C

computer vision

The main project for OctoMY™ - Ready-to-run robot software

ICL : Intellisrc Common Library : This library can help you to write less code and speedup the development of your next great application. It is particularly designed to accomplish most of the common tasks required by backend services.

Active contour (level-set) image processing engine written in modern C++.

Fluvel is a region-based active contour engine focused on clarity, performance, and clean architecture. The core processing logic is independent from the UI, allowing reuse as a standalone library.

The project is currently under active development.

A synthetic dataset generation and detection pipeline for counting coins and identifying those showing "tails" in images. It combines YOLOv26m for detection with a CoinCLIP-based SVM classifier, and includes a custom NMS post-processing step to improve counting accuracy.

Pictures blurring API for a Panoramax instance.

Was previously hosted at https://github.com/cquest/sgblur

A computer vision solution implemented in Python that utilizes deep learning techniques to classify food imagery for dietary analysis and nutritional tracking.

idtracker.ai tracks up to 100 unmarked animals from videos recorded in laboratory conditions using artificial intelligence. Free and open source.

German number plates data for computer vision

Ce projet constitue mon projet de fin d'études et porte sur la conception et le déploiement d'une solution de vision par ordinateur destinée à la détection automatique des risques et non-conformités liés au port des équipements de protection individuelle (EPI) sur les chantiers.

L'objectif est de développer une solution capable d'analyser une image d'une scène de chantier, d'identifier les personnes présentes et d'exploiter les informations relatives au port des équipements de protection afin de déterminer les situations conformes et non conformes.

Le projet s'inscrit dans une démarche de Computer Vision appliquée à la sécurité industrielle, avec une attention particulière portée à la possibilité de déployer le modèle sur un environnement mobile.

Travaux réalisés :

Constitution et préparation d'un dataset de scènes de chantier. Annotation et structuration des données d'entraînement. Nettoyage et préparation des données. Expérimentation de modèles de Deep Learning pour la détection d'objets. Utilisation de YOLO pour la détection des personnes et des équipements de protection. Mise en place d'une logique de décision permettant d'interpréter les détections et d'identifier les situations de non-conformité. Évaluation des performances du modèle. Optimisation du pipeline d'inférence. Conversion du modèle vers TensorFlow Lite. Expérimentation du déploiement du modèle dans une application mobile.

Practical tasks on Deep Learning (DL) and Neural Networks (NN). 🤖

The AI and the Automobile collection brings together multiple specifications that define how AI integrates into modern vehicle systems, treating the automobile as a software-defined platform where intelligence spans perception, control, navigation, and energy management. It emphasizes real-time performance, safety-critical architecture, and the transition from purely mechanical systems to continuously evolving software-driven mobility. Across the collection, the specs also describe how automotive AI should be built through open and interoperable systems with strong safety practices, including simulation, validation pipelines, and human-in-the-loop oversight to handle edge cases. Together, they frame vehicle intelligence as a layered system combining autonomy, redundancy, diagnostics, and secure update mechanisms to enable reliable and scalable deployment. https://roxanneardary.com/ai-and-the-automobile/

API4AI is cloud-native computer vision & AI platform for startups, enterprises and individual developers. This repository contains sample mini apps that utilizes NSFW Content Recognition API provided by API4AI.

This project leverages the Brain Tumor Image database to develop a semantic segmentation model for detecting brain tumors. The model is based on an encoder-decoder U-Net architecture, which classifies each pixel in a medical image as either tumor or healthy tissue. The resulting segmentation is visualized as a binary mask, clearly delineating the tumor region from the surrounding healthy areas.

The model successfully localizes the tumor’s global position with high accuracy but the precise shape and boundaries remain approximate (moderate Dice coefficient). Extending the training phase with additional epochs could refine the segmentation quality, leading to a higher Dice coefficient and more accurate tumor delineation.

lbplib2d-rs a high-performance feature extraction tool that provides optimized implementations of 2D Local Binary Pattern (LBP) and its core variants. Built in Rust for speed and memory efficiency, it includes Python bindings to offer seamless integration for researchers and developers working on image analysis and computer vision tasks

Robochan: middleware for interfacing between generic algorithms (controllers) and robotic platforms and environments (parrot, gym, robosim etc.)

A custom convolutional neural network (CNN) was developed from scratch and trained to recognize flower types using pcituires from the Flowers Recognition Dataset. The model’s architecture and hyperparameters were optimized to maximize recognition accuracy.

The custom CNN is compared against MobileNetV2, a pre-trained model fine-tuned using transfer learning. The comparison highlights the trade-offs between custom-built models and transfer learning approaches in terms of accuracy, training efficiency, and computational cost.

API4AI is cloud-native computer vision & AI platform for startups, enterprises and individual developers. This repository contains sample mini apps that utilizes Wine Recognition API provided by API4AI.

API4AI is cloud-native computer vision & AI platform for startups, enterprises and individual developers. This repository contains sample mini apps that utilizes Virtual Try-On API provided by API4AI.

API4AI is cloud-native computer vision & AI platform for startups, enterprises and individual developers. This repository contains sample mini apps that utilizes OCR API provided by API4AI.