OpenCV is a huge open-source library for computer vision, machine learning, and image processing. It can process images and videos to identify objects, faces, or even the handwriting of a human. In this article, we will see how to convert a colored video to a gray-scale format.
Approach:
- Import the cv2 module.
- Read the video file to be converted using the cv2.VideoCapture() method.
- Run an infinite loop.
- Inside the loop extract the frames of the video using the read() method.
- Pass the frame to the cv2.cvtColor() method with cv2.COLOR_BGR2GRAY as a parameter to convert it into gray-scale.
- Display the frame using the cv2.imshow() method.
Example: Suppose we have the video file CountdownTimer.mov as the input.
Python3
# importing the moduleimport cv2  # reading the videosource = cv2.VideoCapture('Countdown Timer.mov')  # running the loopwhile True:      # extracting the frames    ret, img = source.read()          # converting to gray-scale    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)      # displaying the video    cv2.imshow("Live", gray)      # exiting the loop    key = cv2.waitKey(1)    if key == ord("q"):        break      # closing the windowcv2.destroyAllWindows()source.release() |
Â
Â
Output:
Â
Â
