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我试图找到在不同帧中检测到的所有对象，我认为这将给出阈值中检测到的每个区域的列表，但是find_objects给出了一堆“无”和整个图像的范围？

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(slice(0, 972, None), slice(0, 1296, None))

相关代码可以从这里测试

import numpy as np
import cv2
from matplotlib import pyplot as plt
import pylab

from scipy import ndimage
import os

for img in os.listdir('.'):
    if img.endswith('.jpg'):
        image = cv2.imread(img)
        gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        gray_image = cv2.resize(gray_image, (int(gray_image.shape[1]/2), int(gray_image.shape[0]/2) ))
        ret, threshimg = cv2.threshold(gray_image,0,255,cv2.THRESH_BINARY)
        cv2.imshow('opening',threshimg)
        objects = ndimage.find_objects(threshimg)
        for ob in objects:
            print(ob)
        cv2.waitKey(0)                 # Waits forever for user to press any key   
        cv2.destroyAllWindows()
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1 回答 1

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您可以使用cv2.connectedComponentsWithStats相同的。

import numpy as np
import cv2
from matplotlib import pyplot as plt
import pylab

from scipy import ndimage
import os
### for visualising connected component image
def imshow_components(labels):
    # 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
    return labeled_img

for img in os.listdir('.'):
    if img.endswith('.jpg'):
        image = cv2.imread(img)
        gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        gray_image = cv2.resize(gray_image, (int(gray_image.shape[1]/2), int(gray_image.shape[0]/2) ))
        ret, threshimg = cv2.threshold(gray_image,0,255,cv2.THRESH_BINARY)
        num_labels, labels, stats, centroids = cv2.connectedComponentsWithStats(thresh)
        out_image=imshow_components(labels)
        #### stats will have x,y,w,h,area of each detected connected component

有关连接组件功能的更多信息，请参阅此答案。

于 2020-07-05T07:27:34.757 回答