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58 lines
1.7 KiB
58 lines
1.7 KiB
# Python code to find the co-ordinates of
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# the contours detected in an image.
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import numpy as np
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import cv2
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# Reading image
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font = cv2.FONT_HERSHEY_COMPLEX
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img2 = cv2.imread('card.jpg', cv2.IMREAD_COLOR)
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# Reading same image in another
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# variable and converting to gray scale.
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img = cv2.imread('card.jpg', cv2.IMREAD_GRAYSCALE)
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# Converting image to a binary image
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# ( black and white only image).
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_, threshold = cv2.threshold(img, 110, 255, cv2.THRESH_BINARY)
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# Detecting contours in image.
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contours, _= cv2.findContours(threshold, cv2.RETR_TREE,
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cv2.CHAIN_APPROX_SIMPLE)
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# Going through every contours found in the image.
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for cnt in contours :
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approx = cv2.approxPolyDP(cnt, 0.009 * cv2.arcLength(cnt, True), True)
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# draws boundary of contours.
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cv2.drawContours(img2, [approx], 0, (0, 0, 255), 5)
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# Used to flatted the array containing
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# the co-ordinates of the vertices.
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n = approx.ravel()
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i = 0
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for j in n :
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if(i % 2 == 0):
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x = n[i]
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y = n[i + 1]
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# String containing the co-ordinates.
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string = str(x) + " " + str(y)
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if(i == 0):
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# text on topmost co-ordinate.
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cv2.putText(img2, "Arrow tip", (x, y),
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font, 0.5, (255, 0, 0))
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else:
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# text on remaining co-ordinates.
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cv2.putText(img2, string, (x, y),
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font, 0.5, (0, 255, 0))
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i = i + 1
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# Showing the final image.
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cv2.imshow('image2', img2)
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# Exiting the window if 'q' is pressed on the keyboard.
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if cv2.waitKey(0) & 0xFF == ord('q'):
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cv2.destroyAllWindows()
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