Spaces:
Build error
Build error
| title: Makerspace Inventory AI | |
| emoji: 🔧 | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: "5.50.0" | |
| app_file: app.py | |
| pinned: false | |
| # 🔧 Makerspace Inventory Management System | |
| An intelligent, AI-powered inventory management system designed for makerspaces, workshops, and educational facilities. This system combines computer vision, natural language processing, and optimization algorithms to streamline inventory tracking and improve workspace efficiency. | |
|  | |
|  | |
|  | |
| ## 🌟 Features | |
| ### 🛒 **Smart Check-Out System** | |
| - **AI-Powered Image Recognition**: Upload photos or use your webcam to automatically identify tools and equipment | |
| - **Gemini Vision AI**: Utilizes Google's Gemini 2.5 Flash model for accurate item detection | |
| - **Vector Search**: ChromaDB-powered semantic search for fuzzy matching between detected items and inventory | |
| - **Real-time Inventory Updates**: Automatic quantity tracking and session logging | |
| - **Multi-Item Support**: Scan multiple items in a single image | |
| ### 📦 **Intelligent Item Addition** | |
| - **OCR Receipt Processing**: Upload PDF or image receipts to automatically extract items | |
| - **Fuzzy Matching**: Smart name matching to find items even with typos or variations | |
| - **Interactive Editing**: Review and modify detected items before adding to inventory | |
| - **Manual Entry**: Quick single-item updates with auto-completion | |
| - **Update History**: Complete audit trail of all inventory changes | |
| ### 📊 **Data-Driven Layout Optimization** | |
| - **Pattern Mining**: Discovers which items are frequently checked out together | |
| - **Association Rules**: Calculates support, confidence, and lift metrics for item pairs | |
| - **Distance Optimization**: Uses greedy relocation algorithm to minimize walking distance | |
| - **Visual Analytics**: Side-by-side comparison of current vs. optimized layouts | |
| - **Actionable Recommendations**: Specific move suggestions with quantified benefits | |
| ## 🚀 How to Use | |
| ### Check Out Items | |
| 1. Click **"🛒 Check Out Items"** on the main menu | |
| 2. Upload an image of items or use your webcam | |
| - Or manually type item names (comma-separated) | |
| 3. Review detected items and adjust quantities | |
| 4. Confirm checkout (optionally enter user ID) | |
| ### Add Items to Inventory | |
| 1. Click **"📦 Add Items"** on the main menu | |
| 2. **Receipt Upload Tab**: | |
| - Upload a PDF or image receipt | |
| - Review extracted items | |
| - Check/uncheck items to include | |
| - Edit quantities if needed | |
| - Click "Apply Updates" | |
| 3. **Manual Entry Tab**: | |
| - Type item name | |
| - Enter quantity | |
| - Click "Add to Inventory" | |
| ### Analyze Layout Efficiency | |
| 1. Click **"📊 Inventory Analysis"** on the main menu | |
| 2. Adjust analysis parameters: | |
| - **Minimum Support**: Pattern frequency threshold (0.02 = 2%) | |
| - **Top K Pairs**: Number of frequent pairs to optimize (25) | |
| - **Maximum Moves**: Limit on relocations (10) | |
| - **Minimum Gain**: Distance improvement threshold (0.05 units) | |
| 3. Click "🔍 Run Analysis" | |
| 4. Review: | |
| - Frequent item pairs | |
| - Relocation recommendations | |
| - Distance savings | |
| - Visual layout comparison | |
| ## 📈 Key Metrics Explained | |
| ### **Support** | |
| Frequency of items appearing together in checkout sessions | |
| - Example: 0.10 = items appear together in 10% of checkouts | |
| ### **Lift** | |
| How much more likely items are checked out together vs. randomly | |
| - Lift > 1: Positive correlation (should be near each other) | |
| - Lift = 2: Items are 2× more likely to be checked out together | |
| ### **Confidence A→B** | |
| Probability of checking out item B when checking out item A | |
