cv_posterization_sample.cpp

#pragma once

#include <SDKDDKVer.h>
#define WIN32_LEAN_AND_MEAN
#include <Windows.h>

#include <vector>

#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>

#ifdef _DEBUG
#pragma comment(lib, "opencv_core247d.lib")
#pragma comment(lib, "opencv_imgproc247d.lib")
#pragma comment(lib, "opencv_highgui247d.lib")
#else
#pragma comment(lib, "opencv_core247.lib")
#pragma comment(lib, "opencv_imgproc247.lib")
#pragma comment(lib, "opencv_highgui247.lib")
#endif

//
// see also... https://github.com/nkint/OF_sketches/blob/master/Posterize/src/Posterizer.cpp
//
cv::Mat segment(cv::Mat src, const int &k_size) {
	int cols = src.cols;
	int rows = src.rows;
	int numpix = cols*rows;

	cv::Mat clustered, colored, bestLabels, centers, samples;

	int *colors= new int[k_size];
	for(int i = 0;i < k_size;i++){
		colors[i] = 255 / (i + 1);
	}

	src.convertTo(samples, CV_32FC3);
	samples = samples.reshape(3, samples.rows*samples.cols);

	cv::kmeans(samples, k_size, bestLabels,
		cv::TermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 10, 1.0),
		1, cv::KMEANS_PP_CENTERS, centers);

	clustered = cv::Mat(rows, cols, CV_32F);
	for(int i = 0;i < numpix;i++){
		int label = bestLabels.at<int>(0, i);
		clustered.at<float>(i / cols, i % cols) = (float)((colors[label]));
	}

	clustered.convertTo(clustered, CV_8U);

	delete colors;
	colors = NULL;

	return clustered;
}

cv::Mat posterize(cv::Mat &src, const int &k_size)
{
	cv::Mat blurred_img;
	cv::blur(src, blurred_img, cv::Size(16, 16));

	cv::Mat clustered_img = segment(blurred_img, k_size);

	cv::erode(clustered_img, clustered_img, cv::Mat());
	cv::dilate(clustered_img, clustered_img, cv::Mat());

	cv::Mat result_img = cv::Mat(src.rows, src.cols, CV_8UC3);

	for(int i = 0;i < k_size;i++){
		cv::Mat mask;
		cv::Scalar meanColor;
		int color = 255 / (i + 1);

		cv::inRange(clustered_img, color - 1, color + 1, mask);
		meanColor = cv::mean(src, mask);

		if(src.channels() == 1) {
			meanColor = cv::Scalar(meanColor[0], meanColor[0], meanColor[0]);
		}

		result_img.setTo(meanColor, mask);
	}

	return result_img;
}

int main(int argc, char* argv[])
{
	cv::VideoCapture capture;
	if (capture.open(0) == false) {
		printf("error: capture.open() failed...\n");
		return -1;
	}

	cv::Rect roi(160, 120, 320, 240);

	cv::Mat capture_img, scaled_img, postalization_img, result_img;
	while(true) {
		capture.grab();
		capture >> capture_img;

		cv::Mat roi_img = capture_img(roi);
		cv::Mat scaled_img;
		cv::resize(roi_img, scaled_img, cv::Size(roi_img.cols/4, roi_img.rows/4));

		postalization_img = posterize(scaled_img, 16);

		cv::resize(postalization_img, result_img, cv::Size(postalization_img.cols*2, postalization_img.rows*2));

		// draw
		cv::rectangle(capture_img, roi, CV_RGB(0,255,0), 2);
		cv::imshow("capture_img", capture_img);
		cv::imshow("result_img", result_img);

		int c = cv::waitKey(1);
		if (c == 27) break;
	}

	cv::destroyAllWindows();

	return 0;
}