77 lines
2.6 KiB
Python
77 lines
2.6 KiB
Python
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from __future__ import division
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import cv2
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import numpy as np
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def nothing(*arg):
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pass
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# Initial HSV GUI slider values to load on program start.
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icol = (36, 202, 59, 71, 255, 255) # Green
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#icol = (18, 0, 196, 36, 255, 255) # Yellow
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#icol = (89, 0, 0, 125, 255, 255) # Blue
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#icol = (0, 100, 80, 10, 255, 255) # Red
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cv2.namedWindow('colorTest')
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# Lower range colour sliders.
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cv2.createTrackbar('lowHue', 'colorTest', icol[0], 255, nothing)
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cv2.createTrackbar('lowSat', 'colorTest', icol[1], 255, nothing)
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cv2.createTrackbar('lowVal', 'colorTest', icol[2], 255, nothing)
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# Higher range colour sliders.
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cv2.createTrackbar('highHue', 'colorTest', icol[3], 255, nothing)
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cv2.createTrackbar('highSat', 'colorTest', icol[4], 255, nothing)
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cv2.createTrackbar('highVal', 'colorTest', icol[5], 255, nothing)
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# Raspberry pi file path example.
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frame = cv2.imread('box.png')
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# Windows file path example.
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#frame = cv2.imread('colour-circles-test.jpg')
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while True:
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# Get HSV values from the GUI sliders.
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lowHue = cv2.getTrackbarPos('lowHue', 'colorTest')
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lowSat = cv2.getTrackbarPos('lowSat', 'colorTest')
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lowVal = cv2.getTrackbarPos('lowVal', 'colorTest')
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highHue = cv2.getTrackbarPos('highHue', 'colorTest')
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highSat = cv2.getTrackbarPos('highSat', 'colorTest')
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highVal = cv2.getTrackbarPos('highVal', 'colorTest')
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# Show the original image.
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cv2.imshow('frame', frame)
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# Blur methods available, comment or uncomment to try different blur methods.
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frameBGR = cv2.GaussianBlur(frame, (7, 7), 0)
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#frameBGR = cv2.medianBlur(frameBGR, 7)
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#frameBGR = cv2.bilateralFilter(frameBGR, 15 ,75, 75)
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"""kernal = np.ones((15, 15), np.float32)/255
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frameBGR = cv2.filter2D(frameBGR, -1, kernal)"""
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# Show blurred image.
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cv2.imshow('blurred', frameBGR)
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# HSV (Hue, Saturation, Value).
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# Convert the frame to HSV colour model.
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hsv = cv2.cvtColor(frameBGR, cv2.COLOR_BGR2HSV)
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# HSV values to define a colour range.
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colorLow = np.array([lowHue,lowSat,lowVal])
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colorHigh = np.array([highHue,highSat,highVal])
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mask = cv2.inRange(hsv, colorLow, colorHigh)
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# Show the first mask
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#cv2.imshow('mask-plain', mask)
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kernal = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (7, 7))
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mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernal)
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mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernal)
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# Show morphological transformation mask
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#cv2.imshow('mask', mask)
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# Put mask over top of the original image.
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#result = cv2.bitwise_and(frame, frame, mask = mask)
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# Show final output image
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cv2.imshow('colorTest', result)
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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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