opencv with cuda GaussianBlur on a video in python

To apply GaussianBlur on a video using OpenCV with CUDA in Python, you can use the following code:

import cv2

# Load the video
cap = cv2.VideoCapture('input_video.mp4')

# Create a CUDA enabled GaussianBlur object
blur = cv2.cuda.createGaussianFilter(cap.get(cv2.CAP_PROP_FRAME_HEIGHT), cap.get(cv2.CAP_PROP_FRAME_WIDTH), (3, 3), 0, cv2.CV_32F)

# Process each frame of the video
while True:
    # Capture a frame
    ret, frame = cap.read()
    if not ret:
        break
    
    # Convert the frame to a CUDA enabled matrix
    src = cv2.cuda_GpuMat(frame)
    
    # Apply GaussianBlur on the frame
    dst = blur.apply(src)
    
    # Convert the CUDA enabled matrix to a numpy array
    result = dst.download()
    
    # Display the resulting frame
    cv2.imshow('frame', result)
    
    # Wait for key press
    if cv2.waitKey(1) == ord('q'):
        break

# Release the video and cleanup
cap.release()
cv2.destroyAllWindows()

In this code, we first load the video using `cv2.VideoCapture()`. We then create a CUDA enabled GaussianBlur object using `cv2.cuda.createGaussianFilter()`. We then process each frame of the video in a loop, where we first convert the frame to a CUDA enabled matrix using `cv2.cuda_GpuMat()`. We then apply GaussianBlur on the CUDA enabled matrix using `blur.apply()`. We then convert the CUDA enabled matrix to a numpy array using `dst.download()`. Finally, we display the resulting frame using `cv2.imshow()` and wait for a key press using `cv2.waitKey()`.