70 lines
2.3 KiB
Python
70 lines
2.3 KiB
Python
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#!/usr/bin/env python
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'''
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This program demonstrates Laplace point/edge detection using
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OpenCV function Laplacian()
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It captures from the camera of your choice: 0, 1, ... default 0
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Usage:
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python laplace.py <ddepth> <smoothType> <sigma>
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If no arguments given default arguments will be used.
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Keyboard Shortcuts:
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Press space bar to exit the program.
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'''
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# Python 2/3 compatibility
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from __future__ import print_function
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import numpy as np
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import cv2 as cv
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import sys
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def main():
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# Declare the variables we are going to use
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ddepth = cv.CV_16S
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smoothType = "MedianBlur"
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sigma = 3
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if len(sys.argv)==4:
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ddepth = sys.argv[1]
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smoothType = sys.argv[2]
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sigma = sys.argv[3]
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# Taking input from the camera
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cap=cv.VideoCapture(0)
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# Create Window and Trackbar
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cv.namedWindow("Laplace of Image", cv.WINDOW_AUTOSIZE)
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cv.createTrackbar("Kernel Size Bar", "Laplace of Image", sigma, 15, lambda x:x)
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# Printing frame width, height and FPS
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print("=="*40)
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print("Frame Width: ", cap.get(cv.CAP_PROP_FRAME_WIDTH), "Frame Height: ", cap.get(cv.CAP_PROP_FRAME_HEIGHT), "FPS: ", cap.get(cv.CAP_PROP_FPS))
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while True:
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# Reading input from the camera
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ret, frame = cap.read()
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if ret == False:
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print("Can't open camera/video stream")
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break
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# Taking input/position from the trackbar
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sigma = cv.getTrackbarPos("Kernel Size Bar", "Laplace of Image")
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# Setting kernel size
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ksize = (sigma*5)|1
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# Removing noise by blurring with a filter
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if smoothType == "GAUSSIAN":
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smoothed = cv.GaussianBlur(frame, (ksize, ksize), sigma, sigma)
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if smoothType == "BLUR":
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smoothed = cv.blur(frame, (ksize, ksize))
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if smoothType == "MedianBlur":
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smoothed = cv.medianBlur(frame, ksize)
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# Apply Laplace function
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laplace = cv.Laplacian(smoothed, ddepth, 5)
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# Converting back to uint8
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result = cv.convertScaleAbs(laplace, (sigma+1)*0.25)
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# Display Output
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cv.imshow("Laplace of Image", result)
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k = cv.waitKey(30)
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if k == 27:
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return
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if __name__ == "__main__":
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print(__doc__)
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main()
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cv.destroyAllWindows()
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