C ++中的网络摄像头图像处理OpenCV很慢(Webcam Image Processing in C++ OpenCV is Slow)

我想用C ++ OpenCV模拟protanopia视图（部分色盲之一），使用网络摄像头来模拟它。 这里的代码：

#include "opencv2/opencv.hpp" using namespace cv; int main(int, char**) { int i = 0; Mat im, im2, kernel3; Mat rgb2lms = (Mat_<double>(3, 3) << 17.8824, 43.5161, 4.11935, 3.45565, 27.1554, 3.86714, 0.0299566, 0.184309, 1.46709); //filter1 Mat lms2lmsp = (Mat_<double>(3, 3) << 0, 2.02344, -2.52581, 0, 1, 0, 0, 0, 1); //filter2 Mat Result, Result2, op1, op2, op3, op4, op5, op6; Vec3b zay, zay2; kernel3 = rgb2lms.inv(DECOMP_LU); //filter 3 cv::Mat mat(3, 1, CV_64FC1); //create MAT for matrices multiplication Mat frame; VideoCapture cap(0); // open the default camera if (!cap.isOpened()) // check if we succeeded return -1; namedWindow("edges", 1); for (;;) { cap.read(frame); // get a new frame from camera if (frame.empty()) continue; const int nChannels = frame.channels(); if (i == 0){ Result.create(frame.size(), frame.type()); } //Result2.create(frame.size(), frame.type()); cvtColor(frame, im2, CV_BGR2RGB); //convert to RGB for (int i = 0; i < im2.rows; i++) { for (int j = 0; j < im2.cols; j++) { for (int k = 0; k < nChannels; k++) { zay(k) = im2.at<Vec3b>(i, j)[k]; //acces pixel value and put into 3x1 vector zay //put the value in to mat so i can multiplied with easy mat.at <double>(0, 0) = zay[0]; mat.at <double>(1, 0) = zay[1]; mat.at <double>(2, 0) = zay[2]; op1 = rgb2lms*mat; //apply filter1 op2 = lms2lmsp*op1; //apply filter2 op3 = kernel3*op2; //apply filter3 for (int k = 0; k < nChannels; k++) { Result.at<Vec3b>(i, j)[k] = op3.at<double>(k, 0); //put the result from vector to mat } } } cvtColor(Result, Result2, CV_RGB2BGR); //convert back to BGR imshow("hasil", Result2); if (waitKey(30) >= 0) break; i++; } // the camera will be deinitialized automatically in VideoCapture destructor return 0;

}

运行此代码，但图像视频输出非常慢（滞后）。 我是使用C ++的新手。 我的问题：

输出速度很慢，因为我使用了很多次迭代？ 我使用filter2D（卷积）尝试了这个过程，结果不同。 卷积是否与矩阵乘法滤波器不同？ 如何使输出顺利？ 我应该在该代码中使用指针吗？

谢谢

I want to simulate protanopia view (one of the partial colorblind) with C++ OpenCV using webcam to simulate it. Here the code:

#include "opencv2/opencv.hpp" using namespace cv; int main(int, char**) { int i = 0; Mat im, im2, kernel3; Mat rgb2lms = (Mat_<double>(3, 3) << 17.8824, 43.5161, 4.11935, 3.45565, 27.1554, 3.86714, 0.0299566, 0.184309, 1.46709); //filter1 Mat lms2lmsp = (Mat_<double>(3, 3) << 0, 2.02344, -2.52581, 0, 1, 0, 0, 0, 1); //filter2 Mat Result, Result2, op1, op2, op3, op4, op5, op6; Vec3b zay, zay2; kernel3 = rgb2lms.inv(DECOMP_LU); //filter 3 cv::Mat mat(3, 1, CV_64FC1); //create MAT for matrices multiplication Mat frame; VideoCapture cap(0); // open the default camera if (!cap.isOpened()) // check if we succeeded return -1; namedWindow("edges", 1); for (;;) { cap.read(frame); // get a new frame from camera if (frame.empty()) continue; const int nChannels = frame.channels(); if (i == 0){ Result.create(frame.size(), frame.type()); } //Result2.create(frame.size(), frame.type()); cvtColor(frame, im2, CV_BGR2RGB); //convert to RGB for (int i = 0; i < im2.rows; i++) { for (int j = 0; j < im2.cols; j++) { for (int k = 0; k < nChannels; k++) { zay(k) = im2.at<Vec3b>(i, j)[k]; //acces pixel value and put into 3x1 vector zay //put the value in to mat so i can multiplied with easy mat.at <double>(0, 0) = zay[0]; mat.at <double>(1, 0) = zay[1]; mat.at <double>(2, 0) = zay[2]; op1 = rgb2lms*mat; //apply filter1 op2 = lms2lmsp*op1; //apply filter2 op3 = kernel3*op2; //apply filter3 for (int k = 0; k < nChannels; k++) { Result.at<Vec3b>(i, j)[k] = op3.at<double>(k, 0); //put the result from vector to mat } } } cvtColor(Result, Result2, CV_RGB2BGR); //convert back to BGR imshow("hasil", Result2); if (waitKey(30) >= 0) break; i++; } // the camera will be deinitialized automatically in VideoCapture destructor return 0;

