_16UC1 endl;cout CV_16UC2: CV_16UC2 endl;cout CV_16UC3: CV_16UC3 endl;cout CV_16UC4: CV_16UC4 endl;cout CV_16UC5: CV_16UC(5) endl;cout CV_16SC1: CV_16SC1 endl;cout CV_32SC1: CV_32SC1 endl;cout CV_32FC1: CV_32FC1 endl;cout CV_64FC1: CV_64FC1 endl;
}输出结果
CV_8UC1:0
CV_8UC2:8
CV_8UC3:16
CV_8UC4:24
CV_8UC5:32
CV_8SC1:1
CV_8SC2:9
CV_8SC3:17
CV_8SC4:25
CV_8SC5:33
CV_16UC1:2
CV_16UC2:10
CV_16UC3:18
CV_16UC4:26
CV_16UC5:34
CV_16SC1:3
CV_32SC1:4
CV_32FC1:5
CV_64FC1:6CV_8UC1 8字节无符号类型通道为1CV_8UC3 8字节无符号类型通道为3 即一个长度为3的数据例如[255,255,255] 三通道基本代表R, G, Bimage.type() 16 CV_8UC3 即改图片是3通道单通道增加一通道值增加8 CV_8UC1-0 - uchar CV_8SC1-1 - char CV_16UC1-2 - ushort CV_16SC1-3 - short CV_32SC1-4 - int CV_32FC1-5 - float CV_64FC1-6 - double 4. 读取图片的像素 遍历图片
4.1 获取制定像素
int main(int argc, char *argv[])
{// 3. 获取某一个像素值cout image at 0: image.atVec3b(0) endl;cout image at 10000000: image.atVec3b(10000000) endl;cout image at 39999: image.atVec3b(39999) endl;cout image at 199,199: image.atVec3b(199, 199) endl;}
输出
image at 0: [255, 255, 255]
image at 10000000: [0, 0, 0]
image at 39999: [255, 255, 255]
image at 199,199: [255, 255, 255]at方法 a. 需要制定对应的类型单通道见Section3 说明二通道Vec2b Vec2i Vec2f Vec2d b. 参数可为1个200 * 200 即 0index 39999参数为2个则对应的行和列超出索引也可获取值 4.2 遍历图片
int main(int argc, char *argv[])
{// //5. 遍历图片像素方法1便利判断是白色赋值为黑色for(int i 0;iimage.rows;i){for(int j0;jimage.cols;j){if(image.atVec3b(i,j) white){image.atVec3b(i,j) black;}}}}5. 图片反色
5.1 方法1 遍历
int main(int argc, char *argv[])
{Vec3b white(255, 255, 255);for(int i 0;iimage.rows;i){for(int j0;jimage.cols;j){image.atVec3b(i,j) white - image.atVec3b(i,j);}}
}定义白色Vec3b white(255, 255, 255);遍历图片用white减去每个像素颜色 5.2 方法2 矩阵减法 Mat m(image.rows,image.cols,CV_8UC3,Scalar(255,255,255));image m-image;Mat 代表opencv里的矩阵初始化的时候传入行数列数每个像素的数据格式以及初始值 a. 如果CV_8UC1 就是Scalar(255) b. 如果CV_8UC2 就是Scalar(255, 255)初始化了一个CV_8UC3 和原始图片一样大的矩阵然后做减法 6. 矩阵基本运算
int main(){Mat origin(10, 10, CV_32FC1, Scalar(0));for (int i 0; i 10; i){for (int j 0; j 10; j){if (i j){cout i i j j endl;origin.atfloat(i, j) 2.0;}else if ((i j - 1) || (i j 1)){origin.atfloat(i, j) -1.0;}}}// 矩阵 的逆Mat invert origin.inv();cout origin mat:endl;print(origin);cout endlinvert mat:endl;print(invert);//矩阵加法cout endl add mat:endl;origin origininvert;print(origin);//矩阵乘法cout endl multiply mat:endl;origin origin*invert;print(origin);//初始化对角线cout endl eye mat:endl;Mat eye Mat::eye(10,10,CV_32FC1);print(eye);cout endl normalize mat:endl;Mat result;//归一化最大的位白色最小的为黑色normalize(invert, result, 1.0, 0.0, CV_MINMAX);// 现实窗口逻辑print(result);cout endl;return 0;
}输出结果
origin mat:
