如何通过python的opencv找到数字轮廓

如何通过python的opencv找到数字轮廓，想找出图片中的数字区域，然后单独把每一个数字放进一个列表里面

自己写了一个，问题是提取的时候，5和7会粘连，不知道有什么办法可以解决

# -*- coding: utf-8 -*-
import cv2

# 对框进行排序
def sort_contours(cnts, method="left-to-right"):
    reverse = False
    i = 0
    if method == "right-to-left" or method == "bottom-to-top":
        reverse = True
    if method == "top-to-bottom" or method == "bottom-to-top":
        i = 1
    boundingBoxes = [cv2.boundingRect(c) for c in cnts]  # 用一个最小的矩形，把找到的形状包起来x,y,h,w
    (cnts, boundingBoxes) = zip(*sorted(zip(cnts, boundingBoxes),
                                        key=lambda b: b[1][i], reverse=reverse))

    return cnts, boundingBoxes


# 调整图片尺寸大小
def resize(image, width=None, height=None, inter=cv2.INTER_AREA):
    dim = None
    (h, w) = image.shape[:2]
    if width is None and height is None:
        return image
    if width is None:
        r = height / float(h)
        dim = (int(w * r), height)
    else:
        r = width / float(w)
        dim = (width, int(h * r))
    resized = cv2.resize(image, dim, interpolation=inter)
    return resized


# 定义cv2展示函数
def cv_show(name, img):
    cv2.imshow(name, img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


src_img = 'png/test2.png'
img = cv2.imread(src_img)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh1 = cv2.threshold(gray, 0, 255, cv2.THRESH_OTSU | cv2.THRESH_BINARY_INV)

rect_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (15, 3))
dilation = cv2.dilate(thresh1, rect_kernel, iterations=1)
# dilation = cv2.erode(thresh1, rect_kernel, iterations=3)

contours, hierarchy = cv2.findContours(dilation, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
im2 = img.copy()

x, y, w, h = cv2.boundingRect(contours[0])
cv2.rectangle(im2, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv_show('final', im2)

bk = 5
group = gray[y - bk:y + h + bk, x - bk:x + w + bk]
# cv_show("group", group)
group = resize(group, width=300)


blur = cv2.GaussianBlur(group, (1, 1), 0)
ret, th = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)
contours, hierarchy = cv2.findContours(th, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
refCnts = sort_contours(contours, method="left-to-right")[0]

for contour in refCnts:
    [x, y, w, h] = cv2.boundingRect(contour)
    print(x, y, w, h)
    if h > 20:
        cv2.rectangle(group, (x, y), (x + w, y + h), (255, 0, 255), 0)
        roi = th[y:y + h, x:x + w]
        cv_show("dan shu zi", roi)

加小核

方向腐蚀就可以了