}

This code is run, but the image video output is very slow (lagging). i'm very new using C++. My Question:

Very slow output because i'm using many iterations? I have tried this process using filter2D (convolution) and the result is different. Is the convolution different with matrix multiplication filter? How to make the output smoothly? Should i use pointer in that code?

Thanks

最满意答案

Filter2D不适合您的任务。 它在图像的每个通道上应用卷积滤波器 ，而您想要的是在每个rgb像素上应用的线性转换矩阵。

您正在寻找的功能是变换 。

首先，为了获得更好的性能，将三个转换合并为一个全局转换矩阵：

Mat global_kernel = kernel3*lms2lmsp*rgb2lms;

然后，使用：而不是for循环，

transform(im2, Result, global_kernel);

如果您仍想保存几毫秒，也可以通过直接从bgr颜色空间应用转换来删除cvtColor函数调用。 只需切换rgb2lms矩阵的列：

Mat bgr2lms = (Mat_<double>(3, 3) << 4.11935, 43.5161, 17.8824, 3.86714, 27.1554, 3.45565, 1.46709, 0.184309, 0.0299566);

Filter2D is not the appropriate function for your task. It applies a convolution filter on each channel of the image, while what you want is a linear tranformation matrix applied on each rgb pixel.

The function you are looking for is transform.

First, for better performance, merge your three transformations into a single global transformation matrix:

Mat global_kernel = kernel3*lms2lmsp*rgb2lms;

Then, instead of your for loop, use:

transform(im2, Result, global_kernel);

If you still want to save a few milliseconds, you may also remove the cvtColor function calls by applying your transformation directly from bgr color space. Simply switch the columns of your rgb2lms matrix:

Mat bgr2lms = (Mat_<double>(3, 3) << 4.11935, 43.5161, 17.8824, 3.86714, 27.1554, 3.45565, 1.46709, 0.184309, 0.0299566);C ++中的网络摄像头图像处理OpenCV很慢(Webcam Image Processing in C++ OpenCV is Slow)

我想用C ++ OpenCV模拟protanopia视图（部分色盲之一），使用网络摄像头来模拟它。 这里的代码：

#include "opencv2/opencv.hpp" using namespace cv; int main(int, char**) { int i = 0; Mat im, im2, kernel3; Mat rgb2lms = (Mat_<double>(3, 3) << 17.8824, 43.5161, 4.11935, 3.45565, 27.1554, 3.86714, 0.0299566, 0.184309, 1.46709); //filter1 Mat lms2lmsp = (Mat_<double>(3, 3) << 0, 2.02344, -2.52581, 0, 1, 0, 0, 0, 1); //filter2 Mat Result, Result2, op1, op2, op3, op4, op5, op6; Vec3b zay, zay2; kernel3 = rgb2lms.inv(DECOMP_LU); //filter 3 cv::Mat mat(3, 1, CV_64FC1); //create MAT for matrices multiplication Mat frame; VideoCapture cap(0); // open the default camera if (!cap.isOpened()) // check if we succeeded return -1; namedWindow("edges", 1); for (;;) { cap.read(frame); // get a new frame from camera if (frame.empty()) continue; const int nChannels = frame.channels(); if (i == 0){ Result.create(frame.size(), frame.type()); } //Result2.create(frame.size(), frame.type()); cvtColor(frame, im2, CV_BGR2RGB); //convert to RGB for (int i = 0; i < im2.rows; i++) { for (int j = 0; j < im2.cols; j++) { for (int k = 0; k < nChannels; k++) { zay(k) = im2.at<Vec3b>(i, j)[k]; //acces pixel value and put into 3x1 vector zay //put the value in to mat so i can multiplied with easy mat.at <double>(0, 0) = zay[0]; mat.at <double>(1, 0) = zay[1]; mat.at <double>(2, 0) = zay[2]; op1 = rgb2lms*mat; //apply filter1 op2 = lms2lmsp*op1; //apply filter2 op3 = kernel3*op2; //apply filter3 for (int k = 0; k < nChannels; k++) { Result.at<Vec3b>(i, j)[k] = op3.at<double>(k, 0); //put the result from vector to mat } } } cvtColor(Result, Result2, CV_RGB2BGR); //convert back to BGR imshow("hasil", Result2); if (waitKey(30) >= 0) break; i++; } // the camera will be deinitialized automatically in VideoCapture destructor return 0;

