This repository provides three high-performance engines for increasing video frame rates (FPS) and achieving "butter-smooth" playback.
- Best Engine (Python): Our premium engine featuring TTA and CRF 0 for mathematically lossless results.
- Standard Engine (Python): Uses Deep Learning (RIFE/IFNet) for high visual quality.
- C++ Engine: Uses Multi-Scale Pyramid Motion Estimation for high-speed processing without requiring a GPU.
| Feature | Best Engine | Standard Engine | C++ Engine |
|---|---|---|---|
| Technology | DL + TTA + Lossless | DL (RIFE) | Pyramid Flow |
| Quality | ⭐⭐⭐⭐⭐+ (Absolute Best) | ⭐⭐⭐⭐⭐ (Excellent) | ⭐⭐⭐ (Good / Fast) |
| Speed | Slowest | Faster | Fastest |
| Specialty | 0 Quality Loss | High Fidelity | Real-time / Low-power |
This is the ultimate engine for users who prioritize quality above all else.
- Test Time Augmentation (TTA): Runs multiple passes per frame to eliminate artifacts.
- Mathematically Lossless: Supports
--lossless(CRF 0) encoding. - Scene Detection: Automatically prevents warping at camera cuts.
- Async I/O: Multi-threaded video reading and writing.
# Maximum Quality Mode
python py/best_engine.py --video in.mp4 --output out.mp4 --fps 60 --tta --lossless
# Balanced Mode
python py/best_engine.py --video in.mp4 --output out.mp4 --fps 60 --batch_size 4Uses the RIFE (Real-Time Intermediate Flow Estimation) architecture.
python py/main.py --video input.mp4 --output output.mp4 --fps 60A custom implementation of a Multi-Scale Pyramid Motion Estimator.
cd cpp && mkdir -p build && cd build
cmake .. && make -j$(nproc)./vfi <input_video> <output_video> <target_fps>- FFmpeg: Required for video encoding/decoding.
- Python 3.8+
- CUDA: Recommended for Python engines.
- CMake & G++: For building the C++ engine.
py/best_engine.py: Advanced premium engine.py/main.py: Standard RIFE implementation.cpp/src/: High-performance motion estimation core (C++).