## Overview

Detects faces in an image and identifies 468 facial landmarks (key points) on each face using MediaPipe's BlazeFace and FaceMesh models. It also calculates ARKit-52 blendshape coefficients for facial expression analysis. The node can process multiple images in a batch and outputs both the landmark data and bounding boxes for each detected face.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| --- | --- | --- | --- | --- |
| `face_detection_model` | The MediaPipe face detection model to use for landmark detection. | FACE_DETECTION_MODEL | Yes |  |
| `image` | The input image or batch of images to detect faces in. | IMAGE | Yes |  |
| `detector_variant` | Face detector range. `"short"` is tuned for close-up faces (within ~2 m of the camera); `"full"` covers farther/smaller faces (up to ~5 m) but is slower. `"both"` runs both detectors and keeps whichever found more faces per frame (~2x detection cost). Default: `"short"`. | COMBO | Yes | `"short"`<br>`"full"`<br>`"both"` |
| `num_faces` | Maximum number of faces to return per frame. 0 means no cap (return all detected). Default: 1. | INT | Yes | 0 to 16 |
| `min_confidence` | BlazeFace score threshold. Lower values help catch small or occluded faces. Default: 0.5. | FLOAT | No | 0.00 to 1.00 |
| `missing_frame_fallback` | Per-frame behavior when detection fails in a batch. `"empty"` leaves the frame faceless. `"previous"` copies the most recent successful detection. `"interpolate"` lerps landmarks/bbox/blendshapes between bracketing successful frames. Multi-face: pairs faces across frames by greedy bbox-centre NN. Default: `"empty"`. | COMBO | No | `"empty"`<br>`"previous"`<br>`"interpolate"` |

## Outputs

| Output Name | Description | Data Type |
| --- | --- | --- |
| `face_landmarks` | A structured output containing per-frame face detection results, including 468 facial landmarks, ARKit-52 blendshape coefficients, transformation matrices, and connection sets for mesh visualization. | FACE_LANDMARKS |
| `bboxes` | A list of bounding boxes for each detected face, with coordinates (x, y, width, height), label "face", and confidence score. One list per input frame. | BOUNDING_BOX |

> 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/MediaPipeFaceLandmarker/en.md)

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