65 lines
2.5 KiB
Markdown
65 lines
2.5 KiB
Markdown
# ComfyUI-Lee-RIFE
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Fast, **GPU-batched** RIFE frame interpolation for ComfyUI — a self-contained node
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with the weights bundled, no extra dependencies.
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## What it does
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* Runs RIFE (`rife49.pth`, architecture v4.7) **on the GPU in batches** instead of
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one frame-pair at a time.
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* Enables RIFE's **real bidirectional ensemble** (a forward and a time-reversed
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pass, averaged) for cleaner motion.
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* `fp16` by default (visually identical to `fp32` for interpolation, roughly 2×
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faster on modern NVIDIA cards); `fp32` selectable.
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* Automatically halves the batch on out-of-memory, so it scales from small cards
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to big ones.
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## Requirements
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* ComfyUI
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* An NVIDIA GPU with a CUDA build of PyTorch (the same one ComfyUI already uses).
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* **No extra pip installs** — it only uses what ComfyUI provides.
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## Install
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1. Copy the `ComfyUI-Lee-RIFE` folder into `ComfyUI/custom_nodes/`
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(or `git clone` it there).
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2. Make sure `models/rife49.pth` is present (it ships with this repo;
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see `models/HOW-TO-ADD-WEIGHTS.txt` if it is missing).
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3. Restart ComfyUI completely (the process, not just the browser tab).
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The node appears as **“RIFE GPU Fast (Lee)”** under the **Lee/RIFE** category.
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## Usage
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Wire your frames into `frames`. For doubling 15 fps → 30 fps, set `multiplier = 2`
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and set your video-output node to 30 fps.
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|Parameter|Meaning|
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|`multiplier`|Output frames per input frame (2 = double the frame rate).|
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|`ensemble`|Bidirectional pass (better quality, \~2× the work). On by default.|
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|`scale\_factor`|Internal flow scale; leave at `1.0` unless resolution is very high.|
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|`precision`|`fp16` (fast) or `fp32` (bit-faithful to the original node).|
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|`batch\_size`|Frame-pairs per GPU batch. Higher = better GPU use; lowers itself on OOM.|
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**Output count:** for `multiplier = m` and `N` input frames you get `m × N`
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frames (e.g. 81 frames at 15 fps → 162 frames at 30 fps, same duration).
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On the first run you will see a console line like
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`\[ComfyUI-Lee-RIFE] loaded rife49.pth (arch 4.7) on cuda:0 / torch.float16`,
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confirming it is on the GPU.
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## Credits \& license
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This node's own code is **MIT** (see `LICENSE`), © 2026 Smai-Lee.
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It builds on:
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* **RIFE / Practical-RIFE** (Zhewei Huang et al.) — the model and architecture (MIT).
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* **ComfyUI-Frame-Interpolation** (Fannovel16) — `rife_arch.py` is vendored from it (MIT).
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Full attribution and the upstream license texts are in **`THIRD-PARTY-NOTICES.md`**.
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Please cite the RIFE paper if you use this in research (citation in the notices file).
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