Open Source Computer Vision Library https://opencv.org/
 
 
 
 
 
 

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#!/usr/bin/env python
'''
VideoCapture sample showcasing some features of the Video4Linux2 backend
Sample shows how VideoCapture class can be used to control parameters
of a webcam such as focus or framerate.
Also the sample provides an example how to access raw images delivered
by the hardware to get a grayscale image in a very efficient fashion.
Keys:
ESC - exit
g - toggle optimized grayscale conversion
'''
# Python 2/3 compatibility
from __future__ import print_function
import numpy as np
import cv2 as cv
def main():
def decode_fourcc(v):
v = int(v)
return "".join([chr((v >> 8 * i) & 0xFF) for i in range(4)])
font = cv.FONT_HERSHEY_SIMPLEX
color = (0, 255, 0)
cap = cv.VideoCapture(0)
cap.set(cv.CAP_PROP_AUTOFOCUS, False) # Known bug: https://github.com/opencv/opencv/pull/5474
cv.namedWindow("Video")
convert_rgb = True
fps = int(cap.get(cv.CAP_PROP_FPS))
focus = int(min(cap.get(cv.CAP_PROP_FOCUS) * 100, 2**31-1)) # ceil focus to C_LONG as Python3 int can go to +inf
cv.createTrackbar("FPS", "Video", fps, 30, lambda v: cap.set(cv.CAP_PROP_FPS, v))
cv.createTrackbar("Focus", "Video", focus, 100, lambda v: cap.set(cv.CAP_PROP_FOCUS, v / 100))
while True:
_status, img = cap.read()
fourcc = decode_fourcc(cap.get(cv.CAP_PROP_FOURCC))
fps = cap.get(cv.CAP_PROP_FPS)
if not bool(cap.get(cv.CAP_PROP_CONVERT_RGB)):
if fourcc == "MJPG":
img = cv.imdecode(img, cv.IMREAD_GRAYSCALE)
elif fourcc == "YUYV":
img = cv.cvtColor(img, cv.COLOR_YUV2GRAY_YUYV)
else:
print("unsupported format")
break
cv.putText(img, "Mode: {}".format(fourcc), (15, 40), font, 1.0, color)
cv.putText(img, "FPS: {}".format(fps), (15, 80), font, 1.0, color)
cv.imshow("Video", img)
k = cv.waitKey(1)
if k == 27:
break
elif k == ord('g'):
convert_rgb = not convert_rgb
cap.set(cv.CAP_PROP_CONVERT_RGB, convert_rgb)
print('Done')
if __name__ == '__main__':
print(__doc__)
main()
cv.destroyAllWindows()