python 利用opencv实现颜色检测
需要实现倒车辅助标记检测的功能,倒车辅助标记颜色已经确定了,所以不需要使用深度学习的方法,那样成本太高了,直接可以使用颜色检测的方法。
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首先需要确定待检测目标的HSV值
1 import cv2 2 3 img = cv2.imread('l3.png') 4 gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 5 hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) 6 7 8 def mouse_click(event, x, y, flags, para): 9 if event == cv2.EVENT_LBUTTONDOWN: # 左边鼠标点击 10 print('PIX:', x, y) 11 print("BGR:", img[y, x]) 12 print("GRAY:", gray[y, x]) 13 print("HSV:", hsv[y, x]) 14 15 16 if __name__ == '__main__': 17 cv2.namedWindow("img") 18 cv2.setMouseCallback("img", mouse_click) 19 while True: 20 cv2.imshow('img', img) 21 if cv2.waitKey() == ord('q'): 22 break 23 cv2.destroyAllWindows()
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然后利用颜色检测,检测出指定目标
1 import numpy as np 2 import cv2 3 4 font = cv2.FONT_HERSHEY_SIMPLEX 5 lower_red = np.array([0, 127, 128]) # 红色阈值下界 6 higher_red = np.array([10, 255, 255]) # 红色阈值上界 7 lower_yellow = np.array([15, 230, 230]) # 黄色阈值下界 8 higher_yellow = np.array([35, 255, 255]) # 黄色阈值上界 9 lower_blue = np.array([85,240,140]) 10 higher_blue = np.array([100,255,165]) 11 frame=cv2.imread("l3.png") 12 img_hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) 13 mask_red = cv2.inRange(img_hsv, lower_red, higher_red) # 可以认为是过滤出红色部分,获得红色的掩膜 14 mask_yellow = cv2.inRange(img_hsv, lower_yellow, higher_yellow) # 获得绿色部分掩膜 15 mask_yellow = cv2.medianBlur(mask_yellow, 7) # 中值滤波 16 mask_red = cv2.medianBlur(mask_red, 7) # 中值滤波 17 mask_blue = cv2.inRange(img_hsv, lower_blue, higher_blue) # 获得绿色部分掩膜 18 mask_blue = cv2.medianBlur(mask_blue, 7) # 中值滤波 19 #mask = cv2.bitwise_or(mask_green, mask_red) # 三部分掩膜进行按位或运算 20 print(mask_red) 21 cnts1, hierarchy1 = cv2.findContours(mask_red, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) # 轮廓检测 #红色 22 cnts2, hierarchy2 = cv2.findContours(mask_blue, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) # 轮廓检测 #红色 23 cnts3, hierarchy3 = cv2.findContours(mask_yellow, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) 24 25 for cnt in cnts1: 26 (x, y, w, h) = cv2.boundingRect(cnt) # 该函数返回矩阵四个点 27 cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2) # 将检测到的颜色框起来 28 cv2.putText(frame, 'red', (x, y - 5), font, 0.7, (0, 0, 255), 2) 29 for cnt in cnts2: 30 (x, y, w, h) = cv2.boundingRect(cnt) # 该函数返回矩阵四个点 31 cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2) # 将检测到的颜色框起来 32 cv2.putText(frame, 'blue', (x, y - 5), font, 0.7, (0, 0, 255), 2) 33 34 for cnt in cnts3: 35 (x, y, w, h) = cv2.boundingRect(cnt) # 该函数返回矩阵四个点 36 cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2) # 将检测到的颜色框起来 37 cv2.putText(frame, 'green', (x, y - 5), font, 0.7, (0, 255, 0), 2) 38 cv2.imshow('frame', frame) 39 40 cv2.waitKey(0) 41 cv2.destroyAllWindows()
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效果