ComfyUI-OpenCV-Overlays

This project integrates OpenCV and YOLOv8 into ComfyUI, providing custom nodes for object detection, blob tracking, and aesthetic video overlays.

Overview

The ComfyUI-CVOverlay package provides four main custom nodes:

• CV Model Loader: Loads YOLO models for object detection
• CV Object Detector: Performs real-time object detection using YOLOv8
• CV Blob Tracker: Implements blob tracking algorithms using OpenCV
• CV Aesthetic Overlay: Applies customizable technical/surveillance-style overlays

Features

✨ Lightweight Integration: Minimal dependencies, optimized for ComfyUI workflows
🎯 Multiple Detection Models: Support for YOLOv8n through YOLOv8x models
🎨 Aesthetic Overlays: Technical, surveillance, minimal, and cyberpunk styles
📹 Video Processing: Frame-by-frame processing for video workflows
🎛️ Full Control: Confidence thresholds, colors, opacity, line thickness

Installation

Method 1: Using ComfyUI-Manager (Recommended)

1. Install ComfyUI-Manager if you haven't already
2. Open ComfyUI-Manager in ComfyUI
3. Go to "Install Custom Nodes"
4. Search for "ComfyUI-CVOverlay" and click Install
5. Restart ComfyUI

Method 2: Manual Installation

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

   git clone https://github.com/joosthel/ComfyUI-CVOverlay.git
   

3. Dependencies will be automatically installed by ComfyUI-Manager on next startup
4. Restart ComfyUI

Note: ComfyUI-Manager will automatically handle the installation of required dependencies (opencv-python, ultralytics, torch, etc.) when you restart ComfyUI.

Quick Start

1. Load Model: Use CV Model Loader with yolov8n.pt (lightweight)
2. Detect Objects: Connect your image to CV Object Detector
3. Apply Style: Use CV Aesthetic Overlay to visualize detections
4. Save Result: Connect to ComfyUI's Save Image node

See USAGE.md for detailed examples and workflows.

Node Reference

CV Model Loader

• Loads YOLO models (n/s/m/l/x variants)
• Supports custom trained models
• Output: CV_MODEL

CV Object Detector

• Input: CV_MODEL, IMAGE
• Configurable confidence and IOU thresholds
• Output: IMAGE, CV_DETECTIONS

CV Blob Tracker

• Input: IMAGE, (optional) CV_TRACKS
• Multiple tracking algorithms
• Output: IMAGE, CV_TRACKS

CV Aesthetic Overlay

• Input: IMAGE, (optional) CV_DETECTIONS, CV_TRACKS
• Multiple overlay styles and color schemes
• Output: IMAGE

Project Structure

ComfyUI-CVOverlay/
├── __init__.py              # ComfyUI node registration
├── requirements.txt         # Dependencies
├── USAGE.md                # Usage examples and workflows
├── nodes/                  # Custom nodes
│   ├── cv_model_loader.py
│   ├── cv_object_detector.py
│   ├── cv_blob_tracker.py
│   └── cv_aesthetic_overlay.py
└── utils/                  # Helper functions
    ├── opencv_helpers.py
    └── yolo_utils.py

Requirements

• Python ≥ 3.8
• ComfyUI
• OpenCV ≥ 4.8.0
• Ultralytics (YOLOv8) ≥ 8.0.0
• PyTorch ≥ 1.11.0

Contributing

Contributions welcome! Please submit pull requests or open issues for enhancements and bug fixes.

License

MIT License - see LICENSE file for details.