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