Opencv C++ Crop Image basée sur les changements de coins

Question

J'ai posé une question similaire mais pour python en utilisant un tableau numpy Opencv Python Crop Image Using Numpy Array. Je cherche à recadrer une image basée sur ses coins. Voici une photo pour démontrer l'objectif.

J'ai un code python qui fait l'affaire mais qui doit le convertir en C++. Ce qui suit est mon code python de travail et le code C++ partiel respectivement.

def crop(self,image): 
    grayed = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY) 
    (_,thresh) = cv2.threshold(grayed,1,255,cv2.THRESH_BINARY) 
    result, contours, _= cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) 
    x, y = [], [] 
    for i in range(len(contours)): 
     for j in range(len(contours[i])): 
      x.append(contours[i][j][0][0]) 
      y.append(contours[i][j][0][1]) 
    x1, x2, y1, y2 = min(x), max(x), min(y), max(y) 
    cropped = image[y1:y2, x1:x2] 
    return cropped 

C++ code:

Mat crop(Mat image){ 
    Mat cropped, grayed, thresh, result; 
    vector<vector<Point>> contours; 
    vector<Vec4i> hierarchy; 
    cvtColor(image, grayed, CV_BGR2GRAY); 
    threshold(grayed, thresh, 1, 255,THRESH_BINARY); 
    findContours(thresh, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE); 

    std::vector<int> x,y; 
    cout << contours.size() << endl; 
    for(int i=0; i < contours.size();i++){ 
     for(int j = 0; j < contours.at(i).size();j++){ 
      x.push_back(contours.at(i).at(j).x); 
      y.push_back(contours.at(i).at(j).y); 
     } 
    } 

    cout << x.size() << endl; 
    cout << y.size() << endl; 

    vector<int>::iterator it = max(begin(x), end(x)); 
    int x1 = (*it); 
    it = max(begin(x), end(x)); 
    int x2 = *it; 
    it = min(begin(y), end(y)); 
    int y1 = *it; 
    it = max(begin(y), end(y)); 
    int y2 = *it; 

    cout << x1 << " " << x2 << " " << y1 << "  " << y2 << endl; 

    Rect rect (x1,y1,x2-x1,y2-y1); 
    cropped = image(rect); 
    return cropped; 
} 

Answer 1

Mat crop(Mat image){ 
Mat cropped, grayed, thresh, result; 
vector<vector<Point>> contours; 
vector<Vec4i> hierarchy; 
cvtColor(image, grayed, CV_BGR2GRAY); 
threshold(grayed, thresh, 1, 255,THRESH_BINARY); 
findContours(thresh, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE); 

vector<int> x,y; 
for(int i=0; i < contours.size();i++){ 
    for(int j = 0; j < contours.at(i).size();j++){ 
     x.push_back(contours[i][j].x); 
     y.push_back(contours[i][j].y); 
    } 
} 

auto xVals = std::minmax_element(x.begin(), x.end()); 
auto yVals = std::minmax_element(y.begin(), y.end()); 

Rect rect (*xVals.first,*yVals.first,(*xVals.second)-(*xVals.first),(*yVals.second)-(*yVals.first)); 
cropped = image(rect); 
return cropped; 

}

Answer 2

cv::Mat crop(cv::Mat image){ 
    cv::Mat cropped, grayed, thresh, result; 
    std::vector < std::vector <cv::Point>> contours; 
    std::vector<cv::Vec4i> hierarchy; 
    cvtColor(image, grayed, cv::COLOR_BGR2GRAY); 
    threshold(grayed, thresh, 1, 255, cv::THRESH_BINARY); 
    findContours(result, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, cv::Point(0, 0)); 
    std::vector<int> x, y; 

    for (int i = 0; i < contours.size(); i++){ 
     for (int j = 0; j <= contours.at(i).size(); j++){ 
      x.push_back(contours.at(i).at(j).x); 
      y.push_back(contours.at(i).at(j).y); 
     } 
    } 
    int x1 = std::min_element(x.begin(), x.end()); 
    int x2 = std::max_element(x.begin(), x.end()); 
    int y1 = std::min_element(y.begin(), y.end()); 
    int y2 = std::max_element(y.begin(), y.end()) 

    cv::Rect rect(x1, y1, x2 - x1, y2 - y1); 
    cropped = image(rect); 

    return cropped; 
} 

Essayez cette