import cv2
import numpy as np
# 读取图片
img = cv2.imread('imgc.png')
# 将图片转换为HSV格式
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
# 红色的HSV范围
lower_red1 = np.array([0, 50, 50])
upper_red1 = np.array([10, 255, 255])
lower_red2 = np.array([170, 50, 50])
upper_red2 = np.array([180, 255, 255])
# 黄色的HSV范围
lower_yellow = np.array([25, 50, 50])
upper_yellow = np.array([35, 255, 255])
# 创建掩膜,将指定颜色范围内的像素置为255
mask_red1 = cv2.inRange(hsv, lower_red1, upper_red1)
mask_red2 = cv2.inRange(hsv, lower_red2, upper_red2)
mask_red = cv2.bitwise_or(mask_red1, mask_red2)
mask_yellow = cv2.inRange(hsv, lower_yellow, upper_yellow)
# 对掩膜进行形态学操作,去除噪音
kernel = np.ones((5, 5), np.uint8)
mask_red = cv2.morphologyEx(mask_red, cv2.MORPH_OPEN, kernel)
mask_red = cv2.morphologyEx(mask_red, cv2.MORPH_CLOSE, kernel)
mask_yellow = cv2.morphologyEx(mask_yellow, cv2.MORPH_OPEN, kernel)
mask_yellow = cv2.morphologyEx(mask_yellow, cv2.MORPH_CLOSE, kernel)
# 检测轮廓
contours_red, hierarchy_red = cv2.findContours(mask_red, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contours_yellow, hierarchy_yellow = cv2.findContours(mask_yellow, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# 根据轮廓数量判断上下半圆是否为红黄
if len(contours_red) > 0 and len(contours_yellow) > 0:
print("上下半圆为红黄")
else:
print("上下半圆不是红黄")
# 显示结果
cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()