YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

Ultralytics YOLO 🚀

:robot: The free, Open Source alternative to OpenAI, Claude and others. Self-hosted and local-first. Drop-in replacement, running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more. Features: Generate Text, MCP, Audio, Video, Images, Voice Cloning, Distributed, P2P and decentralized inference

We write your reusable computer vision tools. 💜

OpenMMLab Detection Toolbox and Benchmark

NVR with realtime local object detection for IP cameras

deep learning for image processing including classification and object-detection etc.

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

CVPR 2026 论文和开源项目合集

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

cvpr2024/cvpr2023/cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理

A paper list of object detection using deep learning.

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

Refine high-quality datasets and visual AI models

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

Fast and Accurate ML in 3 Lines of Code

Techniques for deep learning with satellite & aerial imagery

Best Practices, code samples, and documentation for Computer Vision.

[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

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.

A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

Effortless data labeling with AI support from Segment Anything and other awesome models.

Experience, Learn and Code the latest breakthrough innovations with Microsoft AI

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

Deep Learning and Reinforcement Learning Library for Scientists and Engineers