Add Video Upscaling Feature Using AI Model

[smart-dev1028]

Description:
We need to implement a video upscaling feature that takes a low-resolution video input and produces a high-resolution output using an AI-based upscaling model (e.g., Real-ESRGAN or Video Super-Resolution). This feature should support common formats (MP4, AVI) and allow optional frame rate adjustments.

Tasks:

• Integrate AI video upscaling model
• Accept video input via file upload or URL
• Process video frame-by-frame
• Save and return the upscaled video
• Add progress updates during processing

Code Snippet (Python example using Real-ESRGAN + OpenCV):

import cv2
from realesrgan import RealESRGAN

# Load video
input_path = 'input_video.mp4'
output_path = 'upscaled_video.mp4'
cap = cv2.VideoCapture(input_path)

# Initialize Real-ESRGAN model
model = RealESRGAN('cuda', scale=4)  # 4x upscaling
model.load_weights('RealESRGAN_x4.pth')

# Get video properties
fps = int(cap.get(cv2.CAP_PROP_FPS))
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))

# Prepare video writer
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
out = cv2.VideoWriter(output_path, fourcc, fps, (width*4, height*4))

# Process frames
while True:
    ret, frame = cap.read()
    if not ret:
        break
    upscaled_frame = model.predict(frame)
    out.write(upscaled_frame)

cap.release()
out.release()
print("Video upscaling complete!")

Notes:

• GPU support is recommended for faster processing.
• Can add optional CLI/GUI interface for end-users.
• Consider batching frames to improve memory efficiency.

Labels: enhancement, AI, video-processing

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