44 lines
1.1 KiB
Python
44 lines
1.1 KiB
Python
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# -*- coding:utf-8 -*-
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# @Author len
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# @Create 2023/10/27 15:24
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import cv2
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import numpy as np
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# 读取图像
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image = cv2.imread('trafficLight_red.png')
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# 将图像转换为HSV色彩空间
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hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
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# 定义红色在HSV中的范围
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lower_red_1 = np.array([0,50,50])
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upper_red_1 = np.array([10,255,255])
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lower_red_2 = np.array([160,50,50])
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upper_red_2 = np.array([180,255,255])
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# 创建掩码
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mask1 = cv2.inRange(hsv, lower_red_1, upper_red_1)
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mask2 = cv2.inRange(hsv, lower_red_2, upper_red_2)
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mask = mask1 + mask2
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# 对掩码进行腐蚀和膨胀操作，以消除噪声
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mask = cv2.erode(mask, None, iterations=2)
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mask = cv2.dilate(mask, None, iterations=2)
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# 找到掩码中的轮廓
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contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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# 遍历轮廓并在原始图像上绘制
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for contour in contours:
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if cv2.contourArea(contour) > 100: # 你可以根据需要调整这个值
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x, y, w, h = cv2.boundingRect(contour)
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cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
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# 显示结果
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cv2.imshow('Detected Red Light', image)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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