[2, -1, 0, 0, 0, 0, 0, 0, 0, 0;-1, 2, -1, 0, 0, 0, 0, 0, 0, 0;0, -1, 2, -1, 0, 0, 0, 0, 0, 0;0, 0, -1, 2, -1, 0, 0, 0, 0, 0;0, 0, 0, -1, 2, -1, 0, 0, 0, 0;0, 0, 0, 0, -1, 2, -1, 0, 0, 0;0, 0, 0, 0, 0, -1, 2, -1, 0, 0;0, 0, 0, 0, 0, 0, -1, 2, -1, 0;0, 0, 0, 0, 0, 0, 0, -1, 2, -1;0, 0, 0, 0, 0, 0, 0, 0, -1, 2]
invert mat:
[0.90909088, 0.81818181, 0.72727281, 0.63636357, 0.54545444, 0.45454538, 0.36363626, 0.27272728, 0.18181814, 0.090909071;0.81818181, 1.6363636, 1.4545456, 1.2727271, 1.0909089, 0.90909076, 0.72727251, 0.54545456, 0.36363629, 0.18181814;0.72727281, 1.4545456, 2.1818185, 1.9090908, 1.6363634, 1.3636361, 1.0909088, 0.81818181, 0.54545444, 0.27272722;0.63636369, 1.2727274, 1.909091, 2.5454543, 2.1818178, 1.8181814, 1.4545449, 1.090909, 0.72727257, 0.36363629;0.54545456, 1.0909091, 1.6363636, 2.1818178, 2.7272723, 2.2727268, 1.8181812, 1.3636363, 0.9090907, 0.45454535;0.45454544, 0.90909088, 1.3636363, 1.8181814, 2.2727268, 2.7272723, 2.1818175, 1.6363635, 1.0909089, 0.54545444;0.36363637, 0.72727275, 1.090909, 1.4545451, 1.8181815, 2.1818178, 2.545454, 1.9090909, 1.2727271, 0.63636357;0.27272728, 0.54545456, 0.81818181, 1.0909089, 1.3636363, 1.6363634, 1.9090906, 2.1818182, 1.4545454, 0.72727269;0.18181817, 0.36363634, 0.54545456, 0.72727257, 0.90909082, 1.0909089, 1.2727271, 1.4545454, 1.6363635, 0.81818175;0.090909094, 0.18181819, 0.27272728, 0.36363631, 0.45454541, 0.54545444, 0.63636357, 0.72727275, 0.81818175, 0.90909088]
add mat:
[2.909091, -0.18181819, 0.72727281, 0.63636357, 0.54545444, 0.45454538, 0.36363626, 0.27272728, 0.18181814, 0.090909071;-0.18181819, 3.6363635, 0.45454562, 1.2727271, 1.0909089, 0.90909076, 0.72727251, 0.54545456, 0.36363629, 0.18181814;0.72727281, 0.45454562, 4.1818185, 0.90909076, 1.6363634, 1.3636361, 1.0909088, 0.81818181, 0.54545444, 0.27272722;0.63636369, 1.2727274, 0.909091, 4.545454, 1.1818178, 1.8181814, 1.4545449, 1.090909, 0.72727257, 0.36363629;0.54545456, 1.0909091, 1.6363636, 1.1818178, 4.727272, 1.2727268, 1.8181812, 1.3636363, 0.9090907, 0.45454535;0.45454544, 0.90909088, 1.3636363, 1.8181814, 1.2727268, 4.727272, 1.1818175, 1.6363635, 1.0909089, 0.54545444;0.36363637, 0.72727275, 1.090909, 1.4545451, 1.8181815, 1.1818178, 4.545454, 0.90909088, 1.2727271, 0.63636357;0.27272728, 0.54545456, 0.81818181, 1.0909089, 1.3636363, 1.6363634, 0.90909064, 4.181818, 0.45454538, 0.72727269;0.18181817, 0.36363634, 0.54545456, 0.72727257, 0.90909082, 1.0909089, 1.2727271, 0.45454538, 3.6363635, -0.18181825;0.090909094, 0.18181819, 0.27272728, 0.36363631, 0.45454541, 0.54545444, 0.63636357, 0.72727275, -0.18181825, 2.909091]
multiply mat:
