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- Status
- Verificado
- Publicador
- @ethanfel
- Fonte
- GitHub
README
Tween — Video Frame Interpolation for ComfyUI
ComfyUI Python 3.10+ License Models
Six video frame interpolation models in one package — BIM-VFI, EMA-VFI, SGM-VFI, GIMM-VFI, SPEED, and LDF-VFI. Pairwise models include chunked/segmented processing; LDF-VFI adds holistic long-sequence diffusion interpolation.
Installation
Install from the ComfyUI Registry (recommended) or clone manually:
cd ComfyUI/custom_nodes
git clone https://github.com/Ethanfel/ComfyUI-Tween.git
pip install -r requirements.txt
Dependencies are declared in pyproject.toml and requirements.txt and are installed automatically by ComfyUI Manager or pip. There is intentionally no custom install.py, avoiding a second redundant dependency-install pass after Manager processes requirements.txt. LDF-VFI requires PyTorch 2.5+ plus a current diffusers/accelerate stack.
Demo workflow
Import example_workflows/tween_speed_bim_model_lab.json for the recommended starter graph. It requires ComfyUI-VideoHelperSuite for video loading and encoding.
- The SPEED and BIM-VFI branches load the same 25-frame, 24 FPS sample, tune memory settings independently, interpolate to 48 FPS, preserve audio, and save separate comparison videos.
- Keep the loader's
force_rate, Tween'ssource_fps/target_fps, and Video Combine'sframe_ratesynchronized when changing cadence.
cupy (accelerates BIM-VFI, SGM-VFI, and GIMM-VFI)
cupy provides GPU-accelerated optical flow warping. It is deliberately not installed automatically, because replacing or mixing CUDA-specific cupy wheels can disrupt other ComfyUI nodes. BIM-VFI, SGM-VFI, and GIMM-VFI work without it through their PyTorch fallback. EMA-VFI, SPEED, and LDF-VFI do not use it.
-
Find your CUDA version:
python -c "import torch; print(torch.version.cuda)" -
Install the matching package:
CUDA Command 13.x pip install cupy-cuda13x12.x pip install cupy-cuda12x11.x pip install cupy-cuda11x
Make sure to run pip in the same Python environment as ComfyUI, and uninstall any different cupy wheel variant first. If cupy is absent or incompatible, Tween safely uses its PyTorch fallback.
| Problem | Solution |
|---|---|
ModuleNotFoundError: No module named 'cupy' | Install cupy using the steps above |
cupy installed but ImportError at runtime | CUDA version mismatch — uninstall and reinstall the correct version |
| Install hangs or takes very long | Confirm pip selected a prebuilt wheel for your Python and CUDA versions |
| Docker / no build tools | Use the matching prebuilt cupy-cudaXXx wheel, not bare cupy which compiles from source |
Which model should I use?
| Model | Best for | Multiplier path | Typical VRAM | Trade-off |
|---|---|---|---|---|
| BIM-VFI | Strong general pairwise quality | Recursive 2x/4x/8x | ~2 GB/pair | Research/education license |
| EMA-VFI | Speed and lower VRAM | Recursive 2x/4x/8x | ~1.5 GB/pair | Less robust on extreme motion |
| SGM-VFI | Large motion | Recursive 2x/4x/8x | ~3 GB/pair | Slowest pairwise option |
| GIMM-VFI | Arbitrary timesteps, efficient 4 |
Nós neste pacote
Nós 19
Nós neste pacote
Nós 19- BIMVFIInterpolate
- BIMVFISegmentInterpolate
- EMAVFIInterpolate
- EMAVFISegmentInterpolate
- GIMMVFIInterpolate
- GIMMVFISegmentInterpolate
- LDFVFIInterpolate
- LoadBIMVFIModel
- LoadEMAVFIModel
- LoadGIMMVFIModel
- LoadLDFVFIModel
- LoadSGMVFIModel
- LoadSPEEDVFIModel
- SGMVFIInterpolate
- SGMVFISegmentInterpolate
- SPEEDVFIInterpolate
- SPEEDVFISegmentInterpolate
- TweenConcatVideos
- VFIOptimizer
Fontes
2 fontes
Fontes
2 fontesVerificado 11 de out.
Trechos de fonte
1 trecho
Trechos de fonte
1 trechoSource context: Repo ethanfel/ComfyUI-Tween
