Nightingale Video Enhancement Models
This repository contains the pre-trained AI models used by the Nightingale Video Enhancement Service.
Models Included
Real-ESRGAN (Super Resolution)
- File:
RealESRGAN_x4plus.pth - Purpose: Upscales video resolution (e.g., 480p → 1080p)
- Architecture: Real-ESRGAN x4 plus model
- License: BSD 3-Clause
- Source: Real-ESRGAN Repository
RIFE (Frame Interpolation)
- File:
RIFE_v4.6.pth - Purpose: Interpolates frames to increase frame rate (e.g., 15fps → 30fps)
- Architecture: RIFE v4.6 model
- License: MIT License
- Source: RIFE Repository
Usage
These models are automatically downloaded by the Nightingale Video Enhancement Service. To use them in your own project:
from huggingface_hub import hf_hub_download
# Download Real-ESRGAN model
realesrgan_path = hf_hub_download(
repo_id="mkulyma/nightingale-models",
filename="RealESRGAN_x4plus.pth"
)
# Download RIFE model
rife_path = hf_hub_download(
repo_id="mkulyma/nightingale-models",
filename="RIFE_v4.6.pth"
)
Model Details
- Total Size: ~150MB
- Framework: PyTorch
- Device Support: CUDA GPU (recommended) or CPU
- Input: Video files (MP4, AVI, MOV, etc.)
- Output: Enhanced video with higher resolution and/or frame rate
Nightingale Project
These models are part of the Nightingale Video Enhancement Service, an AI-powered video enhancement platform that provides:
- Web-based interface for video upload and processing
- Docker deployment for easy setup
- GPU acceleration with CPU fallback
- Real-time processing monitoring
- Batch processing capabilities
License
The models retain their original licenses:
- Real-ESRGAN: BSD 3-Clause License
- RIFE: MIT License
This model repository packaging: MIT License