opencv with cuda GaussianBlur on a video in python

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

import cv2

# Open the video file
cap = cv2.VideoCapture('video.mp4')

# Create a CUDA enabled Gaussian Blur filter
blur = cv2.cuda.createGaussianFilter(cv2.CV_8UC3, (15, 15), 0, 0, cv2.BORDER_DEFAULT)

while True:
    # Read a frame from the video
    ret, frame = cap.read()
    
    if not ret:
        break
    
    # Convert the frame to CUDA format
    frame_cuda = cv2.cuda_GpuMat()
    frame_cuda.upload(frame)
    
    # Apply Gaussian Blur
    blurred_cuda = blur.apply(frame_cuda)
    
    # Download the result back to CPU memory
    blurred = blurred_cuda.download()
    
    # Display the result
    cv2.imshow('Gaussian Blur', blurred)
    
    # Wait for the user to press 'q' to quit
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release the video file and close the window
cap.release()
cv2.destroyAllWindows()

In this code, we first open the video file using `cv2.VideoCapture()`. We then create a CUDA enabled Gaussian Blur filter using `cv2.cuda.createGaussianFilter()`. Inside the loop, we read a frame from the video and convert it to CUDA format using `cv2.cuda_GpuMat()`. We apply Gaussian blur using the filter we created earlier and download the result back to CPU memory using `download()`. Finally, we display the result using `cv2.imshow()` and wait for the user to press 'q' to quit.

Note that you need to have OpenCV with CUDA support installed for this code to work. Also, you may need to adjust the kernel size and other parameters of the Gaussian Blur filter to get the desired effect.