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() |
Output:
