FUNCAP Image Matching API

Supports multiple FunCaptcha variants, loads models smart so it’s quick, and gives you back the best match with no fuss.

Features

• Fast image similarity matching using ONNX Runtime
• Support for multiple variants/models
• Simple REST API interface
• Cross-origin resource sharing (CORS) enabled

Installation

1. Clone this repository:

   git clone https://github.com/ziad-gg/fcap-classification.git
   cd fcap-classification
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Ensure you have the proper model files in the models directory:

   mkdir -p models
   # Place your .onnx model files in the models directory
   

Usage

1. Start the Flask server:

   python server.py
   

2. Send a POST request to /match_image endpoint with:

   • image: Base64-encoded image data
   • variant: The variant/model to use for matching

Example Request

{
  "image": "base64_encoded_image_data_here",
  "variant": "waterIconCup"
}

Example Response

{
  "success": true,
  "result": {
    "best_match_index": 2,
    "similarity_score": 0.87
  }
}

Supported Variants

Variant Name	Description	Available
waterIconCup	WaterIconCup model	✅ Basic version
bowling	bowling model	✅ Basic version

Premium Models

For higher accuracy models and additional variants, contact @ziaath on Telegram. Premium models offer:

• Higher accuracy rates
• Faster processing
• Support for more image types
• Custom training for your specific use cases

API Reference

POST /match_image

Matches a reference image against potential matches using the specified model variant.

Parameters:

• image (required): Base64-encoded image data
• variant (optional): Model variant to use (defaults to "waterIconCup")

Responses:

• 200: Successful operation with match results
• 400: Bad request (missing parameters)
• 500: Server error

License

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.