> ## 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.

# LoadMediaPipeFaceLandmarker - ComfyUI Built-in Node Documentation

> Complete documentation for the LoadMediaPipeFaceLandmarker 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/LoadMediaPipeFaceLandmarker/en.md)

## Overview

This node loads a MediaPipe Face Landmarker v2 model, which can detect faces and facial landmarks (like eyes, nose, and mouth) in images. It contains two detection variants (short-range and full-range) along with shared mesh data, blendshapes, and canonical geometry for facial analysis.

## Inputs

| Parameter    | Data Type | Required | Range                                                         | Description                                  |
| ------------ | --------- | -------- | ------------------------------------------------------------- | -------------------------------------------- |
| `model_name` | STRING    | Yes      | List of available models in the `models/detection/` directory | Face detection model from models/detection/. |

## Outputs

| Output Name            | Data Type              | Description                                                                                                                                                                       |
| ---------------------- | ---------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `FACE_DETECTION_MODEL` | FACE\_DETECTION\_MODEL | A loaded FaceLandmarker model object containing both detection variants (short/full), connection sets for facial topology, canonical data, and model patchers for GPU management. |

**Note:** The output is a complex object that can be used by other nodes for face detection and landmark extraction tasks. It contains two detection variants: "short" for close-range detection and "full" for full-range detection.

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