Welcome to My Project Documentation

Revolutionizing Retail with AI-Powered Solutions

On-Shelf Availability (OSA) Analysis

Intelligent Inventory Management for Modern Retail

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Project Team

This innovative project was developed by a team of students passionate about artificial intelligence and its practical applications in the retail sector, under the supervision of a recognized expert in the field.

Team Members

Faris Amine – AI & Data Technologies Engineering Student

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Es-safi Abderrahman – AI & Data Technologies Engineering Student

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Project Supervisor

Prof. Tawfik Masrour – Professor, AI Expert

Research Director in Applied Artificial Intelligence

Project Mentor & Academic Supervisor

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Project Details

Program:

IADT-SI (AI & Data Technologies)

Duration:

January 2025 - June 2025

Institution:

ENSAM Meknès

Field:

Artificial Intelligence, Computer Vision, Retail Analytics

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Table of Contents

This documentation provides comprehensive coverage of the On-Shelf Availability analysis project, from theoretical foundations to practical implementation.

Documentation Sections

• 1. Introduction
  • 1.1. Overview
  • 1.2. The Business Challenge
  • 1.3. Our Mission
  • 1.4. Comprehensive Solution Framework
  • 1.5. Implementation Benefits
• 2. Data Documentation
  • 2.1. Overview
  • 2.2. Data Sources and Collection
  • 2.3. Void Detection Dataset Development
  • 2.4. Product Detection Dataset
  • 2.5. Data Preprocessing Pipeline
  • 2.6. Related Resources
• 3. Dual YOLO Detection and Spatial Analysis System
  • 3.1. Overview
  • 3.2. Processing Pipeline
  • 3.3. System Architecture
  • 3.4. Spatial Context Analysis
  • 3.5. Spatial Clustering Algorithm
  • 3.6. Spatial Pattern Analysis
  • 3.7. Void Attribution System
  • 3.8. Multi-Factor Scoring System
  • 3.9. Inventory Estimation Module
  • 3.10. Visualization and Analysis Features
  • 3.11. Performance Specifications
  • 3.12. Configuration Parameters
  • 3.13. Future Enhancements
• 4. Trained Models
  • 4.1. Empty Space Detection (void.pt)
  • 4.2. Individual Product Detection (sku.pt)
  • 4.3. Technical Appendices
• 5. Intelligent Retail Shelf Analysis App
  • 5.1. Overview
  • 5.2. Features
  • 5.3. Installation
  • 5.4. Usage
  • 5.5. API Reference
  • 5.6. Configuration Options
  • 5.7. Performance Optimization
  • 5.8. Troubleshooting
  • 5.9. Best Practices
  • 5.10. Future Enhancements
  • 5.11. Version History
  • 5.12. Acknowledgments

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Getting Started

Note

New to this project?

We recommend starting with the Introduction section to understand the project scope, objectives, and problem statement before exploring the technical implementations.

Astuce

Navigation:

Use the table of contents above or the sidebar navigation to quickly access specific sections of the documentation.

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