A local-first, privacy-friendly AI video upscaling tool built in Python.
Upscale videos to 1080p and 4K using Real-ESRGAN (AI) with automatic fallback to FSRCNN (CPU).

No cloud. No uploads. Fully offline.

• Real-ESRGAN for high-quality AI enhancement
• NVIDIA CUDA support
• Apple Silicon (MPS) support

• Automatically switches to OpenCV FSRCNN
• Works on CPU-only systems without configuration

• AI upscale to 1080p
• High-quality Lanczos interpolation for 4K delivery

• Automatic 4:3 → 16:9 correction
• Smart padding (no stretching or cropping)

• Extracts original audio
• Lossless remux into upscaled video

• No uploads
• No server-side processing
• No data leaves your machine

• macOS (Intel & Apple Silicon)
• Linux
• Windows

• Python 3.8+
• FFmpeg (must be available in PATH)

Download from: https://ffmpeg.org/download.html
Ensure ffmpeg is added to PATH.

1. Clone the repository

   git clone https://github.com/pratik227/video-enhance.git
   cd video-enhance

2. Install dependencies

   pip install -r requirements.txt

3. Download model weights

   AI Upscaling (Recommended)
   Place one of the following files in the project root:

   • RealESRGAN_x4plus.pth
   • RealESRGAN_x4.pth

   CPU Fallback
   Place this file in the models/ directory:

Rename your input video to match the default name OR update the INPUT_VIDEO variable in the script.

• AI-enhanced 1080p video
• High-quality 4K video
• Original audio preserved

• torch
• opencv-python
• ffmpeg-python
• numpy
• tqdm
• realesrgan
• ai-forever Real-ESRGAN

• GPU acceleration is auto-detected at runtime
• FSRCNN fallback is used automatically if GPU is unavailable
• Optimized for long-form and archival video processing

• Old SD footage
• Personal media restoration
• Content remastering
• Offline processing pipelines

If this project helps you, consider supporting its development.

💝 GitHub Sponsors
https://github.com/sponsors/pratik227

☕ Buy Me a Coffee
https://buymeacoffee.com/pratik227

⭐ Free Support

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Pratik Patel
Independent builder focused on local-first, privacy-respecting tools

GitHub: https://github.com/pratik227

MIT License
See the LICENSE file for details.