使用此代碼，您可以獲得驗證碼中的每個字母。

def inverte(imagem, name):
    imagem = (255 - imagem)
    cv2.imwrite(name, imagem)
imagem = cv2.imread(image_file)
inverte(imagem, '2.png')
image_file = '2.png'image = cv2.imread(image_file)
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
image = cv2.copyMakeBorder(image, 20, 20, 20, 20, cv2.BORDER_REPLICATE)
thresh = cv2.threshold(image, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
letter_image_regions = []for contour in contours:
    (x, y, w, h) = cv2.boundingRect(contour)    if w / h > 1.25:
        half_width = int(w / 2)
        letter_image_regions.append((x, y, half_width, h))
        letter_image_regions.append((x + half_width, y, half_width, h))    else:
        letter_image_regions.append((x, y, w, h))

letter_image_regions = sorted(letter_image_regions, key=lambda x: x[0])for letter_bounding_box in letter_image_regions:
    x, y, w, h = letter_bounding_box
    letter_image = image[y - 2:y + h + 2, x - 2:x + w + 2]
    letter_image = resize_to_fit(letter_image, 20, 20)
    letter_image = np.expand_dims(letter_image, axis=2)
    letter_image = np.expand_dims(letter_image, axis=0)

這是調整大小以適應功能

import cv2

import imutils

def resize_to_fit(image, width, height):

    # grab the dimensions of the image, then initialize

    # the padding values

    (h, w) = image.shape[:2]

    # if the width is greater than the height then resize along

    # the width

    if w > h:

        image = imutils.resize(image, width=width)

    # otherwise, the height is greater than the width so resize

    # along the height

    else:

        image = imutils.resize(image, height=height)

    # determine the padding values for the width and height to

    # obtain the target dimensions

    padW = int((width - image.shape[1]) / 2.0)

    padH = int((height - image.shape[0]) / 2.0)

    # pad the image then apply one more resizing to handle any

    # rounding issues

    image = cv2.copyMakeBorder(image, padH, padH, padW, padW,

                               cv2.BORDER_REPLICATE)

    image = cv2.resize(image, (width, height))

    # return the pre-processed image

    return image