转换C++ OpenCV的Python的

Question

我想删除我的图像水平和垂直线条看起来像这样：

虽然google搜索，我发现，我认为可能的工作的解决方案：Extract horizontal and vertical lines by using morphological operations，但是，它是在C++ 。

我已经尝试将解决方案转换为Python，但我没有得到相同的结果。为了保持图像一样，我已经尽我的Python版本在该解决方案中使用的相同的图像：

下面是我的Python版本有关C++版本中的注释：

img = cv2.imread(path) 
    img=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) 

    #// Apply adaptiveThreshold at the bitwise_not of gray, notice the ~ symbol 
    #Mat bw; 
    #adaptiveThreshold(~gray, bw, 255, CV_ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 15, -2); 
    th2 = cv2.adaptiveThreshold(img,255, cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,15,-2) 
    cv2.imwrite("th2.jpg", th2) 

    #Mat horizontal = bw.clone(); 
    #Mat vertical = bw.clone(); 
    horizontal = th2 
    vertical = th2 

    #int horizontalsize = horizontal.cols/30; 
    rows,cols = horizontal.shape 
    horizontalsize = cols/30 

    #// Create structure element for extracting horizontal lines through morphology operations 
    #Mat horizontalStructure = getStructuringElement(MORPH_RECT, Size(horizontalsize,1)); 
    horizontalStructure = cv2.getStructuringElement(cv2.MORPH_RECT, (horizontalsize,1)) 

    #// Apply morphology operations 
    #erode(horizontal, horizontal, horizontalStructure, Point(-1, -1)); 
    #dilate(horizontal, horizontal, horizontalStructure, Point(-1, -1)); 
    #// Show extracted horizontal lines 
    #imshow("horizontal", horizontal); 
    horizontal = cv2.erode(horizontal, horizontalStructure, (-1, -1)) 
    horizontal = cv2.dilate(horizontal, horizontalStructure, (-1, -1)) 
    cv2.imwrite("horizontal.jpg", horizontal) 

    #// Specify size on vertical axis 
    #int verticalsize = vertical.rows/30; 
    verticalsize = rows/30 

    #// Create structure element for extracting vertical lines through morphology operations 
    #Mat verticalStructure = getStructuringElement(MORPH_RECT, Size(1,verticalsize)); 
    verticalStructure = cv2.getStructuringElement(cv2.MORPH_RECT, (1, verticalsize)) 

    #// Apply morphology operations 
    #erode(vertical, vertical, verticalStructure, Point(-1, -1)); 
    #dilate(vertical, vertical, verticalStructure, Point(-1, -1)); 
    #// Show extracted vertical lines 
    #imshow("vertical", vertical); 

    vertical = cv2.erode(vertical, verticalStructure, (-1, -1)) 
    vertical = cv2.dilate(vertical, verticalStructure, (-1, -1)) 
    cv2.imwrite("vertical.jpg", vertical) 

    #// Inverse vertical image 
    #bitwise_not(vertical, vertical); 
    #imshow("vertical_bit", vertical); 

    vertical = cv2.bitwise_not(vertical) 
    cv2.imwrite("vertical_bit.jpg", vertical) 

    #// Extract edges and smooth image according to the logic 
    #// 1. extract edges 
    #// 2. dilate(edges) 
    #// 3. src.copyTo(smooth) 
    #// 4. blur smooth img 
    #// 5. smooth.copyTo(src, edges) 


    #step1 
    #Mat edges; 
    #adaptiveThreshold(vertical, edges, 255, CV_ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 3, -2); 
    #imshow("edges", edges); 
    edges = cv2.adaptiveThreshold(vertical,255, cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,3,-2) 
    cv2.imwrite("edges.jpg", edges) 

    #step2 
    #Mat kernel = Mat::ones(2, 2, CV_8UC1); 
    #dilate(edges, edges, kernel); 
    #imshow("dilate", edges); 
    kernel = np.ones((2, 2), dtype = "uint8") 
    dilated = cv2.dilate(edges, kernel) 
    cv2.imwrite("dialted.jpg", dilated) 

    # step3 
    #Mat smooth; 
    #vertical.copyTo(smooth); 
    smooth = vertical.copy() 

    #step 4 
    #blur(smooth, smooth, Size(2, 2)); 
    smooth = cv2.blur(smooth, (2,2)) 

    #step 5 
    #smooth.copyTo(vertical, edges); 
    (rows, cols) = np.where(edges != 0) 
    vertical[rows, cols] = smooth[rows, cols] 

    // Show final result 
    #imshow("smooth", vertical); 
    cv2.imwrite("smooth.jpg", vertical) 

当我在

运行此我回来

这是没有结果的搜索解决方案上面链接得到。

我相信这个问题可能是在我的转换本的C++行：

// Apply adaptiveThreshold at the bitwise_not of gray, notice the ~ symbol 
    Mat bw; 
    adaptiveThreshold(~gray, bw, 255, CV_ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 15, -2); 

到这条巨蟒线

th2 = cv2.adaptiveThreshold(img,255, cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,15,-2) 

问题

我怎样才能最好地转换成C++代码链接到Python的解决方案？

Answer 1

看起来像你有这个问题，因为波形符号运算符应用按位非操作的图像中的所有像素。看看这三条线的C++代码：

cv::Mat img = imread("smiley.png", IMREAD_GRAYSCALE); 
imshow("Image0", img); 
imshow("Image1", ~img); // tilde 

这些图像你：

快速的解决方案：如果你要正确地应用阈值那么无论

• 向输入数组应用按位求反，或使用'THRESH_BINARY_IN'或'
• ' V'而不是'THRESH_BINARY'