awesome-repositories.com
博客
MCP
awesome-repositories.com

通过 AI 驱动的搜索,发现最优秀的开源仓库。

探索精选搜索开源替代品自托管软件博客网站地图
项目MCP 服务器关于排名机制媒体报道
法律隐私政策服务条款
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

Data labeling tool

排名更新于 2026年7月27日

For data labeling interfaces, the strongest matches are inception-project/inception (INCEpTION is a semantic annotation platform tailored for text), jiesutd/yedda (YEDDA is a lightweight collaborative text annotation tool designed) and rtiinternational/smart (This repository provides a self-hostable tool for text and). heartexlabs/label-studio and chakki-works/doccano round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.

Hand-picked data labeling tools to annotate images, text, and audio. Compare top open-source GitHub repositories to find the best fit.

Data labeling tool

用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
  • inception-project/inceptioninception-project 的头像

    inception-project/inception

    700在 GitHub 上查看↗

    A semantic annotation platform offering intelligent assistance and knowledge management. Homepage · Usage · Demo · FAQ

    INCEpTION is a semantic annotation platform tailored for text and NLP tasks, offering collaborative workflows and intelligent assistance, making it a strong fit for text labeling despite lacking image or video capabilities.

    JavaText AnnotationText Annotation Tools
    在 GitHub 上查看↗700
  • jiesutd/yeddajiesutd 的头像

    jiesutd/YEDDA

    1,071在 GitHub 上查看↗

    YEDDA: A Lightweight Collaborative Text Span Annotation Tool. Code for ACL 2018 Best Demo Paper Nomination.

    YEDDA is a lightweight collaborative text annotation tool designed for manual and entity span labeling, fitting the text-annotation aspect of your search though it lacks image, audio, or video capabilities.

    PythonText AnnotationText Annotation Tools
    在 GitHub 上查看↗1,071
  • rtiinternational/smartRTIInternational 的头像

    RTIInternational/SMART

    230在 GitHub 上查看↗

    Smarter Manual Annotation for Resource-constrained collection of Training data

    This repository provides a self-hostable tool for text and image annotation to assist in training machine learning models, fitting the core category despite lacking audio, video, and advanced active learning features.

    PythonText AnnotationText Annotation Tools
    在 GitHub 上查看↗230
  • heartexlabs/label-studioheartexlabs 的头像

    heartexlabs/label-studio

    27,626在 GitHub 上查看↗

    Label Studio is a multi-type data labeling tool and data annotation workspace designed to prepare datasets for machine learning training. It functions as a cloud-integrated data pipeline that imports raw data from storage, manages the annotation process, and exports labels into standardized formats. The platform features a machine learning model integration framework that connects to external model servers. This enables model-assisted annotation and active learning, allowing the system to perform pre-labeling and refine predictions based on human feedback. The software provides project manag

    Label Studio is a self-hostable, collaborative data labeling platform supporting multimodal annotations like images, text, audio, and video alongside active learning and customizable interfaces.

    TypeScriptActive Learning
    在 GitHub 上查看↗27,626
  • chakki-works/doccanochakki-works 的头像

    chakki-works/doccano

    10,687在 GitHub 上查看↗

    Doccano is a collaborative labeling platform and text annotation tool designed to create training data for machine learning. It provides a specialized interface for performing sequence labeling and text classification on natural language datasets. The system functions as a supervised learning dataset manager, allowing multiple users to coordinate within a shared workspace to label datasets for natural language processing tasks. It supports the preparation of raw text data for model training by converting unstructured documents into structured labeled examples. The platform includes capabilit

    Doccano is a collaborative labeling platform built for natural language processing, matching the intent for data annotation tools despite focusing solely on text rather than images or video.

    PythonText AnnotationText Annotation Tools
    在 GitHub 上查看↗10,687
  • cvat-ai/cvatcvat-ai 的头像

    cvat-ai/cvat

    15,317在 GitHub 上查看↗

    CVAT is an open-source, web-based platform designed for annotating images, videos, and 3D point clouds to create high-quality training datasets for machine learning. It functions as a containerized server that orchestrates the entire lifecycle of computer vision data, from initial task creation and manual labeling to quality assurance and final dataset export. The platform distinguishes itself through deep integration with machine learning models, allowing users to deploy custom AI models as serverless functions for automated object detection, tracking, and skeleton annotation. It supports co

    CVAT is a comprehensive, self-hostable data annotation platform supporting image, video, and 3D data with collaborative workflows and automated AI-assisted labeling.

    PythonInterface LabelingObject Mask Generators
    在 GitHub 上查看↗15,317
  • doccano/doccanodoccano 的头像

    doccano/doccano

    10,674在 GitHub 上查看↗

    Doccano is a collaborative data labeling platform and machine learning dataset management system. It provides a web-based interface for teams to import raw text, mark datasets, and export structured annotations for model training. The project specifically supports text annotation for classification and named entity recognition tasks. It enables teams to coordinate multiple users on a single project to maintain consistent labeling guidelines and increase the speed of dataset creation. The system includes tools for data management and team coordination, providing the ability to import raw data

    Doccano is a collaborative web-based data labeling platform tailored specifically for text annotation tasks, making it a great fit for team-based text projects despite lacking native image and audio annotation features.

    PythonText AnnotationText Annotation Tools
    在 GitHub 上查看↗10,674
  • humansignal/label-studioHumanSignal 的头像

    HumanSignal/label-studio

    27,619在 GitHub 上查看↗

    Label Studio is a multi-modal data annotation platform designed to create and manage high-quality training datasets for machine learning. It functions as a self-hosted, containerized environment that supports secure, private deployments, including air-gapped configurations. The platform provides a centralized workspace for labeling diverse media types, such as images, text, audio, and time-series data, to support supervised and reinforcement learning workflows. The platform distinguishes itself through deep integration with machine learning backends, enabling active learning loops, automated

    Label Studio is a self-hostable multi-modal data annotation platform that provides collaborative workspaces and active learning workflows for images, text, audio, and video training data.

    TypeScriptObject Mask Generators
    在 GitHub 上查看↗27,619
  • label-sleuth/label-sleuthlabel-sleuth 的头像

    label-sleuth/label-sleuth

    273在 GitHub 上查看↗

      Quick Start   |   Documentation   |   Join Slack  

    Label Sleuth is a self-hostable text annotation platform featuring active learning workflows tailored for building machine learning models, though it is limited to text data and lacks support for images, audio, or video.

    PythonText Annotation Tools
    在 GitHub 上查看↗273
  • argilla-io/argillaargilla-io 的头像

    argilla-io/argilla

    5,015在 GitHub 上查看↗

    Argilla is a collaborative AI feedback tool and data curation management system. It serves as a human-in-the-loop dataset platform designed to coordinate workforce annotators and domain experts in labeling, rating, and refining data samples for machine learning projects. The platform focuses on large language model dataset curation and reinforcement learning from human feedback workflows. It provides a shared workspace for integrating human expertise into AI development to validate model outputs and correct data errors. The system manages the end-to-end machine learning data pipeline, includ

    Argilla is a collaborative AI feedback tool and data curation platform designed for human-in-the-loop data labeling and reinforcement learning workflows, directly fulfilling the requirements for an annotating and labeling tool.

    PythonData Labeling InterfacesData Labeling PlatformsAnnotation Sampling
    在 GitHub 上查看↗5,015
  • opencv/cvatopencv 的头像

    opencv/cvat

    16,086在 GitHub 上查看↗

    CVAT is an open-source computer vision annotation tool and visual dataset management platform. It provides a self-hosted interface for labeling images, videos, and 3D data to create datasets for vision AI models. The platform features AI-assisted data labeling to automate the creation of masks and bounding boxes, utilizing a plug-in system to connect external machine learning models. It includes a consensus-based quality assurance system that verifies label accuracy by comparing independent annotations. The system covers collaborative team management, project organization through task decomp

    CVAT is an open-source, self-hosted data labeling platform that provides collaborative workflows, AI-assisted image and video annotation, and quality assurance tools for computer vision training.

    PythonComputer Vision ToolsVisual Annotation ToolsAI-Assisted Labeling
    在 GitHub 上查看↗16,086
  • wkentaro/labelmewkentaro 的头像

    wkentaro/labelme

    15,984在 GitHub 上查看↗

    Labelme is a Python-based image annotation tool used to create computer vision datasets. It serves as a visual editor for semantic segmentation, allowing users to define object boundaries using polygons, rectangles, points, and circles. The application also functions as a multispectral image annotator, supporting high-bit depth TIFF files used in satellite and scientific imagery. The tool incorporates AI-assisted labeling capabilities to automate the creation of masks and polygons. These features allow for shape generation driven by text prompts or interactive point selections, which propose

    Labelme is a Python-based image annotation tool specialized in image segmentation and computer vision datasets, though it lacks text, audio, and video annotation features.

    PythonSemantic Segmentation
    在 GitHub 上查看↗15,984
  • microsoft/vottmicrosoft 的头像

    microsoft/VoTT

    4,427在 GitHub 上查看↗

    VoTT is a computer vision annotation software and machine learning dataset preparation tool. It is a desktop application designed for drawing bounding boxes and assigning tags to objects in images and videos to create training datasets for object detection models. The application utilizes a cross-platform desktop interface to manage image and video assets. It features a local-first storage integration to handle large media assets directly from the host machine's file system and includes frame-rate controlled video sampling to extract specific images from video streams for labeling. The softw

    VoTT is a desktop application for annotating images and videos with bounding boxes to prepare computer vision training datasets, which fits the category well despite missing text and audio modalities.