| - Example: 0.80 = 80% chance of checking B with A | |
| ### **Distance Saved** | |
| Reduction in walking distance by relocating items | |
| - Measured in grid units (1 unit ≈ 1 meter) | |
| ## 🛠️ Technology Stack | |
| - **Frontend**: Gradio 5.9 (Interactive web interface) | |
| - **AI/ML**: | |
| - Google Gemini 2.5 Flash (Vision AI for image recognition) | |
| - Sentence Transformers (Semantic embeddings) | |
| - ChromaDB (Vector database for similarity search) | |
| - **OCR**: Tesseract + Pytesseract | |
| - **Data Processing**: Pandas, NumPy | |
| - **Optimization**: Custom greedy algorithm for layout optimization | |
| - **Visualization**: Matplotlib | |
| - **Fuzzy Matching**: RapidFuzz | |
| ## 📂 File Structure | |
| ``` | |
| . | |
| ├── app.py # Main application file | |
| ├── requirements.txt # Python dependencies | |
| ├── README.md # This file | |
| ├── items.csv # Inventory database | |
| ├── locations.csv # Physical location grid | |
| ├── checkouts.csv # Checkout history | |
| ├── update_log.csv # Inventory update log | |
| ├── screwdriver.png # Example checkout image | |
| └── mcmaster_receipt.pdf # Example receipt | |
| ``` | |
| ## 🔧 Local Setup | |
| ### Prerequisites | |
| - Python 3.10 or higher | |
| - Tesseract OCR installed on your system | |
| ### Installation | |
| 1. Clone the repository: | |
| ```bash | |
| git clone <repository-url> | |
| cd makerspace-inventory | |
| ``` | |
| 2. Install system dependencies (Ubuntu/Debian): | |
| ```bash | |
| sudo apt-get update | |
| sudo apt-get install -y tesseract-ocr poppler-utils | |
| ``` | |
| 3. Install Python dependencies: | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| 4. Run the application: | |
| ```bash | |
| python app.py | |
| ``` | |
| 5. Open your browser to `http://localhost:7860` | |
| ### Environment Variables | |
| The Gemini API key is currently hardcoded. For production use, set it as an environment variable: | |
| ```bash | |
| export GEMINI_API_KEY="your-api-key-here" | |
| ``` | |
| ## 📊 Data Format | |
| ### items.csv | |
| ```csv | |
| item_id,item_name,category,quantity,unit,description,location_id | |
| I0001,Hex Key Set,Hand Tools,12,sets,Standard SAE hex key sets,L001 | |
| ``` | |
| ### locations.csv | |
| ```csv | |
| location_id,x,y,capacity | |
| L001,0,0,1 | |
| ``` | |
| ### checkouts.csv | |
| ```csv | |
| timestamp,user_id,session_id,item_id | |
| 2025-12-05T10:30:00Z,U0001,S00001,I0001 | |
| ``` | |
| ## 🎯 Use Cases | |
| - **Makerspaces & Fab Labs**: Track tools and equipment usage | |
| - **Educational Workshops**: Monitor student equipment checkouts | |
| - **Tool Libraries**: Manage community tool sharing | |
| - **Research Labs**: Optimize equipment layout based on usage patterns | |
| - **Manufacturing Facilities**: Improve tool room efficiency | |
| ## 🤝 Contributing | |
| Contributions are welcome! Please feel free to submit issues or pull requests. | |
| ### Development Roadmap | |
| - [ ] Barcode/QR code scanning | |
| - [ ] User authentication system | |
| - [ ] Advanced analytics dashboard | |
| - [ ] Mobile app integration | |
| - [ ] Multi-location support | |
| - [ ] Automated reorder suggestions | |
| - [ ] Integration with purchasing systems | |
| ## 📝 License | |
| This project is licensed under the MIT License - see the LICENSE file for details. | |
| ## 👥 Authors | |
| Developed as part of a makerspace automation project. | |
| ## 🙏 Acknowledgments | |
| - Google Gemini AI for vision capabilities | |
| - Anthropic Claude for development assistance | |
| - Open-source community for amazing tools and libraries | |
| ## 📞 Support | |
| For questions, issues, or feature requests, please open an issue on GitHub or contact the development team. | |
| --- | |
| **Built with ❤️ for makers, by makers** | |