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THE FIRST COLLECTIONA 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.
LocalAI is an open-source, self-hosted AI engine that runs LLMs, vision, voice, image and video models on any hardware, including CPU-only. It offers OpenAI, Anthropic and ElevenLabs-compatible APIs, on-demand modular backends, multi-user auth, and built-in agents with RAG and MCP.
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.
Frigate is a local NVR for IP cameras with realtime AI object detection, built for Home Assistant. It uses OpenCV and TensorFlow, motion-triggered detection, MQTT, object-based retention, 24/7 recording, RTSP restreaming and low-latency WebRTC/MSE live view.
Ultralytics provides a suite of state-of-the-art YOLO models for computer vision tasks including object detection, segmentation, and classification.
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.
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.
YOLOv5 is a fast, accurate computer vision framework in PyTorch for object detection, instance segmentation, and image classification. It supports training on custom datasets, inference from various sources, and exporting models to formats like ONNX, TensorRT, and CoreML.
FiftyOne is an open-source tool for building high-quality datasets and computer vision models. It enables users to visualize, label, evaluate, and curate visual AI data.