如何使用OpenCV ConnectedComponents获取图像

Question

如何使用Python OpenCV ConnectedComponents函数获取图像？

通过搜索过去的问题，我只能找到如何以不同的颜色为连接的对象着色（经过测试并可以工作，但是我不知道标签如何工作）
这些先前回答的问题的参考：Stackoverflow question 48303309和Stackoverflow question 46441893

使用此代码，我可以获得阴影输出

import cv2
import numpy as np

img = cv2.imread('eGaIy.jpg', 0)
img = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)[1]  # ensure binary
ret, labels = cv2.connectedComponents(img)

# Map component labels to hue val
label_hue = np.uint8(179*labels/np.max(labels))
blank_ch = 255*np.ones_like(label_hue)
labeled_img = cv2.merge([label_hue, blank_ch, blank_ch])

# cvt to BGR for display
labeled_img = cv2.cvtColor(labeled_img, cv2.COLOR_HSV2BGR)

# set bg label to black
labeled_img[label_hue==0] = 0

cv2.imshow('labeled.png', labeled_img)
cv2.waitKey()

有什么方法可以从图像中获取连接的对象吗？
因此输出将是原始图像中的多张图像

Answer 1

image = cv2.imread('image.png', cv2.IMREAD_UNCHANGED);
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]

# getting mask with connectComponents
ret, labels = cv2.connectedComponents(binary)
for label in range(1,ret):
    mask = np.array(labels, dtype=np.uint8)
    mask[labels == label] = 255
    cv2.imshow('component',mask)
    cv2.waitKey(0)

# getting ROIs with findContours
contours = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[1]
for cnt in contours:
    (x,y,w,h) = cv2.boundingRect(cnt)
    ROI = image[y:y+h,x:x+w]
    cv2.imshow('ROI', ROI)
    cv2.waitKey(0)

cv2.destroyAllWindows()