使用python检测边缘后如何将图像裁剪成碎片 [英] How to crop an image into pieces after detecting the edges using python

问题描述

我正在研究一个残缺的文档重建项目.首先，我尝试检测包含撕裂的文档碎片的图像边缘，然后尝试使用示例代码

I am working on a torn document reconstruction project. First I tried to detect the edges of the image which contain torn document pieces and then I tried to crop the image into the pieces through the detected edges using the sample code,

import cv2
import numpy as np
img = cv2.imread("test.png")
img = cv2.imread("d:/test.jpeg")

cv2.imshow('Original Image',img)

new_img = cv2.Canny(img, 0, 505)
cv2.imshow('new image', new_img)

blurred = cv2.blur(new_img, (3,3))
canny = cv2.Canny(blurred, 50, 200)

## find the non-zero min-max coords of canny
pts = np.argwhere(canny>0)
y1,x1 = pts.min(axis=0)
y2,x2 = pts.max(axis=0)

## crop the region
cropped = new_img[y1:y2, x1:x2]
cv2.imwrite("cropped.png", cropped)

tagged = cv2.rectangle(new_img.copy(), (x1,y1), (x2,y2), (0,255,0), 3, cv2.LINE_AA)
cv2.imshow("tagged", tagged)
cv2.waitKey()

我的输入图像是

运行上面的代码后，我得到类似的输出

after running the above code i gets a output like

有人可以帮我裁剪残缺的文档碎片并将其分配给变量

can someone help me to crop the torn document pieces and assign them into variables

推荐答案

我的工作流程的开始与您的相似.第一步:模糊图像.

The beginning of my workflow is similar to yours. First step: blur the image..

blurred = cv2.GaussianBlur(gray, (5, 5), 0) # Blur

第二步:获取精明的图片...

Second step: get the canny image...

canny = cv2.Canny(blurred, 30, 150) # Canny

第三步:在canny图像上绘制轮廓.这样就关闭了撕碎的碎片.

Third step: draw the contours on the canny image. This closes the torn pieces.

# Find contours
_, contours, _ = cv2.findContours(canny,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
# Draw contours on canny (this connects the contours
cv2.drawContours(canny, contours, -1, 255, 2)
canny = 255 - canny

第四步:洪水填埋(洪水泛滥区为灰色)

Fourth step: floodfill (the floodfilled areas are gray)

# Get mask for floodfill
h, w = thresh.shape[:2]
mask = np.zeros((h+2, w+2), np.uint8)
# Floodfill from point (0, 0)
cv2.floodFill(thresh, mask, (0,0), 123);

第五步:消除非常小的轮廓和非常大的轮廓

Fifth step: get rid of the really small and really large contours

# Create a blank image to draw on
res = np.zeros_like(src_img)
# Create a list for unconnected contours
unconnectedContours = []
for contour in contours:
    area = cv2.contourArea(contour)
    # If the contour is not really small, or really big
    if area > 123 and area < 760000:
        cv2.drawContours(res, [contour], 0, (255,255,255), cv2.FILLED)
        unconnectedContours.append(contour)

最后，将片段分割后，就可以将其嵌套.

Finally, once you have segmented the pieces, they can be nested.

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