如何使用 OpenCV ConnectedComponents 获取图像
How to use OpenCV ConnectedComponents to get the images
如何使用PythonOpenCV ConnectedComponents函数获取图像?
通过搜索过去的一些问题,我只能找到如何用不同颜色遮蔽连接的对象(我测试过并且有效,但我不知道标签是如何工作的)
参考这些先前回答的问题: and
使用这段代码,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取出连接的对象吗?
所以输出将是来自原始图像的多个图像
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()
如何使用PythonOpenCV ConnectedComponents函数获取图像?
通过搜索过去的一些问题,我只能找到如何用不同颜色遮蔽连接的对象(我测试过并且有效,但我不知道标签是如何工作的)
参考这些先前回答的问题:
使用这段代码,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取出连接的对象吗?
所以输出将是来自原始图像的多个图像
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()