Extensions/ComfyUI-VFI
ComfyUI Extension

ComfyUI-VFI

ComfyUI-RIFE is an inference wrapper for RIFE designed for use with ComfyUI.

By GACLove·Created about a year ago·Updated 10 months ago· 55
GACLove/ComfyUI-VFI
Nodes2
On cloudLocal install
Categoryimage/animation
Stars55
Updated10 months ago
Readme

ComfyUI-VFI

Video Frame Interpolation nodes for ComfyUI using RIFE (Real-Time Intermediate Flow Estimation).

RIFE

Features

  • High-quality frame interpolation using RIFE
  • Convert between different frame rates (e.g., 30fps to 60fps)
  • Adjustable processing scale for performance/quality trade-off
  • Model caching for efficient processing
  • Progress tracking in ComfyUI

Installation

  • Clone this repository into your ComfyUI custom_nodes directory:
cd ComfyUI/custom_nodes
git clone https://github.com/your-username/ComfyUI-VFI.git
  • Install required dependencies:
cd ComfyUI-VFI
pip install -r requirements.txt
  • The RIFE model will be automatically downloaded on first use
    • Alternatively, you can manually place flownet.pkl in:
      • ComfyUI-VFI/rife/train_log/
      • Or ComfyUI/models/rife/

Usage

The node will appear in the "image/animation" category as "RIFE Frame Interpolation".

Inputs

  • images: Image sequence tensor [N, H, W, C]
  • source_fps: Original frame rate (default: 30.0)
  • target_fps: Desired frame rate (default: 60.0)
  • scale: Processing scale factor (default: 1.0)
    • Lower values (0.25-0.5) for faster processing
    • Higher values (1.0-4.0) for better quality

Output

  • images: Interpolated image sequence tensor

Example Workflow

  1. Load video frames using a video loader node
  2. Connect to RIFE Frame Interpolation node
  3. Set source and target FPS
  4. Connect output to video encoder or preview

Model Download

The RIFE model (flownet.pkl) can be downloaded from the official RIFE repository.