Question

我正在使用从此答案中获取的代码：Detect text region in image using Opencv

我正在使用的代码是：

import cv2
def captch_ex(file_name ):
    img  = cv2.imread(file_name)

    img_final = cv2.imread(file_name)
    img2gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    ret, mask = cv2.threshold(img2gray, 180, 255, cv2.THRESH_BINARY)
    image_final = cv2.bitwise_and(img2gray , img2gray , mask =  mask)
    ret, new_img = cv2.threshold(image_final, 180 , 255, cv2.THRESH_BINARY)  # for black text , cv.THRESH_BINARY_INV
    '''
            line  8 to 12  : Remove noisy portion
    '''
    kernel = cv2.getStructuringElement(cv2.MORPH_CROSS,(3 , 3)) # to manipulate the orientation of dilution , large x means horizonatally dilating  more, large y means vertically dilating more
    dilated = cv2.dilate(new_img,kernel,iterations = 9) # dilate , more the iteration more the dilation

    contours = cv2.findContours(dilated,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)[0] # get contours
    index = 0
    for contour in contours:
        # get rectangle bounding contour
        [x,y,w,h] = cv2.boundingRect(contour)

        #Don't plot small false positives that aren't text
        if w < 35 and h<35:
            continue

        # draw rectangle around contour on original image
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,255),2)

        #you can crop image and send to OCR  , false detected will return no text :)
        cropped = img_final[y :y +  h , x : x + w]

        s = file_name + 'crop_' + str(index) + '.png'
        cv2.imwrite(s , cropped)
        index = index + 1
    # write original image with added contours to disk

file_name ='rec_5.png'
captch_ex(file_name)

最重要的区别是： contours = cv2.findContours(dilated,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)[0] 添加了[0]，因为我一直收到此错误

Traceback (most recent call last):
  File "test2.py", line 38, in <module>
    captch_ex(file_name)
  File "test2.py", line 20, in captch_ex
    [x,y,w,h] = cv2.boundingRect(contour)
TypeError: points is not a numpy array, neither a scalar

不幸的是，我找不到源代码，但我在某处读到版本3的此方法发生了变化，现在这是必需的。

我的问题是，当我向这个函数提供一个图像时，我会收到数百张1 px.宽度的裁剪图像，这些图像无法完成该函数在参考答案中明显解决的问题。

截至目前，我猜测上面提到的额外[0]可能是导致错误的原因，但如果没有它，我可以让脚本完成。

Answer 1

问题在于cv2.findContours()方法，实际上它有不同的Opencv 2和Opencv 3的返回参数，你必须检查你正在使用的Opencv版本的文档，一般来说：

Opencv 2：

contours, hierarchy = cv2.findContours(dilated,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)

Opencv 3：

image, contours, hierarchy = cv2.findContours(dilated,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)

现在您不需要[0]黑客访问轮廓，您可以继续：

for contour in contours:
    # get rectangle bounding contour
    [x,y,w,h] = cv2.boundingRect(contour)

使用OpenCV和Python从图像中识别和裁剪文本的问题

1 个答案: