Update Feature
- Descending order sort in contours
- Processing to biggest contour area top 5
- Comparing to error distance of pixels mean
- Shortest error distance is best
Next Develop
- Size, HSV의 Balance 비교
- AdaptiveHSV 적용?
- AutoFocus 카메라 사용시 샤프닝 적용
#include <iostream>
#include <cmath>
#include <opencv2/opencv.hpp>
#define MIN_CONTOUR 3
#define COUNT_CONTOUR 5
using namespace std;
using namespace cv;
Mat frame;
Scalar meanHSV = Scalar(0, 0, 0);
bool comparePointVectors(const vector<Point>& a, const vector<Point>& b) {
return a.size() > b.size();
}
vector<vector<Point>> SortingArea(vector<vector<Point>> SortingContours) {
sort(SortingContours.begin(), SortingContours.end(), comparePointVectors);
return SortingContours;
}
Scalar pixels_avg(vector<Scalar> pixels) {
Scalar avgHSV(0, 0, 0);
for (int i = 0; i < pixels.size(); i++)
avgHSV += pixels[i];
avgHSV /= static_cast<float>(pixels.size());
return avgHSV;
}
int Close_HSV(vector<Scalar> Compare_HSV_List) {
int Close_HSV_Index = 0;
int Close_HSV_Dis, Close_HSV_Dis_List;
Scalar Close_HSV = Compare_HSV_List[0];
Scalar Close_HSV_Min, Close_HSV_Min_List, Close_HSV_List;
for (int i = 1; i < Compare_HSV_List.size(); i++) {
Close_HSV_Min = meanHSV - Close_HSV;
Close_HSV_Dis = abs(Close_HSV_Min[0]) + abs(Close_HSV_Min[1]) + abs(Close_HSV_Min[2]);
Close_HSV_Min_List = meanHSV - Compare_HSV_List[i];
Close_HSV_Dis_List = abs(Close_HSV_Min_List[0]) + abs(Close_HSV_Min_List[1]) + abs(Close_HSV_Min_List[2]);
if (Close_HSV_Dis > Close_HSV_Dis_List) {
Close_HSV = Compare_HSV_List[i];
Close_HSV_Index = i;
}
else continue;
}
return Close_HSV_Index;
}
void HSV_Process(Scalar lowerHSV, Scalar upperHSV) {
Mat hsv_frame, mask;
vector<Scalar> HSV_List;
cvtColor(frame, hsv_frame, COLOR_BGR2HSV);
inRange(hsv_frame, lowerHSV, upperHSV, mask);
imshow("mask", mask);
vector<vector<Point>> contours;
findContours(mask, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
contours = SortingArea(contours);
//cout << "contours : " << contours.size() << endl;
if (contours.size() > MIN_CONTOUR) {
for (int i = 0; i < COUNT_CONTOUR; i++) {
Mat contours_mask = Mat::zeros(hsv_frame.size(), CV_8UC1);
drawContours(contours_mask, contours, i, Scalar(255), -1);
//mean으로 가능은 할 듯
vector<Scalar> pixels;
for (int y = 0; y < contours_mask.rows; y++) {
for (int x = 0; x < contours_mask.cols; x++) {
if (contours_mask.at<uchar>(y, x) == 255) {
pixels.push_back(hsv_frame.at<Vec3b>(y, x));
}
}
}
HSV_List.push_back(pixels_avg(pixels));
}
int Close_Contour_Index = Close_HSV(HSV_List);
Rect boundRect = boundingRect(contours[Close_Contour_Index]);
drawContours(frame, contours, Close_Contour_Index, cv::Scalar(0, 255, 255), 1);
rectangle(frame, boundRect, Scalar(0, 255, 0), 2);
}
}
Scalar Push_Button(Rect2i roi_point) {
Mat hsv_frame;
hsv_frame = frame(roi_point).clone();
cvtColor(hsv_frame, hsv_frame, COLOR_BGR2HSV);
imshow("hsv_frame", hsv_frame);
return mean(hsv_frame);
}
Scalar AdaptiveHSVUpdate(Rect2i roi_point) {
Mat hsv_frame;
hsv_frame = frame(roi_point).clone();
cvtColor(hsv_frame, hsv_frame, COLOR_BGR2HSV);
return mean(hsv_frame);
}
int main() {
VideoCapture cap = VideoCapture(0);
if (!cap.isOpened()) {
cout << "Could't load camera" << endl;
return -1;
}
double width = cap.get(CAP_PROP_FRAME_WIDTH);
double height = cap.get(CAP_PROP_FRAME_HEIGHT);
namedWindow("frame");
int key;
int frameCount = 0;
Scalar dis_HSV = Scalar(32, 32, 32);
Scalar lowerHSV, upperHSV;
Rect2i roi_frame = Rect(Point(width / 5 * 2, height / 10 * 2), Point(width / 5 * 3, height / 10 * 8));
while (1) {
cap >> frame;
flip(frame, frame, 1);
if (frame.empty()) {
cout << "Could't load frame" << endl;
return -1;
}
//Raspberry Camera Mode//
//Mat gaussian_blur;
//GaussianBlur(frame, gaussian_blur, Size(9, 9), 5);
//Mat sharpened = frame - gaussian_blur;
//Mat result = frame + sharpened;
key = waitKey(10);
if (key == 27) break;
else if (key == 32) {
meanHSV = Push_Button(roi_frame);
cout << "meanHSV : " << meanHSV << endl;
lowerHSV = meanHSV - dis_HSV;
upperHSV = meanHSV + dis_HSV;
}
if (meanHSV[0] != 0 || meanHSV[1] != 0 || meanHSV[2] != 0) {
HSV_Process(lowerHSV, upperHSV);
}
rectangle(frame, roi_frame, Scalar(0, 0, 255), 2, 8);
imshow("frame", frame);
}
cap.release();
destroyAllWindows();
return 0;
}