Move installation to top, add shields.io badges, create visual model
comparison chart, use collapsible sections for node reference, condense
acknowledgments into a table with citations in a collapsible block.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add step-by-step instructions, CUDA version table, troubleshooting
section, and note that EMA-VFI works without cupy.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
No more pip calls at import time. Users get a clear error with
install instructions from the Load node if cupy is missing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
BIM-VFI, SGM-VFI, and GIMM-VFI Load nodes now check for cupy at
load time and raise a clear error with the user's CUDA version and
the exact pip install command. Updated README with step-by-step
cupy install instructions.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Dependencies are now handled by pyproject.toml / requirements.txt
via ComfyUI Manager or pip. Only cupy is auto-installed at load time
since it requires matching the PyTorch CUDA version; failures produce
a warning instead of crashing. Also added timm to requirements.txt.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Second IMAGE output exposes the full power-of-2 oversampled frames
before target FPS selection. Identical to the first output when
target_fps=0. Document the new output in README.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The Google Drive folder contains .pkl files but the default model
name used .pth, causing the post-download existence check to fail.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The concat node is model-agnostic (just joins video segments via
ffmpeg), so it shouldn't be under BIM-VFI. Now accepts any model type
as the dependency input and lives under the video/Tween category.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Update logger names, install prefixes, README clone instructions, and
error messages to reflect the new repo name. Model-specific node names
and categories (BIM-VFI, EMA-VFI, SGM-VFI) are unchanged.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
SGM-VFI combines local flow estimation with sparse global matching
(GMFlow) to handle large motion and occlusion-heavy scenes. Adds 3 new
nodes: Load SGM-VFI Model, SGM-VFI Interpolate, SGM-VFI Segment
Interpolate. Architecture files vendored from MCG-NJU/SGM-VFI with
device-awareness fixes (no hardcoded .cuda()), relative imports, and
debug code removed. README updated with model comparison table.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Integrate EMA-VFI alongside existing BIM-VFI with three new ComfyUI nodes:
Load EMA-VFI Model, EMA-VFI Interpolate, and EMA-VFI Segment Interpolate.
Architecture files vendored from MCG-NJU/EMA-VFI with device-awareness
fixes (removed hardcoded .cuda() calls), warp cache management, and
relative imports. InputPadder extended to support EMA-VFI's replicate
center-symmetric padding. Auto-installs timm dependency on first load.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
First startup may appear to hang while cupy (~800MB) installs.
Document manual fallback for environments where auto-install fails.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- chunk_size input splits input into overlapping segments processed
independently then stitched, bounding memory for 1000+ frame videos
while producing identical results to processing all at once
- Fix cache clearing logic: use counter instead of modulo so it triggers
regardless of batch_size value
- Replace inefficient torch.cat gather with direct tensor slicing
- Add README with usage guide, VRAM recommendations, and full
attribution to BiM-VFI (Seo, Oh, Kim — CVPR 2025, KAIST VIC Lab)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
