Ethanfel/video-montage-linker
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Ethanfel
2026-02-03 23:31:41 +01:00
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@@ -13,18 +13,20 @@ A PyQt6 application for creating sequenced symlinks from image folders with adva
- Per-folder trim settings (exclude frames from start/end)
### Cross-Dissolve Transitions
Smooth blending between folder boundaries with three blend methods:
Smooth blending between folder boundaries with four blend methods:
| Method | Description | Quality | Speed |
|--------|-------------|---------|-------|
| **Cross-Dissolve** | Simple alpha blend | Good | Fastest |
| **Optical Flow** | Motion-compensated blend using OpenCV Farneback | Better | Medium |
| **RIFE (AI)** | Neural network frame interpolation | Best | Fast (GPU) |
| **RIFE (ncnn)** | Neural network interpolation via rife-ncnn-vulkan | Best | Fast (GPU) |
| **RIFE (Practical)** | PyTorch-based Practical-RIFE (v4.25/v4.26) | Best | Medium (GPU) |
- **Asymmetric overlap**: Set different frame counts for each side of a transition
- **Blend curves**: Linear, Ease In, Ease Out, Ease In/Out
- **Output formats**: PNG, JPEG (with quality), WebP (lossless with method setting)
- **RIFE auto-download**: Automatically downloads rife-ncnn-vulkan binary
- **Practical-RIFE models**: Auto-downloads from Google Drive on first use
### Preview
- **Video Preview**: Play video files from source folders
@@ -54,11 +56,24 @@ Smooth blending between folder boundaries with three blend methods:
pip install PyQt6 Pillow numpy opencv-python
```
### RIFE (Optional)
For AI-powered frame interpolation, the app can auto-download [rife-ncnn-vulkan](https://github.com/nihui/rife-ncnn-vulkan) or you can install it manually:
- Select **RIFE (AI)** as the blend method
- Click **Download** to fetch the latest release
**Note:** Practical-RIFE creates its own isolated venv with PyTorch. The `gdown` package is installed automatically for downloading models from Google Drive.
### RIFE ncnn (Optional)
For AI-powered frame interpolation using Vulkan GPU acceleration:
- Select **RIFE (ncnn)** as the blend method
- Click **Download** to auto-fetch [rife-ncnn-vulkan](https://github.com/nihui/rife-ncnn-vulkan)
- Or specify a custom binary path
- Models: rife-v4.6, rife-v4.15-lite, etc.
### Practical-RIFE (Optional)
For PyTorch-based frame interpolation with latest models:
- Select **RIFE (Practical)** as the blend method
- Click **Setup PyTorch** to create an isolated venv with PyTorch (~2GB)
- Models auto-download from Google Drive on first use
- Available models: v4.26, v4.25, v4.22, v4.20, v4.18, v4.15
- Optional ensemble mode for higher quality (slower)
The venv is stored at `~/.cache/video-montage-linker/venv-rife/`
## Usage
@@ -98,7 +113,8 @@ video-montage-linker/
├── core/
│ ├── models.py # Enums, dataclasses
│ ├── database.py # SQLite session management
│ ├── blender.py # Image blending, RIFE downloader
│ ├── blender.py # Image blending, RIFE downloader, Practical-RIFE env
│ ├── rife_worker.py # Practical-RIFE inference (runs in isolated venv)
│ └── manager.py # Symlink operations
└── ui/
├── widgets.py # TrimSlider, custom widgets