ComfyUI Face Detection Node

A ComfyUI custom node for face detection and cropping using OpenCV Haar cascades, with full ComfyUI v3 schema support and backward compatibility.

Features

• Face Detection: Uses OpenCV Haar cascade classifiers for robust face detection
• Flexible Cropping: Crop largest face or all detected faces
• Adjustable Parameters: Configurable detection threshold, minimum face size, and padding
• Multiple Classifiers: Choose between default and alternative Haar cascades
• ComfyUI v3 Ready: Full schema support with backward compatibility for v1/v2
• Async Execution: Stateless execution pattern for better performance

Installation

Via ComfyUI Manager (Recommended)

1. Open ComfyUI Manager
2. Search for "Face Detection Node"
3. Click Install

Manual Installation

1. Navigate to your ComfyUI custom nodes directory
2. Clone this repository:

   git clone https://github.com/Limbicnation/ComfyUI_FaceDetectionNode.git
   cd ComfyUI_FaceDetectionNode
   pip install -r requirements.txt
   

Usage

1. Add the "Face Detection and Crop" node to your workflow
2. Connect an image input
3. Adjust parameters:
   • Detection Threshold: Confidence threshold (0.1-1.0)
   • Min Face Size: Minimum face size in pixels (32-512)
   • Padding: Padding around detected faces (0-256)
   • Output Mode: "largest_face" or "all_faces"
   • Face Output Format: "strip" (horizontal layout) or "individual" (separate batch items)
   • Classifier Type: "default" or "alternative"

Parameters

| Parameter | Type | Range | Default | Description | |-----------|------|-------|---------|-------------| | detection_threshold | Float | 0.1-1.0 | 0.8 | Face detection confidence threshold | | min_face_size | Int | 32-512 | 64 | Minimum size for detected faces | | padding | Int | 0-256 | 32 | Padding around detected faces | | output_mode | Combo | - | largest_face | Output mode for detected faces | | face_output_format | Combo | - | strip | Format for multiple faces (strip/individual) | | classifier_type | Combo | - | default | Haar cascade classifier type |

Compatibility

• ComfyUI v3: Full schema support with async execution
• ComfyUI v1/v2: Backward compatibility via wrapper class
• Auto-detection: Automatically selects appropriate implementation

Requirements

• Python ≥ 3.8
• OpenCV ≥ 4.5.0
• PyTorch ≥ 1.9.0
• NumPy ≥ 1.21.0
• Pillow ≥ 8.0.0

License

Apache License Version 2.0, January 2004 - see LICENSE file for details.