> ## Documentation Index
> Fetch the complete documentation index at: https://docs.comfy.org/llms.txt
> Use this file to discover all available pages before exploring further.

# OpticalFlowLoader - ComfyUI Built-in Node Documentation

> Complete documentation for the OpticalFlowLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpticalFlowLoader/en.md)

## Overview

Loads an optical flow model from the `models/optical_flow/` folder. Currently, only torchvision's RAFT-large format is supported, which is the model used by the VOIDWarpedNoise node. ComfyUI does not download optical flow weights automatically; you must place the checkpoint file manually in the `models/optical_flow/` directory.

## Inputs

| Parameter    | Data Type | Required | Range                                          | Description                                                                                                                            |
| ------------ | --------- | -------- | ---------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------- |
| `model_name` | STRING    | Yes      | List of files in `models/optical_flow/` folder | Optical flow model to load. Files must be placed in the `optical_flow` folder. Today only torchvision's `raft_large.pth` is supported. |

## Outputs

| Output Name    | Data Type | Description                                                                        |
| -------------- | --------- | ---------------------------------------------------------------------------------- |
| `OPTICAL_FLOW` | MODEL     | The loaded optical flow model, wrapped in a ModelPatcher for use with other nodes. |

***

**Source fingerprint (SHA-256):** `62f79c2e96fafe4856321481bdc22ca474e65be2bb4c117cb0e929ff33e75d5a`