/awesome-yolo-object-detection

🚀🚀🚀 A collection of some awesome public YOLO object detection series projects and the related object detection datasets.

Awesome-YOLO-Object-Detection

Awesome

🚀🚀🚀 YOLO is a great real-time one-stage object detection framework. This repository lists some awesome public YOLO object detection series projects and the related object detection datasets.

Contents

Summary

Extensional Frameworks

Other Versions of YOLO

Lighter and Deployment Frameworks

Applications

Datasets

  • Datasets Share Platform

    • OpenDataLab : OpenDataLab 是上海人工智能实验室的大模型数据基座团队打造的数据开放平台，现已成为**大模型语料数据联盟开源数据服务指定平台，为开发者提供全链条的 AI 数据支持，应对和解决数据处理中的风险与挑战，推动 AI 研究及应用。

    • Science Data Bank(ScienceDB) : Make your research data citable, discoverable and persistently accessible Satisfy flexible data sharing requirements Dedicate to facilitating data dissemination and reusing. Science Data Bank (ScienceDB) is a public, general-purpose data repository aiming to provide data services (e.g. data acquisition, long-term preservation, publishing, sharing and access) for researchers, research projects/teams, journals, institutions, universities, etc. It supports a variety of data acquisition and data licenses. ScienceDB is dedicated to promoting data findable, citable and reusable on the prerequisite of protecting the rights and interests of data owners and it is built and operated by Computer Network Information Center, Chinese Academy of Sciences.

    • **科学数据 : 《**科学数据（中英文网络版）》（China Scientific Data）（CN11-6035/N，ISSN 2096-2223）是目前**唯一的专门面向多学科领域科学数据出版的学术期刊，作为国家网络连续型出版物的首批试点之一，由**科学院主管，**科学院计算机网络信息中心和ISC CODATA**全国委员会合办，国家科技基础条件平台中心、**科学院网络安全和信息化领导小组办公室指导，国内外公开发行，中英文，季刊。 **科学引文数据库（CSCD）来源期刊，**科技核心期刊 ，收录于**科协高质量科技期刊分级目录。

    • 飞桨AI Studio : 飞桨AI Studio开放数据集。

    • 极市开发者平台 : 极市开发者平台开放数据集。

    • openvinotoolkit/datumaro : Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.

  • Datasets Tools

    • Data Annotation

      • Label Studio : Label Studio is a multi-type data labeling and annotation tool with standardized output format. labelstud.io

      • AnyLabeling : Effortless data labeling with AI support from YOLO and Segment Anything! AnyLabeling = LabelImg + Labelme + Improved UI + Auto-labeling.

      • LabelImg : 🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in images.

      • labelme : Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

      • DarkLabel : Video/Image Labeling and Annotation Tool.

      • AlexeyAB/Yolo_mark : GUI for marking bounded boxes of objects in images for training neural network Yolo v3 and v2.

      • Cartucho/OpenLabeling : Label images and video for Computer Vision applications.

      • CVAT : Computer Vision Annotation Tool (CVAT). 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.

      • VoTT : Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.

      • WangRongsheng/KDAT : 一个专为视觉方向目标检测全流程的标注工具集，全称：Kill Object Detection Annotation Tools。

      • Rectlabel-support : RectLabel - An image annotation tool to label images for bounding box object detection and segmentation.

      • cnyvfang/labelGo-Yolov5AutoLabelImg : 💕YOLOV5 semi-automatic annotation tool (Based on labelImg)💕一个基于labelImg及YOLOV5的图形化半自动标注工具。

      • CVUsers/Auto_maker : 深度学习数据自动标注器开源 目标检测和图像分类（高精度高效率）。

      • MyVision : Computer vision based ML training data generation tool 🚀

      • wufan-tb/AutoLabelImg : auto-labelimg based on yolov5, with many other useful tools. AutoLabelImg 多功能自动标注工具。

      • MrZander/YoloMarkNet : Darknet YOLOv2/3 annotation tool written in C#/WPF.

      • mahxn0/Yolov3_ForTextLabel : 基于yolov3的目标/自然场景文字自动标注工具。

      • MNConnor/YoloV5-AI-Label : YoloV5 AI Assisted Labeling.

      • LILINOpenGitHub/Labeling-Tool : Free YOLO AI labeling tool. YOLO AI labeling tool is a Windows app for labeling YOLO dataset.

      • whs0523003/YOLOv5_6.1_autolabel : YOLOv5_6.1 自动标记目标框。

      • 2vin/PyYAT : Semi-Automatic Yolo Annotation Tool In Python.

      • AlturosDestinations/Alturos.ImageAnnotation : A collaborative tool for labeling image data for yolo.

      • stephanecharette/DarkMark : Marking up images for use with Darknet.

      • 2vin/yolo_annotation_tool : Annotation tool for YOLO in opencv.

      • sanfooh/quick_yolo2_label_tool : yolo快速标注工具 quick yolo2 label tool.

      • folkien/yaya : YAYA - Yet annother YOLO annoter for images (in QT5). Support yolo format, image modifications, labeling and detecting with previously trained detector.

      • pylabel-project/pylabel : Python library for computer vision labeling tasks. The core functionality is to translate bounding box annotations between different formats-for example, from coco to yolo.

      • opendatalab/labelU : Uniform, Unlimited, Universal and Unbelievable Annotation Toolbox.

    • Data Augmentation

      • Albumentations : Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to increase the quality of trained models. The purpose of image augmentation is to create new training samples from the existing data. "Albumentations: Fast and Flexible Image Augmentations". (Information 2020)

      • doubleZ0108/Data-Augmentation : General Data Augmentation Algorithms for Object Detection(esp. Yolo).

    • Data Management

      • YOLOExplorer : YOLOExplorer : Iterate on your YOLO / CV datasets using SQL, Vector semantic search, and more within seconds. Explore, manipulate and iterate on Computer Vision datasets with precision using simple APIs. Supports SQL filters, vector similarity search, native interface with Pandas and more.

  • General Detection and Recognition Datasets

    • Object Detection Datasets

    • Object Recognition Datasets

  • Autonomous Driving Datasets

    • Diverse Autonomous Driving Datasets

      • BDD100K : "BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning". (CVPR 2020)

      • CODA : "CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving". (ECCV 2022)

    • Traffic Sign Detection Datasets

      • TT100K : "Traffic-Sign Detection and Classification in the Wild". (CVPR 2016)

      • CCTSDB : CSUST Chinese Traffic Sign Detection Benchmark **交通数据集由长沙理工大学综合交通运输大数据智能处理湖南省重点实验室张建明老师团队制作完成。 "A Real-Time Chinese Traffic Sign Detection Algorithm Based on Modified YOLOv2". (Algorithms, 2017)

      • CCTSDB2021 : "CCTSDB 2021: a more comprehensive traffic sign detection benchmark". (Human-centric Computing and Information Sciences, 2022)

    • License Plate Detection and Recognition Datasets

      • CCPD : "Towards End-to-End License Plate Detection and Recognition: A Large Dataset and Baseline". (ECCV 2018)

  • Adverse Weather Datasets

  • Person Detection Datasets

    Anti-UAV Datasets

    • Anti-UAV : 🔥🔥Official Repository for Anti-UAV🔥🔥. "Evidential Detection and Tracking Collaboration: New Problem, Benchmark and Algorithm for Robust Anti-UAV System". (arXiv 2023)

  • Optical Aerial Imagery Datasets

    • COWC : "A large contextual dataset for classification, detection and counting of cars with deep learning". (ECCV 2016)

    • RSOD : "Accurate object localization in remote sensing images based on convolutional neural networks". (IEEE TGRS 2017)

    • LEVIR : "Random access memories: A new paradigm for target detection in high resolution aerial remote sensing images". (IEEE Transactions on Image Processing 2017)

    • LEVIR-Ship : "A Degraded Reconstruction Enhancement-based Method for Tiny Ship Detection in Remote Sensing Images with A New Large-scale Dataset". (IEEE TGRS 2022)

    • MASATI : "Automatic ship classification from optical aerial images with convolutional neural networks". (Remote Sensing 2018)

    • xView : "xView: Objects in Context in Overhead Imagery". (arXiv 2018)

    • DOTA : "DOTA: A Large-Scale Dataset for Object Detection in Aerial Images". (CVPR 2018). "Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges". (IEEE TPAMI 2021).

    • ITCVD : "Deep Learning for Vehicle Detection in Aerial Images". (IEEE ICIP 2018)

    • Bridge Dataset : "A Tool for Bridge Detection in Major Infrastructure Works Using Satellite Images". (IEEE ICIP 2018)

    • DIOR : "Object detection in optical remote sensing images: A survey and a new benchmark". (ISPRS 2020)

    • PESMOD : "UAV Images Dataset for Moving Object Detection from Moving Cameras". (arXiv 2021)

    • AI-TOD : "Tiny Object Detection in Aerial Images". (IEEE ICPR 2021)

    • RsCarData : "DSFNet: Dynamic and Static Fusion Network for Moving Object Detection in Satellite Videos". (IEEE GRSL 2021)

    • VISO : "Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark". (IEEE TGRS 2021)

    • VisDrone : "Detection and Tracking Meet Drones Challenge". (IEEE TPAMI 2021)

    • FAIR1M : "FAIR1M: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery". (ISPRS 2021)

    • SeaDronesSee : "SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water". (WACV 2022)

  • Low-light Image Datasets

  • Infrared Image Datasets

  • SAR Image Datasets

  • Multispectral Image Datasets

    • FLIR_ADAS : Teledyne FLIR Free ADAS Thermal Dataset v2.

    • VEDAI : "Vehicle Detection in Aerial Imagery: A small target detection benchmark". (Journal of Visual Communication and Image Representation 2015)

    • KAIST_rgbt : "Multispectral Pedestrian Detection: Benchmark Dataset and Baseline". (CVPR 2015)

    • TNO : "The TNO multiband image data collection". (Data in brief, 2017)

    • MFNet : MFNet-pytorch, image semantic segmentation using RGB-Thermal images. "MFNet: Towards real-time semantic segmentation for autonomous vehicles with multi-spectral scenes". (IROS 2017). (MFNet Dataset : Multi-spectral Object Detection and Semantic Segmentation Datasets)

    • LLVIP : "LLVIP: A Visible-Infrared Paired Dataset for Low-Light Vision". (ICCV 2021)

    • MSRS : MSRS: Multi-Spectral Road Scenarios for Practical Infrared and Visible Image Fusion. "PIAFusion : A progressive infrared and visible image fusion network based on illumination aware". (Information Fusion, 2022)

    • TarDAL : "Target-Aware Dual Adversarial Learning and a Multi-Scenario Multi-Modality Benchmark To Fuse Infrared and Visible for Object Detection". (CVPR 2022). (M3FD Dataset)

    • DroneVehicle : "Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning". (IEEE TCSVT 2022)

  • 3D Object Detection Datasets

    • Objectron : "Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose Annotations". (CVPR, 2021)

  • Vehicle-to-Everything Field Datasets

  • Super-Resolution Field Datasets

    • VideoLQ : "Investigating Tradeoffs in Real-World Video Super-Resolution". (CVPR, 2022)

  • Face Detection and Recognition Datasets

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