opencv_tutorials/python/code_052/opencv_052.py at master · HZHCoder1990/opencv_tutorials · GitHub

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import cv2 as cv

import numpy as np

def canny_demo(image):

t = 80

canny_output = cv.Canny(image, t, t * 2)

cv.imshow("canny_output", canny_output)

cv.imwrite("canny_output.png", canny_output)

return canny_output

src = cv.imread("stuff.jpg")

cv.namedWindow("input", cv.WINDOW_AUTOSIZE)

cv.imshow("input", src)

binary = canny_demo(src)

k = np.ones((3, 3), dtype=np.uint8)

binary = cv.morphologyEx(binary, cv.MORPH_DILATE, k)

# 轮廓发现

out, contours, hierarchy = cv.findContours(binary, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)

for c in range(len(contours)):

rect = cv.minAreaRect(contours[c])

cx, cy = rect[0]

ww, hh = rect[1]

ratio = np.minimum(ww, hh) / np.maximum(ww, hh)

print(ratio)

mm = cv.moments(contours[c])

m00 = mm['m00']

m10 = mm['m10']

m01 = mm['m01']

cx = np.int(m10 / m00)

cy = np.int(m01 / m00)

box = cv.boxPoints(rect)

box = np.int0(box)

if ratio > 0.9:

cv.drawContours(src, [box], 0, (0, 0, 255), 2)

cv.circle(src, (np.int32(cx), np.int32(cy)), 2, (255, 0, 0), 2, 8, 0)

if ratio < 0.5:

cv.drawContours(src, [box], 0, (255, 0, 255), 2)

cv.circle(src, (np.int32(cx), np.int32(cy)), 2, (0, 0, 255), 2, 8, 0)

# 显示

cv.imshow("contours_analysis", src)

cv.imwrite("contours_analysis.png", src)

cv.waitKey(0)

cv.destroyAllWindows()

opencv_tutorials/python/code_052/opencv_052.py at master · HZHCoder1990/opencv_tutorials · GitHub

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