README.md

metadata

title: Petri Net Converter Suite
emoji: 🔄
colorFrom: blue
colorTo: purple
sdk: docker
app_port: 7860
pinned: false
license: mit

Petri Net Converter Suite

A Gradio-based application that converts hand-drawn Petri net sketches into digital formats using computer vision and OCR.

Demo

🚀 Try the live demo on Hugging Face Spaces

What it does

The application processes images of Petri net diagrams and automatically:

• Detects places, transitions, and arcs using computer vision
• Extracts text labels using OCR
• Converts the detected elements into standard formats (PNML, JSON, GraphViz, etc.)
• Provides visual feedback of the detection process

Setup

Requirements

Python 3.8+ and the dependencies listed in requirements.txt.

Installation

1. Clone the repository:

git clone <repository-url>
cd petri-net-converter

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment variables (optional, for full functionality):

cp env.example .env
# Edit .env and add your API keys:
# GROQ_API_KEY=your_groq_api_key_here
# ROBOFLOW_API_KEY=your_roboflow_api_key_here

4. Run the application:

python app.py

The application will start on http://localhost:7860.

Usage

1. Image Processor Tab: Upload an image of a Petri net sketch and a YAML configuration file, then click "Process"
2. Configuration Editor Tab: Create or modify YAML configuration files for processing parameters
3. Petri Net Converter Tab: Convert processed results into various output formats

Supported Formats

• Input: PNG, JPG, JPEG images + YAML configuration files
• Output: PNML (XML), PetriObj, JSON, GraphViz DOT, PNG visualizations

License

MIT License