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我正在使用 houghLine 方法进行线检测。但它只给出 1 行作为输出，我认为这是获得最多票数的行。我尝试了In opencv using houghlines 的解决方案，只打印一行，但这需要很多时间并且无法正常工作。

我的代码是：

folderInPath = "DevanagariHandwrittenCharacterDataset/Test"
folderOutPath = "DevanagariHandwrittenCharacterDataset/Test_Lines"


for folderPath in os.listdir(folderInPath):
    inPath = "DevanagariHandwrittenCharacterDataset/Test/" + folderPath
    #os.mkdir(os.path.join(folderOutPath, folderPath+'_lines'))
    outPath = os.path.join(folderOutPath, folderPath+'_lines')
    dirs = "DevanagariHandwrittenCharacterDataset/Test/" + folderPath
    for imagePath in os.listdir(dirs):
        # imagePath contains name of the image for eg. 46214.png 
        inputPath = os.path.join(inPath, imagePath)
        # inputPath contains the full directory name for eg. character_1_ka/46214.png|

        # Reading the required image in which operations are to be done.  
        # Make sure that the image is in the same directory in which this python program is 
        img = cv2.imread(inputPath)
    
        # Convert the img to grayscale 
        gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
        
        # Apply edge detection method on the image 
        edges = cv2.Canny(gray,50,150,apertureSize = 3)
    
        # This returns an array of r and theta values 
        lines = cv2.HoughLines(edges,1,np.pi/180, 5) 
        
        for line in lines:
            # The below for loop runs till r and theta values are in the range of the 2d array 
            for r,theta in line:
                # Stores the value of cos(theta) in a 
                a = np.cos(theta) 

                # Stores the value of sin(theta) in b 
                b = np.sin(theta)

                # x0 stores the value rcos(theta) 
                x0 = a*r 

                # y0 stores the value rsin(theta) 
                y0 = b*r 

                # x1 stores the rounded off value of (rcos(theta)-1000sin(theta))
                x1 = int(x0 + 1000*(-b))

                # y1 stores the rounded off value of (rsin(theta)+1000cos(theta))
                y1 = int(y0 + 1000*(a))

                # x2 stores the rounded off value of (rcos(theta)+1000sin(theta)) 
                x2 = int(x0 - 1000*(-b))

                # y2 stores the rounded off value of (rsin(theta)-1000cos(theta)) 
                y2 = int(y0 - 1000*(a)) 

                # cv2.line draws a line in img from the point(x1,y1) to (x2,y2). (0,0,255) denotes the colour of the line to be  
                #drawn. In this case, it is red. 
                cv2.line(img,(x1,y1), (x2,y2), (0,0,255),2) 

                # fullOutPath contains the path of the output 
                fullOutPath = os.path.join(outPath, 'lines_'+imagePath)

                # All the changes made in the input image are finally written on a new image houghlines.jpg 
                cv2.imwrite(fullOutPath, img) 
    print("Done " + folderPath)

有关信息，我的图像输入是 32 x 32 像素的印地语字符。对此有任何建议或解决方案的人。

我在我的数据集中附加了一张图像。有几个这样的图像。图片

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1 回答 1

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您的代码通常是正确的，只是您没有为 Line detection 选择正确的参数lines = cv2.HoughLines(edges,1,np.pi/180, 5)。

将此指令替换为：lines = cv2.HoughLines(edges,1,np.pi/90, 18)

会给你这个结果：

结果

注意：如果要检测更多或更少的线，则必须相应地更改参数。

于 2021-01-23T11:01:01.150 回答