MediaPipe: Face Detection in ComfyUI

Portable or self deployed users
Desktop or Cloud users

Make sure your ComfyUI is updated.

Workflows in this guide can be found in the Workflow Templates. If you can’t find them in the template, your ComfyUI may be outdated. (Desktop version’s update will delay sometime)If nodes are missing when loading a workflow, possible reasons:

You are not using the latest ComfyUI version (Nightly version)
Some nodes failed to import at startup

MediaPipe is Google’s open-source machine learning solution for real-time perception. In ComfyUI, MediaPipe Face Detection provides BlazeFace detection, FaceMesh v2 landmark estimation, and ARKit-52 blendshapes — all in a single unified workflow. MediaPipe Face Detection is natively supported in ComfyUI (PR #14009), and the model weights are available under the Apache 2.0 License. MediaPipe GitHub | Comfy-Org Model Repository

Key capabilities

Fast face detection — BlazeFace-based detector with short (~2 m) and full (~5 m) range variants
478 facial landmarks — dense FaceMesh v2 keypoints per detected face
ARKit-52 blendshapes — real-time facial expression coefficients
Face region masks — per-region masks for face oval, lips, eyes, and irises
Face bounding boxes — outputs compatible with DrawBBoxes for bounding box visualization

Scope: Face detection only — BlazeFace + FaceMesh v2 + ARKit blendshapes. This does not cover hand, pose, or holistic detection.

MediaPipe Face Detection Workflow

1. Download the Workflow

Update your ComfyUI to the latest version, then go to Workflow → Browse Templates and find “Mediapipe: Image Face Detection” under the Utility category.

Download JSON Workflow File

Download workflow

Run on Comfy Cloud

Open in cloud

Download Sample Image

Get the example input image for this workflow

2. Download the Model

The MediaPipe Face Detection model is hosted on the Comfy-Org MediaPipe model repository.

mediapipe_face_fp32.safetensors

Place it in the following directory structure:

📂 ComfyUI/
└── 📂 models/
    └── 📂 detection/
        └── mediapipe_face_fp32.safetensors

3. Using the Workflow

This workflow uses a subgraph node that orchestrates face detection, visualization, and mask generation. The subgraph exposes the following controls:

Learn about Subgraph

This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.

Subgraph inputs:

Input	Description
image	Input image batch to analyze
face_landmarker	Optional. Leave empty to use the built-in model loader. Connect an external `FACE_DETECTION_MODEL` output to override

Subgraph parameters:

Parameter	Default	Description
model_name	`mediapipe_face_fp32.safetensors`	Checkpoint in `ComfyUI/models/detection/`. If missing, download the model above
detector_variant	`short`	short — tuned for close/large faces (~2 m range). full — covers smaller/farther faces (~5 m), slower. both — runs both detectors and keeps whichever found more faces per frame (~2× cost)
num_faces	`1`	Maximum faces to return per frame. `0` = no cap (return all detected). Range: 0–16
custom_face_oval	`false`	Include face-outline region in the mask output
custom_lips	`false`	Include lips in the mask (union with other enabled regions)
custom_left_eye	`false`	Include left eye region in the mask
custom_right_eye	`false`	Include right eye region in the mask
custom_irises	`false`	Include iris regions in the mask

Mask toggles use custom mode internally: only checked regions are filled; multiple ON regions are unioned into one mask per frame. Subgraph outputs:

Output	Type	Description
face_landmarks	`FACE_LANDMARKS`	Per-frame faces with 478 2D/3D landmarks, ARKit-52 blendshapes, mesh topology data — feeds into visualization and mask nodes
bboxes	`BOUNDING_BOX`	Face bounding boxes — compatible with `DrawBBoxes` node
mask	`MASK`	Binary mask from the enabled region toggles

4. Run the Workflow

Ensure the model file is placed in ComfyUI/models/detection/
Load an image in the Load Image node
Adjust detection parameters as needed
Click Queue or use Ctrl(Cmd) + Enter to run
The workflow outputs the mesh overlay, bounding boxes, and mask preview

Community Resources

MediaPipe GitHub — Upstream MediaPipe framework
Comfy-Org/mediapipe — Official ComfyUI model weights
ComfyUI Subgraph Guide — Learn how subgraphs work

​Key capabilities

​MediaPipe Face Detection Workflow

​1. Download the Workflow