import cv2
import numpy as np
# load image as grayscale
img = cv2.imread('xray_chest.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# threshold
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)[1]
hh, ww = thresh.shape
# make bottom 2 rows black where they are white the full width of the image
thresh[hh-3:hh, 0:ww] = 0
# get bounds of white pixels
white = np.where(thresh==255)
xmin, ymin, xmax, ymax = np.min(white[1]), np.min(white[0]), np.max(white[1]), np.max(white[0])
print(xmin,xmax,ymin,ymax)
# crop the image at the bounds adding back the two blackened rows at the bottom
crop = img[ymin:ymax+3, xmin:xmax]
# save resulting masked image
cv2.imwrite('xray_chest_thresh.jpg', thresh)
cv2.imwrite('xray_chest_crop.jpg', crop)
# display result
cv2.imshow("thresh", thresh)
cv2.imshow("crop", crop)
cv2.waitKey(0)
cv2.destroyAllWindows()
在Python/OpenCV中有一种方法可以做到这一点
输入:
底部两行变黑的阈值图像:
裁剪输入:
另一种方法是从阈值图像中获得白色区域的外部轮廓。获取轮廓的边界。然后切到那些边界
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