Python OpenCV：将图像裁剪为内容，并使背景透明

Question

我有以下图像：

我想将图像裁剪为实际内容，然后使背景（后面的空白）透明。我看到了以下问题：如何根据内容裁剪图像（Python 和 OpenCV）？，在查看答案并尝试之后，我得到了以下代码：

img = cv.imread("tmp/"+img+".png")
mask = np.zeros(img.shape[:2],np.uint8)

bgdModel = np.zeros((1,65),np.float64)
fgdModel = np.zeros((1,65),np.float64)

rect = (55,55,110,110)
cv.grabCut(img,mask,rect,bgdModel,fgdModel,5,cv.GC_INIT_WITH_RECT)

mask2 = np.where((mask==2)|(mask==0),0,1).astype('uint8')
img = img*mask2[:,:,np.newaxis]

plt.imshow(img),plt.colorbar(),plt.show()

但是当我尝试这段代码时，我得到以下结果：

这并不是我正在寻找的结果，而是预期的结果：

Answer 1

这是在 Python/OpenCV 中执行此操作的一种方法。

正如我在评论中提到的，您提供的图像在牛周围有一个白色圆圈，然后是透明背景。我已将背景设置为全白作为我的输入。

输入：

import cv2
import numpy as np

# read image
img = cv2.imread('cow.png')

# convert to grayscale
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

# invert gray image
gray = 255 - gray

# threshold
thresh = cv2.threshold(gray,0,255,cv2.THRESH_BINARY)[1]

# apply close and open morphology to fill tiny black and white holes and save as mask
kernel = np.ones((3,3), np.uint8)
mask = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)

# get contours (presumably just one around the nonzero pixels) 
contours = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contours = contours[0] if len(contours) == 2 else contours[1]
cntr = contours[0]
x,y,w,h = cv2.boundingRect(cntr)

# make background transparent by placing the mask into the alpha channel
new_img = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
new_img[:, :, 3] = mask

# then crop it to bounding rectangle
crop = new_img[y:y+h, x:x+w]

# save cropped image
cv2.imwrite('cow_thresh.png',thresh)
cv2.imwrite('cow_mask.png',mask)
cv2.imwrite('cow_transparent_cropped.png',crop)

# show the images
cv2.imshow("THRESH", thresh)
cv2.imshow("MASK", mask)
cv2.imshow("CROP", crop)
cv2.waitKey(0)
cv2.destroyAllWindows()

阈值图像：

面具：

透明背景的裁剪结果：