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Converting Color video to grayscale using OpenCV in Python
  • Last Updated : 05 Sep, 2020

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:

  1. Import the cv2 module.
  2. Read the video file to be converted using the cv2.VideoCapture() method.
  3. Run an infinite loop.
  4. Inside the loop extract the frames of the video using the read() method.
  5. Pass the frame to the cv2.cvtColor() method with cv2.COLOR_BGR2GRAY as a parameter to convert it into gray-scale.
  6. Display the frame using the cv2.imshow() method.

Example: Suppose we have the video file CountdownTimer.mov as the input.

Python3




# importing the module
import cv2
  
# reading the vedio
source = cv2.VideoCapture('Countdown Timer.mov')
  
# running the loop
while 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 window
cv2.destroyAllWindows()
source.release()

Output:

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