基于SimpleBlobDetector识别骰子点数

import cv2
# putText函数使用的字体定义
font = cv2.FONT_HERSHEY_SIMPLEX
 
# 读取图片、灰度转换、自适应阈值
img = cv2.imread("A.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
thresh = cv2.adaptiveThreshold(gray,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
                            cv2.THRESH_BINARY_INV,15,3)
# 查看二值化结果
cv2.imshow("thres", thresh)
# 轮廓查找
contours,hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

# 设置SimpleBlobDetector参数
params = cv2.SimpleBlobDetector_Params()

# 通过圆率来过滤>0.7
params.filterByCircularity = True
params.minCircularity = 0.7

# 应用参数
detector = cv2.SimpleBlobDetector_create(params)

# 变量轮廓通过外界矩形宽截取每个骰子ROI
for cnt in contours:
  (x, y, w, h) = cv2.boundingRect(cnt)
  if w > 100 and h > 100:
    cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
    roi = gray[y:y+h, x:x+w]
    cv2.imshow("roi",roi)
    cv2.waitKey(0)
    # 圆形Blob检测
    keypoints = detector.detect(roi)
    # len(keypoints)就是检测到的圆形Blob数量
    print(len(keypoints))
    cv2.putText(img, str(len(keypoints)), (x+15, y+25), font, 1.0, (0, 0, 255), 2)

# 显示结果
cv2.imshow("result", img)
cv2.waitKey(0)
cv2.destroyAllWindows()