An innovative educational project to explore, understand and test artificial intelligence freely.
The AI Fablab project was born from a simple observation: AI technologies are increasingly numerous and complex. Our mission is to make these tools accessible to everyone, from beginners to experts.
For this first year, the AI Fablab focuses on image processing.
Democratize access to artificial intelligence tools by creating a learning space where everyone can discover, understand and experiment with different AI models.
Become the INSA reference for hands-on learning of applied AI across multiple domains, offering a unique practical learning experience.
This project is part of the INSA Rennes 4INFO curriculum, in partnership with Teklia, a company specializing in document image analysis using artificial intelligence.
Duration: 2 semesters (September 2025 - May 2026)
2025-2026 theme: Image processing (future extensions: audio, video, text)
An interactive and educational encyclopedia dedicated to artificial intelligence models for image processing.
The AI Fablab is a web platform that centralizes and documents AI models. Inspired by physical FabLabs that provide tools and knowledge, our virtual Fablab guides you from theory to practice.
The AI Fablab separates tasks and models into different categories, with a modular architecture ready to support additional domains (audio, video, text).
5 classical tasks: object detection, OCR, segmentation, image similarity, and more.
A curated selection of models (YOLO, CLIP, ResNet, TesseractOCR...) is available in the AI Fablab.
Image analysis via keywords (CLIP, SigLIP), OCR (Tesseract, Paddle OCR, Qwen2.5-VL)
Classification (ResNet-50), face detection, depth estimation (Depth Pro), pose estimation (VITPose)
Image embeddings (ViT, DINOv3), similarity metrics (cosine, SSIM)
Aesthetic evaluation using HumanAesExpert and MUSIQ
Each model is documented with maximum detail:
The AI Fablab includes a secure admin interface to easily manage all content (domains, tasks, models).
It allows creating, editing and deleting entries directly from the browser, without technical skills or external tools.
An interactive application to test AI models on a collection of INSA Rennes photo archives.
The demonstrator is a web application that applies models from the Fablab in practice. It lets users explore real image archives (INSA 60-year archives) using AI tasks.
Learning by doing philosophy: theoretical concepts from the Fablab become directly testable in the demonstrator.
Image search engine using keywords. AI is transparent to the user, like Google Images.
Technologies: CLIP, SigLIP encoders, precomputed AI filters
Selection of tasks and models with ability to:
Detailed explanation of how the demonstrator is built.
Direct links to the Fablab for deeper understanding and full documentation.
Issue: running AI models in real time is too expensive for multiple users.
Solution: heavy precomputation
Result: near-instant responses even for complex queries (on ~4500 images dataset).
A modular and scalable architecture designed for maintainability and extensibility.
Two independent web applications:
Each has its own frontend (Angular) and backend (Python/FastAPI).
Common Python module that:
Docker for:
Hosting: VPS provided by INSA Rennes IT department
Angular
TypeScript framework
TypeScript
Static typing
HTML5 /
CSS3
Structure & design
Python
Main language
FastAPI
REST API framework
SQLite
Database
NumPy
Numerical computing
PyTorch
Deep Learning
Transformers
Hugging Face
OpenCV
Computer Vision
Docker
Containerization
Git /
GitLab
Version control
VSCode
Code editor
Teklia is a company specialized in automatic document analysis using artificial intelligence.
Contributions: