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