    TypeScriptBounding Box Interfaces2D Object LabelingAnnotation Format Exporters
    在 GitHub 上查看↗4,427
  • cloud-annotations/cloud-annotationscloud-annotations 的头像

    cloud-annotations/cloud-annotations

    2,681在 GitHub 上查看↗

    Cloud Annotations is a web-based platform designed for collaborative image annotation and the preparation of computer vision datasets. It provides an interface for teams to draw bounding boxes and polygons over digital media, transforming raw images into structured training data for machine learning models. The platform distinguishes itself through a real-time synchronization engine that allows multiple users to edit the same image simultaneously. By utilizing browser-based local storage and standardized data serialization, it supports offline workflows and ensures that exported annotations r

    Cloud Annotations is a web-based collaborative image and vision dataset annotation tool that supports team workflows, though it lacks text, audio, and video labeling features.

    TypeScriptComputer Vision ToolsCollaborative AnnotationMachine Learning Data Preparation
    在 GitHub 上查看↗2,681
  • humansignal/labelimgHumanSignal 的头像

    HumanSignal/labelImg

    25,015在 GitHub 上查看↗

    labelImg is a computer vision labeling tool and image bounding box annotator used to create training datasets for machine learning models. It functions as a desktop utility for drawing rectangular labels on images and saving object coordinates and class names in common machine learning formats. The tool is specifically designed to generate and edit PascalVOC formatted XML files and create image labels in the text-based format required by YOLO object detection pipelines. The software covers object detection annotation and training data preparation, including the ability to manage label catego

    LabelImg is a dedicated desktop utility for image bounding box annotation and dataset preparation, though its narrow focus on rectangular bounding boxes means it lacks advanced features like segmentation, video support, or collaborative workflows.

    PythonDataset Labeling InterfacesAnnotationAnnotation Format Exporters
    在 GitHub 上查看↗25,015
  • tzutalin/labelimgtzutalin 的头像

    tzutalin/labelImg

    25,012在 GitHub 上查看↗

    labelImg is a desktop image annotation tool and dataset preparation utility used to create labeled datasets for computer vision training. It provides a graphical interface for drawing bounding boxes around objects in images and assigning them class labels to build ground truth data for machine learning models. The software specifically supports the Pascal VOC XML annotation format, exporting image coordinates and class names into standard XML or text structures. It allows users to load predefined class lists from text files to standardize naming across an entire project. Beyond initial label

    This repository is a desktop image annotation tool used to create bounding-box datasets for computer vision training, making it a valid option within the category even though it is limited to images and lacks collaborative or video features.

    PythonComputer Vision Tools2D Object LabelingAnnotation Format Converters
    在 GitHub 上查看↗25,012
  • voxel51/fiftyonevoxel51 的头像

    voxel51/fiftyone

    10,841在 GitHub 上查看↗

    FiftyOne is a visual tool for curating, analyzing, and managing image and video datasets for machine learning model training. It serves as a platform for identifying annotation errors, refining ground truth labels, and evaluating vision model performance by comparing predictions against ground truth to identify failure modes. The system functions as a containerized data platform that supports team collaboration on large-scale visual datasets in a cloud environment. It includes specialized capabilities for exploring high-dimensional embeddings to discover data clusters and retrieve correspondi

    FiftyOne is a visual dataset curation and evaluation platform tailored for machine learning, featuring image and video analysis capabilities that support annotation project management and collaboration, though it focuses more on dataset exploration and error identification than a dedicated end-to-end labeling tool.

    PythonDataset CuratorsAnnotation Project ManagementCollaborative Dataset Management
    在 GitHub 上查看↗10,841
  • csailvision/labelmeannotationtoolCSAILVision 的头像

    CSAILVision/LabelMeAnnotationTool

    1,467在 GitHub 上查看↗

    Source code for the LabelMe annotation tool.

    This repository provides the source code for the classic LabelMe annotation tool, which fits the data labeling category for images even though it lacks advanced features like active learning or collaborative workflows.

    JavaScriptAnnotation and Data Tools
    在 GitHub 上查看↗1,467
  • javserjod/label-appjavserjod 的头像

    javserjod/label-app

    2在 GitHub 上查看↗

    Label App is a free, simple application designed to assist in manually editing, visualizing and labelling your moderate-sized datasets.

    Label App is a self-contained data labeling tool for manual dataset annotation, fitting the category well despite having a narrower feature set focused on moderate-sized datasets.

    PythonSpecialized Data Tools
    在 GitHub 上查看↗2
一览前 10 名对比
仓库Star 数语言许可证最后推送
inception-project/inception700JavaApache-2.02026年6月26日
jiesutd/yedda1.1KPythonApache-2.02023年2月19日
rtiinternational/smart230PythonMIT2024年12月2日
heartexlabs/label-studio27.6KTypeScriptApache-2.02026年6月17日
chakki-works/doccano10.7KPythonMIT2026年4月14日
cvat-ai/cvat15.3KPythonmit2026年2月19日
doccano/doccano10.7KPythonMIT2026年4月14日
humansignal/label-studio27.6KTypeScriptApache-2.02026年6月16日
label-sleuth/label-sleuth273PythonApache-2.02025年5月26日
argilla-io/argilla5KPythonApache-2.02026年6月22日

Related searches

  • 数据标注工具
  • Code annotation tool
  • a library for rendering interactive data visualizations
  • an open source dataset for image segmentation
  • Generic interface libraries
  • Text search engine
  • Data access layer
  • UI component library