Documentation Index
Fetch the complete documentation index at: https://mintlify.com/AprendeIngenia/reciclaje_ai/llms.txt
Use this file to discover all available pages before exploring further.
Overview
Before installing Reciclaje AI, ensure your system meets the following requirements for optimal performance of the waste detection and classification system.Hardware Requirements
Minimum Requirements
- CPU: Dual-core processor (2.0 GHz or higher)
- RAM: 4 GB
- Storage: 2 GB free disk space
- Webcam: USB or built-in camera for real-time detection
- GPU: Not required (CPU inference supported)
Recommended Requirements
- CPU: Quad-core processor (3.0 GHz or higher)
- RAM: 8 GB or more
- Storage: 5 GB free disk space (for model files and datasets)
- Webcam: HD camera (720p or higher) for better detection accuracy
- GPU: NVIDIA GPU with CUDA support for faster inference
- CUDA 11.x or higher
- cuDNN 8.x or higher
- 4GB+ VRAM recommended
While a GPU is not required, it significantly improves real-time detection performance, especially for high-resolution video streams.
Software Requirements
Operating System
Reciclaje AI is compatible with the following operating systems:- Windows: 10 or 11 (64-bit)
- macOS: 10.15 (Catalina) or later
- Linux: Ubuntu 18.04+, Debian 10+, or equivalent distributions
Python Version
- Python 3.8 - 3.11 (recommended: Python 3.10)
Core Dependencies
The following Python packages are required:| Package | Version | Purpose |
|---|---|---|
ultralytics | Latest | YOLOv8 model framework |
opencv-python | 4.5.0+ | Computer vision and video processing |
numpy | 1.21.0+ | Numerical computations |
Pillow | 8.0.0+ | Image processing for GUI |
imutils | 0.5.4+ | Image manipulation utilities |
tkinter | Built-in | Graphical user interface |
Camera Requirements
Supported Cameras
- USB webcams (UVC-compatible)
- Built-in laptop cameras
- External IP cameras (with appropriate streaming configuration)
Camera Specifications
- Resolution: 640x480 minimum (1280x720 recommended)
- Frame Rate: 15 FPS minimum (30 FPS recommended)
- Connection: USB 2.0 or higher
The application is configured to use camera index 0 by default. If you have multiple cameras, you may need to modify the camera index in the source code.
Network Requirements
For Model Download
- Active internet connection (required for initial setup)
- Minimum 10 Mbps download speed recommended
- Access to HuggingFace (huggingface.co)
For Runtime
- No internet connection required after installation
- All processing is performed locally
Display Requirements
- Resolution: 1280x720 minimum (for GUI application)
- Color Depth: 24-bit or higher
Storage Space Breakdown
- Python packages: ~1.5 GB
- YOLOv8 model file: ~6 MB
- GUI assets: ~5 MB
- Additional space: 500 MB (for temporary files and logs)
Platform-Specific Notes
Windows
- Visual C++ Redistributable may be required for OpenCV
- Windows Defender may flag the application during first run
macOS
- Command Line Tools for Xcode required
- Camera permissions must be granted in System Preferences
Linux
- GTK+ or Qt libraries required for OpenCV GUI support
- Camera access permissions may need to be configured
Verification
To check your Python version:Next Steps
Once you’ve verified your system meets these requirements, proceed to:Setup Guide
Install Python dependencies and configure your environment
Model Download
Download the pre-trained YOLOv8 model from HuggingFace