[4.181818, 5.4545455, 6.909091, 7.6363621, 7.7272706, 7.2727251, 6.3636341, 5.0909085, 3.5454535, 1.8181813;5.454545, 11.090909, 13.090909, 14.63636, 14.909087, 14.090905, 12.363631, 9.9090891, 6.9090891, 3.5454535;6.9090915, 13.09091, 18.818182, 20.363632, 20.999994, 19.999994, 17.636356, 14.181816, 9.9090881, 5.0909076;7.636363, 14.636362, 20.363634, 25.18181, 25.454536, 24.545444, 21.818171, 17.63636, 12.363632, 6.3636341;7.727272, 14.909089, 20.999996, 25.454536, 28.727262, 27.272717, 24.545443, 19.999994, 14.090904, 7.2727246;7.2727261, 14.090907, 19.999996, 24.545444, 27.272717, 28.727262, 25.454533, 20.999994, 14.909085, 7.7272701;6.3636355, 12.363635, 17.636362, 21.818174, 24.545446, 25.454536, 25.181808, 20.363632, 14.63636, 7.6363616;5.090909, 9.90909, 14.181817, 17.636358, 19.999994, 20.999994, 20.36363, 18.81818, 13.090906, 6.9090896;3.5454543, 6.9090905, 9.90909, 12.363633, 14.090905, 14.909086, 14.636359, 13.090907, 11.090907, 5.4545441;1.8181818, 3.5454545, 5.090909, 6.3636351, 7.2727256, 7.7272706, 7.6363616, 6.9090905, 5.4545445, 4.181818]
eye mat:
[1, 0, 0, 0, 0, 0, 0, 0, 0, 0;0, 1, 0, 0, 0, 0, 0, 0, 0, 0;0, 0, 1, 0, 0, 0, 0, 0, 0, 0;0, 0, 0, 1, 0, 0, 0, 0, 0, 0;0, 0, 0, 0, 1, 0, 0, 0, 0, 0;0, 0, 0, 0, 0, 1, 0, 0, 0, 0;0, 0, 0, 0, 0, 0, 1, 0, 0, 0;0, 0, 0, 0, 0, 0, 0, 1, 0, 0;0, 0, 0, 0, 0, 0, 0, 0, 1, 0;0, 0, 0, 0, 0, 0, 0, 0, 0, 1]
normalize mat:
[0.31034487, 0.27586213, 0.24137938, 0.20689656, 0.17241378, 0.13793103, 0.10344826, 0.068965539, 0.034482758, 1.3546499e-09;0.27586213, 0.58620697, 0.51724154, 0.44827589, 0.37931034, 0.31034482, 0.24137928, 0.17241383, 0.10344827, 0.034482758;0.24137938, 0.51724154, 0.79310369, 0.68965524, 0.58620691, 0.48275861, 0.37931028, 0.27586213, 0.17241378, 0.068965517;0.2068966, 0.44827598, 0.6896553, 0.93103451, 0.7931034, 0.65517235, 0.51724124, 0.37931037, 0.24137929, 0.10344827;0.17241383, 0.37931043, 0.58620697, 0.7931034, 1, 0.82758617, 0.65517229, 0.48275867, 0.31034482, 0.13793102;0.13793106, 0.31034487, 0.48275867, 0.65517235, 0.82758617, 1, 0.79310334, 0.58620691, 0.37931034, 0.17241378;0.1034483, 0.24137937, 0.37931037, 0.51724136, 0.65517241, 0.7931034, 0.93103445, 0.68965524, 0.44827589, 0.20689656;0.068965539, 0.17241383, 0.27586213, 0.37931034, 0.48275867, 0.58620691, 0.68965518, 0.79310358, 0.51724142, 0.24137934;0.03448277, 0.10344829, 0.17241383, 0.24137929, 0.31034485, 0.37931034, 0.44827589, 0.51724142, 0.58620691, 0.2758621;9.8328981e-09, 0.034482773, 0.068965539, 0.10344828, 0.13793105, 0.17241378, 0.20689656, 0.24137937, 0.2758621, 0.31034487]
a123456lucky build %
