ComfyUI DINO-X Detector Node

A ComfyUI node that integrates DINO-X API for object detection and segmentation. This node allows you to detect and segment objects in images using text prompts.

Features

• Text prompt-based object detection
• Bounding box visualization
• Instance segmentation masks
• Configurable detection threshold
• Support for multiple objects per image
• Real-time visualization

Installation

1. Get your DINO-X API token:

   • Visit DeepDataSpace
   • Register and request an API token
   • Save your token for use with the node

2. Install the node in your ComfyUI custom_nodes directory:

cd ComfyUI/custom_nodes
git clone https://github.com/yourusername/comfyui-dinox-detector
cd comfyui-dinox-detector
pip install -e .

Usage

1. In ComfyUI, find the "DINO-X Object Detector" node under the "detection" category

2. Connect your inputs:

   • image: The input image to process
   • text_prompt: Text description of objects to detect (e.g. "wheel . eye . helmet")
   • api_token: Your DINO-X API token
   • bbox_threshold: Detection confidence threshold (0.0-1.0)

3. The node outputs:

   • box_annotated: Image with bounding boxes and labels
   • mask_annotated: Image with instance segmentation masks

Example Workflow

1. Load Image → DINO-X Object Detector → Preview Image

{
  "3": {
    "class_type": "LoadImage",
    "inputs": {
      "image": "example.jpg"
    }
  },
  "4": {
    "class_type": "DinoxDetector",
    "inputs": {
      "image": ["3", 0],
      "text_prompt": "person . car . dog . cat . bird",
      "api_token": "your-api-token-here",
      "bbox_threshold": 0.25
    }
  },
  "5": {
    "class_type": "PreviewImage",
    "inputs": {
      "images": ["4", 0]
    }
  },
  "6": {
    "class_type": "PreviewImage",
    "inputs": {
      "images": ["4", 1]
    }
  }
}

Development

Running Tests

1. Install development dependencies:

pip install -e ".[dev]"

2. Run the tests:

pytest dinox_detector/test_node.py -v

The tests cover:

• Input validation
• API interaction (mocked)
• Real-world image testing
• Image processing
• Error handling

Test Assets

The test suite includes:

• Synthetic test images for basic functionality testing
• Real-world test image (leather jacket) for realistic detection scenarios

Test assets are stored in the test_assets directory.

License

This node is released under the Apache 2.0 license. See LICENSE file for details.