}

运行此代码，但图像视频输出非常慢（滞后）。 我是使用C ++的新手。 我的问题：

输出速度很慢，因为我使用了很多次迭代？ 我使用filter2D（卷积）尝试了这个过程，结果不同。 卷积是否与矩阵乘法滤波器不同？ 如何使输出顺利？ 我应该在该代码中使用指针吗？

谢谢

I want to simulate protanopia view (one of the partial colorblind) with C++ OpenCV using webcam to simulate it. Here the code:

#include "opencv2/opencv.hpp" using namespace cv; int main(int, char**) { int i = 0; Mat im, im2, kernel3; Mat rgb2lms = (Mat_<double>(3, 3) << 17.8824, 43.5161, 4.11935, 3.45565, 27.1554, 3.86714, 0.0299566, 0.184309, 1.46709); //filter1 Mat lms2lmsp = (Mat_<double>(3, 3) << 0, 2.02344, -2.52581, 0, 1, 0, 0, 0, 1); //filter2 Mat Result, Result2, op1, op2, op3, op4, op5, op6; Vec3b zay, zay2; kernel3 = rgb2lms.inv(DECOMP_LU); //filter 3 cv::Mat mat(3, 1, CV_64FC1); //create MAT for matrices multiplication Mat frame; VideoCapture cap(0); // open the default camera if (!cap.isOpened()) // check if we succeeded return -1; namedWindow("edges", 1); for (;;) { cap.read(frame); // get a new frame from camera if (frame.empty()) continue; const int nChannels = frame.channels(); if (i == 0){ Result.create(frame.size(), frame.type()); } //Result2.create(frame.size(), frame.type()); cvtColor(frame, im2, CV_BGR2RGB); //convert to RGB for (int i = 0; i < im2.rows; i++) { for (int j = 0; j < im2.cols; j++) { for (int k = 0; k < nChannels; k++) { zay(k) = im2.at<Vec3b>(i, j)[k]; //acces pixel value and put into 3x1 vector zay //put the value in to mat so i can multiplied with easy mat.at <double>(0, 0) = zay[0]; mat.at <double>(1, 0) = zay[1]; mat.at <double>(2, 0) = zay[2]; op1 = rgb2lms*mat; //apply filter1 op2 = lms2lmsp*op1; //apply filter2 op3 = kernel3*op2; //apply filter3 for (int k = 0; k < nChannels; k++) { Result.at<Vec3b>(i, j)[k] = op3.at<double>(k, 0); //put the result from vector to mat } } } cvtColor(Result, Result2, CV_RGB2BGR); //convert back to BGR imshow("hasil", Result2); if (waitKey(30) >= 0) break; i++; } // the camera will be deinitialized automatically in VideoCapture destructor return 0;

}

This code is run, but the image video output is very slow (lagging). i'm very new using C++. My Question:

Very slow output because i'm using many iterations? I have tried this process using filter2D (convolution) and the result is different. Is the convolution different with matrix multiplication filter? How to make the output smoothly? Should i use pointer in that code?

Thanks

最满意答案

Filter2D不适合您的任务。 它在图像的每个通道上应用卷积滤波器 ，而您想要的是在每个rgb像素上应用的线性转换矩阵。

您正在寻找的功能是变换 。

首先，为了获得更好的性能，将三个转换合并为一个全局转换矩阵：

Mat global_kernel = kernel3*lms2lmsp*rgb2lms;

然后，使用：而不是for循环，

transform(im2, Result, global_kernel);

如果您仍想保存几毫秒，也可以通过直接从bgr颜色空间应用转换来删除cvtColor函数调用。 只需切换rgb2lms矩阵的列：

Mat bgr2lms = (Mat_<double>(3, 3) << 4.11935, 43.5161, 17.8824, 3.86714, 27.1554, 3.45565, 1.46709, 0.184309, 0.0299566);

Filter2D is not the appropriate function for your task. It applies a convolution filter on each channel of the image, while what you want is a linear tranformation matrix applied on each rgb pixel.

The function you are looking for is transform.

First, for better performance, merge your three transformations into a single global transformation matrix:

Mat global_kernel = kernel3*lms2lmsp*rgb2lms;

Then, instead of your for loop, use:

transform(im2, Result, global_kernel);

If you still want to save a few milliseconds, you may also remove the cvtColor function calls by applying your transformation directly from bgr color space. Simply switch the columns of your rgb2lms matrix:

Mat bgr2lms = (Mat_<double>(3, 3) << 4.11935, 43.5161, 17.8824, 3.86714, 27.1554, 3.45565, 1.46709, 0.184309, 0.0299566);