68 lines
2.2 KiB
Python
68 lines
2.2 KiB
Python
import cv2
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import numpy as np
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def test():
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raw = cv2.imread("./data/003.png")
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# 设定颜色HSV范围，假定为红色
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redLower = np.array([30, 0, 0])
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redUpper = np.array([255, 193, 255])
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img = raw
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# 将图像转化为HSV格式
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hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
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# 去除颜色范围外的其余颜色
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mask = cv2.inRange(hsv, redLower, redUpper)
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cv2.imshow("mask", mask)
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# 二值化操作
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ret, binary = cv2.threshold(mask, 0, 255, cv2.THRESH_BINARY)
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# 膨胀操作，因为是对线条进行提取定位，所以腐蚀可能会造成更大间隔的断点，将线条切断，因此仅做膨胀操作
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kernel = np.ones((5, 5), np.uint8)
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dilation = cv2.dilate(binary, kernel, iterations=1)
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#
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# img2 = cv2.bitwise_and(img, img, mask=mask)
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# cv2.imshow('image', mask)
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# cv2.waitKey(0)
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# cv2.destroyAllWindows()
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# 获取图像轮廓坐标，其中contours为坐标值，此处只检测外形轮廓
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contours, hierarchy = cv2.findContours(dilation, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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aim_box = (0, 0, 0, 0)
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if len(contours) > 0:
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print('Run!')
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# cv2.boundingRect()返回轮廓矩阵的坐标值，四个值为x, y, w, h， 其中x, y为左上角坐标，w,h为矩阵的宽和高
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boxes = [cv2.boundingRect(c) for c in contours]
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for box in boxes:
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x, y, w, h = box
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if box[2] * box[3] > aim_box[2] * aim_box[3]:
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aim_box = box
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# print(box)
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else:
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pass
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# x, y, w, h = aim_box
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# gray = cv2.GaussianBlur(raw, (5, 5), 0)
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# canny = cv2.Canny(gray, 70, 210)
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# contours, hierarchy = cv2.findContours(canny.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
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# contours = sorted(contours, key=cv2.contourArea, reverse=True)[:3]
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#
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# drawed = cv2.drawContours(raw, contours, -1, (0, 0, 255), 2)
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# print(f"轮廓数量：{len(contours)}")
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# cv2.imshow("raw", cv2.imread("./data/003.png"))
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# cv2.imshow("test1", drawed)
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# cv2.imshow("test", canny)
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cv2.waitKey(0)
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# Press the green button in the gutter to run the script.
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if __name__ == '__main__':
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test()
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# See PyCharm help at https://www.jetbrains.com/help/pycharm/
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