技術標籤：Python OpenCV 影象學習-21年opencvpython

# 凸缺陷和輪廓形狀匹配
import cv2
import numpy as np

img = cv2.imread('image/five.jpg')

img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(img_gray, 140, 255, 0)

im, contours, hierarchy = cv2.findContours(thresh, 2, 1)
print(len(contours))

img = cv2.drawContours(img, contours, 1, (0, 255, 0), 3)

# cv2.imshow('im', img)


cnt = contours[1]  # 注意隨著圖片的改變要檢測的輪廓序號也會發生變化，在本圖輪廓序號和二值化相關（閾值）
hull = cv2.convexHull(cnt, returnPoints=False)  # 注意引數

defects = cv2.convexityDefects(cnt, hull)

print(defects)
for i in range(defects.shape[0]):
    s, e, f, d = defects[i, 0]
    start = tuple(cnt[s][0])
    end = tuple(cnt[e][0])
    far = tuple(cnt[f][0])
    cv2.line(img, start, end, [0, 255, 0], 2)
    cv2.circle(img, far, 5, [0, 0, 255], -1)

# 計算輸出兩個輪廓的相似度-----輪廓形狀匹配
# ret值越小，越匹配
cnt1 = contours[0]
cnt2 = contours[1]
ret = cv2.matchShapes(cnt1, cnt2, 1, 0.0)

print(ret)

cv2.imshow('img', img)
cv2.waitKey(0)
cv2.destroyAllWindows()