opencv pipeline to get coordinates in images of graphs added
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# 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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img = cv2.imread('card.jpg', cv2.IMREAD_COLOR)
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# Converts images from BGR to HSV
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hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
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lower_blue = np.array([110,50,50])
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upper_blue = np.array([130,255,255])
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# Here we are defining range of bluecolor in HSV
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# This creates a mask of blue coloured
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# objects found in the frame.
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mask = cv2.inRange(hsv, lower_blue, upper_blue)
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res = cv2.bitwise_and(img,img, mask= mask)
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cv2.imshow('img', img)
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cv2.imshow('mask', mask)
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cv2.imshow('res', res)
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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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# Python program for Detection of a
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# specific color(blue here) using OpenCV with Python
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import cv2
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import numpy as np
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# Webcamera no 0 is used to capture the frames
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cap = cv2.VideoCapture(0)
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# This drives the program into an infinite loop.
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while(1):
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# Captures the live stream frame-by-frame
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_, frame = cap.read()
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# Converts images from BGR to HSV
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hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
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lower_blue = np.array([110,50,50])
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upper_blue = np.array([130,255,255])
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# Here we are defining range of bluecolor in HSV
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# This creates a mask of blue coloured
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# objects found in the frame.
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mask = cv2.inRange(hsv, lower_blue, upper_blue)
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# The bitwise and of the frame and mask is done so
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# that only the blue coloured objects are highlighted
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# and stored in res
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res = cv2.bitwise_and(frame,frame, mask= mask)
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cv2.imshow('frame',frame)
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cv2.imshow('mask',mask)
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cv2.imshow('res',res)
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# This displays the frame, mask
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# and res which we created in 3 separate windows.
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k = cv2.waitKey(5) & 0xFF
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if k == 27:
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break
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# Destroys all of the HighGUI windows.
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cv2.destroyAllWindows()
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# release the captured frame
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cap.release()
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