Open source. Open possibilities.

A comprehensive toolkit for computer vision that provides model-agnostic building blocks for data loading, visualization, and dataset management.

Free, open-source AI engineering curriculum from first principles: 523 lessons in 20 phases (~342 hours), with math-to-production coverage in Python, TypeScript, Rust, and Julia. Every lesson ships a reusable prompt, skill, agent, or MCP server; includes an installable AI tutor and Claude certification prep.

A growing collection of 61 computer vision tutorials covering state-of-the-art models like YOLO11, SAM 3, RF-DETR, and Qwen3-VL for object detection, segmentation, OCR, and more.

AirSim is Microsoft's open-source simulator for drones and cars, built as an Unreal Engine plugin with an experimental Unity release. It supports software- and hardware-in-the-loop simulation with PX4 and ArduPilot, and exposes cross-language APIs for collecting images and controlling vehicles for AI research.

A modern C++ toolkit providing machine learning algorithms and tools for data analysis and real-world application development.

Gesture Ninja is a computer vision-based application that enables users to play Fruit Ninja using real-time finger tracking via a webcam.

Label Studio is an open-source, multi-type data labeling tool supporting audio, text, images, video, and time series with a simple UI and export to various model formats.

Meshify is a real-time face mesh detection application that identifies and tracks facial landmarks using OpenCV, MediaPipe, and CVZone.

X-AnyLabeling is a cross-platform desktop application for AI-assisted annotation of image, video, text, and multimodal data, with many built-in deep learning models, diverse labeling tools, and multi-format import/export.

A local facial recognition attendance system with a React Native Expo mobile app and FastAPI Python backend. It captures faces via Expo Camera, processes them with OpenCV LBPH, and logs timestamped attendance into SQLite.

Deep Lake is a serverless multimodal database for AI that combines vector search with storage for embeddings, images, video, audio, and documents. It streams data directly from cloud storage to PyTorch/TensorFlow, supports versioning, and integrates with LangChain, LlamaIndex, and Weights & Biases.

Ultralytics provides a suite of state-of-the-art YOLO models for computer vision tasks including object detection, segmentation, and classification.

OpenCV is an open-source computer vision library providing a wide range of tools for image processing and visual analysis.

A free 12-week, 24-lesson curriculum from Microsoft for learning AI fundamentals: neural networks, deep learning, computer vision, NLP, transformers, ethics, plus hands-on notebooks, quizzes, and labs.

JavaCV provides Java wrappers for OpenCV, FFmpeg, and other computer vision libraries via JavaCPP Presets. It enables image processing, video capture/recording, face detection, and camera calibration on Java and Android with hardware-accelerated display.

RF-DETR is a real-time transformer model architecture from Roboflow for object detection, instance segmentation, and keypoint detection, built on a DINOv2 backbone and designed for fine-tuning.

A personal Elixir/OTP game-automation bot for a 2D MMORPG, using screen capture and synthetic input on macOS. It features a supervised process fleet, pure decision logic, and fail-safe actuation controls.

A curated list of computer science courses with video lectures, covering algorithms, AI, databases, operating systems, and more.

FaceAttend is a locally hosted classroom attendance system that uses video-based face recognition to identify enrolled students.

jetson-inference is a C++ and Python deep-vision library for NVIDIA Jetson. It uses TensorRT for on-device inference and PyTorch for training, with examples, pre-trained models, and tutorials for classification, detection, segmentation, pose, action, depth, and camera streaming.