LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 โ object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
We write your reusable computer vision tools. ๐
NVR with realtime local object detection for IP cameras
CVAT is a leading data annotation platform for image, video, audio, and 3D datasets. It offers open-source, cloud, and enterprise products, as well as labeling services, with AI-assisted labeling, quality assurance, team collaboration, analytics, and developer APIs.
Refine high-quality datasets and visual AI models
Fast and Accurate ML in 3 Lines of Code
X-AnyLabeling: A lightweight, efficient, and unified cross-platform desktop application for annotating text, image, video, point cloud and multimodal data, combining versatile built-in tools with state-of-the-art AI models and flexible multi-format export.
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.
Techniques for deep learning with satellite & aerial imagery
RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning. [ICLR 2026]
A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM 3, and Qwen3-VL.
All-in-One Development Tool based on PaddlePaddle
Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
Most popular metrics used to evaluate object detection algorithms.
[CAAI AIR'24] Bilateral Reference for High-Resolution Dichotomous Image Segmentation
Self-hosted, local only NVR and AI Computer Vision software. With features such as object detection, motion detection, face recognition and more, it gives you the power to keep an eye on your home, office or any other place you want to monitor.
D-FINE: Redefine Regression Task of DETRs as Fine-grained Distribution Refinement [ICLR 2025 Spotlight]
Images to inference with no labeling (use foundation models to train supervised models).
Deep Learning Server and CLI for Torch and TensorRT
Turn any computer or edge device into a command center for your computer vision projects.
The collection of pre-trained, state-of-the-art AI models for ailia SDK
Add object detection, tracking, mobile notifications, and search to any security camera.
Core ML model zoo for iOS/macOS โ PyTorch models converted to ready-to-use .mlpackage, each with a conversion script and SwiftUI sample app. Sibling repos cover Apple's Core AI framework (iOS/macOS 27) and on-device LLMs.
Python sample codes and documents about Autonomous vehicle control algorithm. This project can be used as a technical guide book to study the algorithms and the software architectures for beginners.
Set of methods to ensemble boxes from different object detection models, including implementation of "Weighted boxes fusion (WBF)" method.
High-performance, privacy-first on-device AI inference library for React Native, powered by PyTorch's ExecuTorch runtime
All-in-one training for vision models (YOLO, ViTs, RT-DETR, DINOv3): pretraining, fine-tuning, distillation.
A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. ๐26 knowledge distillation methods presented at TPAMI, CVPR, ICLR, ECCV, NeurIPS, ICCV, AAAI, etc are implemented so far. ๐ Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.
Xtreme1 is an all-in-one data labeling and annotation platform for multimodal data training and supports 3D LiDAR point cloud, image, and LLM.
Build, train, optimize, and run computer vision models locally, from raw images to live inference. Open source, optimized for Intel XPU (CPU-only and CUDA also supported).
Frigate integration for Home Assistant
โก๏ธThe spatial perception framework for rapidly building smart robots and spaces
Legacy JSON-to-YOLO dataset converter for COCO, LabelMe, Labelbox, VoTT, INFOLKS, and ATH annotations. Superseded by convert_coco() in the Ultralytics package.
Neural Network Compression Framework for enhanced OpenVINOโข inference
Ultralytics YOLOv8, YOLOv9, YOLOv10, YOLOv11, YOLOv12 for ROS 2
The modern, local-first platform for professional video surveillance.
Microsoft AI for Good Lab โ Biodiversity research hub. Open-source AI models, edge devices, and tools for biodiversity monitoring and conservation. Your source for MegaDetector, SPARROW, PytorchWildlife, Bioacoustics, and more.
Python framework that facilitates the quick development of complex video analysis applications and other series-processing based applications in a multiprocessing environment.
MetaSeg: Packaged version of the Segment Anything repository
LibreYOLO is a MIT licensed open source computer vision library
Python Computer Vision & Video Analytics Framework With Batteries Included
YoloDotNet - A C# .NET 8.0 project for Classification, Object Detection, OBB Detection, Segmentation and Pose Estimation in both images and live video streams.
๐ฎ Trash Annotations in Context Dataset Toolkit
A collection of deep learning based RGB-T-Fusion methods, codes, and datasets. The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Crowd Counting, RGB-T Fusion Tracking.
Hierarchical perception library in Python for pose estimation, object detection, instance segmentation, keypoint estimation, face recognition, etc.
nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.
Exclusively Dark (ExDARK) dataset which to the best of our knowledge, is the largest collection of low-light images taken in very low-light environments to twilight (i.e 10 different conditions) to-date with image class and object level annotations.
Image augmentation for computer vision. AGPL-3.0-only or commercial licensing.
๐ A high performance real-time object detection solution using YOLO11 โก๏ธ powered by ONNX-Runtime
Ultralytics YOLO iOS app and Swift package for real-time Core ML inference across major computer vision tasks.
Official Ultralytics YOLO Flutter plugin for real-time inference on Android and iOS across major vision tasks.
Eyes are All JEV Needs - real time visual devisions from RGB, video and RGB-D cameras.
Real-time parking lot occupancy detection using existing security cameras and on-device computer vision.
A 4B grounding foundation model for physical intelligence. Unifies detection, referring, pointing, OCR, GUI, and layout grounding, achieving SOTA overall across 34 benchmarks and improving robot generalization and data efficiency in controlled evaluations.
Turn your cameras into Home Assistant sensors with a local AI: garage door open/closed, people and cars, water, gas and power meters read by any camera or ESP32-CAM. 100% local, any CPU.
GTR: Gated Token Recurrence for Efficient Dense Prediction
INT8 single-class YOLOv3-Tiny accelerator and OV5640-to-HDMI bare-metal demo for Xilinx Zynq-7000 XC7Z100, with PyTorch training and parameter-export tools. Topics yolov3-tiny, fpga, zynq-7000, xc7z100, verilog, vivado, vitis, pytorch, int8-quantization, object-detection, axi4-stream, ov5640, hdmi, embedded-systems, computer-vision
A 4B diffusion grounding model for fast, precise visual evidence extraction. Unifies diverse grounding tasks through parallel decoding, with optional self-speculative decoding delivering 4.51x autoregressive throughput on COCO.