使用 Opencv python 从图像中裁剪凹多边形

Question

如何从图像中裁剪凹多边形。我的输入图像看起来像 .

闭合多边形的坐标为 [10,150],[150,100],[300,150],[350,100],[310,20],[35,10]。我希望使用 opencv 裁剪以凹多边形为界的区域。我搜索了其他类似的问题，但我找不到正确的答案。这就是我问它的原因？你能帮帮我吗？

任何帮助将不胜感激。！！！

Answer 1

您可以分 3 步完成：

1. 从图像中创建一个蒙版

   掩码 = np.zeros((高度, 宽度)) 点 = np.array([[[10,150],[150,100],[300,150],[350,100],[310,20],[35,10]]]) cv2.fillPoly(mask, points, (255))

2. 对原始图像应用蒙版

   res = cv2.bitwise_and(img,img,mask = mask)

3. 您可以选择删除图像以得到更小的图像

   rect = cv2.boundingRect(points) # 返回矩形的 (x,y,w,h) 裁剪 = res[rect[1]: rect[1] + rect[3], rect[0]: rect[0] + rect[2]]

有了这个，你应该在最后裁剪图像

更新

为了完整起见，这里是完整的代码：

import numpy as np
import cv2

img = cv2.imread("test.png")
height = img.shape[0]
width = img.shape[1]

mask = np.zeros((height, width), dtype=np.uint8)
points = np.array([[[10,150],[150,100],[300,150],[350,100],[310,20],[35,10]]])
cv2.fillPoly(mask, points, (255))

res = cv2.bitwise_and(img,img,mask = mask)

rect = cv2.boundingRect(points) # returns (x,y,w,h) of the rect
cropped = res[rect[1]: rect[1] + rect[3], rect[0]: rect[0] + rect[2]]

cv2.imshow("cropped" , cropped )
cv2.imshow("same size" , res)
cv2.waitKey(0)

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对于彩色背景版本，使用如下代码：

import numpy as np
import cv2

img = cv2.imread("test.png")
height = img.shape[0]
width = img.shape[1]

mask = np.zeros((height, width), dtype=np.uint8)
points = np.array([[[10,150],[150,100],[300,150],[350,100],[310,20],[35,10]]])
cv2.fillPoly(mask, points, (255))

res = cv2.bitwise_and(img,img,mask = mask)

rect = cv2.boundingRect(points) # returns (x,y,w,h) of the rect
im2 = np.full((res.shape[0], res.shape[1], 3), (0, 255, 0), dtype=np.uint8 ) # you can also use other colors or simply load another image of the same size
maskInv = cv2.bitwise_not(mask)
colorCrop = cv2.bitwise_or(im2,im2,mask = maskInv)
finalIm = res + colorCrop
cropped = finalIm[rect[1]: rect[1] + rect[3], rect[0]: rect[0] + rect[2]]

cv2.imshow("cropped" , cropped )
cv2.imshow("same size" , res)
cv2.waitKey(0)

Answer 2

步骤

1. 使用多边形点查找区域
2. 使用多边形创建蒙版
3. 对裁剪进行蒙版操作
4. 如果需要，添加白色背景

代码：

# 2018.01.17 20:39:17 CST
# 2018.01.17 20:50:35 CST
import numpy as np
import cv2

img = cv2.imread("test.png")
pts = np.array([[10,150],[150,100],[300,150],[350,100],[310,20],[35,10]])

## (1) Crop the bounding rect
rect = cv2.boundingRect(pts)
x,y,w,h = rect
croped = img[y:y+h, x:x+w].copy()

## (2) make mask
pts = pts - pts.min(axis=0)

mask = np.zeros(croped.shape[:2], np.uint8)
cv2.drawContours(mask, [pts], -1, (255, 255, 255), -1, cv2.LINE_AA)

## (3) do bit-op
dst = cv2.bitwise_and(croped, croped, mask=mask)

## (4) add the white background
bg = np.ones_like(croped, np.uint8)*255
cv2.bitwise_not(bg,bg, mask=mask)
dst2 = bg+ dst


cv2.imwrite("croped.png", croped)
cv2.imwrite("mask.png", mask)
cv2.imwrite("dst.png", dst)
cv2.imwrite("dst2.png", dst2)

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源图片：

结果：