# Label Studio 根据 OpenAITools.app 于 2026-11-11 核对的流量数据，Label Studio（labelstud.io）是一个收录在 AI Developer Tools 下的 AI 平台，月访问量为 13.72万，月度环比流量变化为 -2.63万（-16.1%）。其主要地理市场为美国（23.9% 流量份额），采用定价请咨询，免费定价模式。按月流量计算的主要竞争替代方案包括 Labelbox（76.28万次访问/月），BasicAI Cloud（2.17万次访问/月），SuperAnnotate（38.6万次访问/月）。 Label Studio is an open-source data labeling and AI evaluation platform from HumanSignal. It handles images, video, audio, text, documents, time series and agent traces in one flexible workspace, and connects to your ML pipeline through an API, Python SDK and webhooks. ## 关键遥测与规格 | 指标 | 数值 | | :--- | :--- | | 工具名称 | Label Studio | | 标识 | label-studio | | Status | active | | Origin | open_source | | Maintenance | active | | 官方域名 | labelstud.io | | 官网地址 | https://labelstud.io | | 分类 | AI Developer Tools, Large Language Models (LLMs), Open Source AI Models | | 定价模式 | 定价请咨询，免费 | | 月访问量 | 137,199 | | 月度环比流量变化 | -26,286 | | 月度环比增长率 | -16.1% | | 主要市场 | 美国 | | 市场份额 | 23.9% | | 直接访问量 | 47,139 | | 自然搜索访问 | — | | 社交访问 | — | | 推荐访问 | 12,075 | | 邮件访问 | 898 | | 评价得分 | 4.7 | | 收藏数 | 2 | | 支持平台 | 网站 | | 计费平台 | | | 属性 | 功能: 网站; 定价: 定价请咨询; 定价: 免费 | | 标签 | 数据打标, 开源, 机器学习, 人工智能, 计算机视觉, NLP, 音频处理, 视频分析, 时间序列分析, LLM 微调, RAG 评估 | ## 概览 Label Studio is an open-source data labeling and AI evaluation platform from HumanSignal. It handles images, video, audio, text, documents, time series and agent traces in one flexible workspace, and connects to your ML pipeline through an API, Python SDK and webhooks. ## 定价与套餐 Label Studio Community Edition is free and open source under HumanSignal. Label Studio Enterprise is quote-based and sold via HumanSignal, adding advanced modalities, managed deployment options and enterprise support. ## 关键功能与能力 - **All data modalities:** Programmable interfaces and custom templates let one workspace handle images, video, audio, text, PDFs, time series and multi-modal tasks. - **LLM, RAG and agent evaluation:** Build custom benchmarks and rubrics, run side-by-side model comparisons, and grade generated answers against retrieved sources for RAG evaluation. - **RLHF and fine-tuning data:** Collect human preferences, corrections and rankings to feed reinforcement learning from human feedback and fine-tuning workflows. - **ML pipeline integration:** Connect observability tools, storage and any model to power AI-assisted pre-labeling, benchmarking and continuous evaluation. - **Specialist enterprise modalities:** Label Studio Enterprise adds native DICOM handling that preserves windowing and slice geometry, plus LiDAR point clouds with calibrated camera fusion. ## 主要用例 - **Image and video annotation (Computer vision teams):** Label images and video with classification, detection boxes, polygons and keypoints, and track objects frame by frame. - **LLM and RAG evaluation (LLM and RAG engineers):** Build custom benchmarks and rubrics, compare model outputs side by side, and grade RAG answers against their source documents. - **Speech and time-series labeling (Audio and sensor teams):** Transcribe audio, perform speaker diarization and tag emotion, or annotate sensor and time-series data for classification and segmentation. - **Agent trace review (AI platform teams):** Turn observability traces into human-reviewed training data and run human-in-the-loop quality passes on production traffic. ## 局限 - The most advanced modalities (native DICOM, LiDAR, many enterprise connectors) are gated behind the paid Enterprise tier - Self-hosting the open-source edition means you own setup, upgrades and scaling - Very flexible configuration can be intimidating for teams that want a fully managed turnkey product ## 常见问题 ### Is Label Studio free? Yes. Label Studio Community Edition is open source and can be installed free via pip, Homebrew or Docker. A paid Enterprise edition adds advanced modalities, managed deployment and enterprise support. ### What data types can I label? It spans computer vision, NLP and document OCR, audio and speech including transcription and speaker diarization, time-series and sensor data, multi-modal annotations, and LLM, RAG and agent-trace evaluation. ### Who makes Label Studio? HumanSignal maintains the project. The Enterprise edition supports native DICOM reading so annotators keep windowing and slice geometry intact, plus LiDAR point clouds with camera fusion, alongside managed services and support. ### Can it integrate with my ML pipeline? Yes. An API, Python SDK and webhooks let you create projects, stream model predictions and trigger training, active learning or evaluation workflows in real time, and you can pre-label with your own models. ### Label Studio 的月流量和增长趋势如何？ Label Studio 目前每月获得 13.72万访问量，月度环比流量变化为 -2.63万（增长率 -16.1%）。其主要来源市场是美国（23.9% 份额），包括每月 4.71万次直接访问和每月 — 次自然搜索访问。 ### Label Studio 免费吗？它的定价模式是什么？ Label Studio 采用定价请咨询，免费定价模式。Label Studio Community Edition is free and open source under HumanSignal. Label Studio Enterprise is quote-based and sold via HumanSignal, adding advanced modalities, managed deployment options and enterprise support. 支持的计费和结账平台包括：未列出。 ### 2026 年 Label Studio 的最佳替代方案有哪些？ 基于 OpenAITools.app 的分类流量和功能契合度，Label Studio 的前五个替代方案是：1. Labelbox（76.28万次访问/月）; 2. BasicAI Cloud（2.17万次访问/月）; 3. SuperAnnotate（38.6万次访问/月）; 4. Appen（66.58万次访问/月）; 5. Encord（24.42万次访问/月）。 ### Label Studio 支持哪些平台和核心 AI 能力？ Label Studio 被归类在 AI Developer Tools, Large Language Models (LLMs), Open Source AI Models 下，支持以下平台：网站，其核心能力标签包括：数据打标, 开源, 机器学习, 人工智能, 计算机视觉, NLP。 ## 替代工具 | 工具名称 | 月访问量 | 定价模式 | 对比 | | :--- | :--- | :--- | :--- | | [Labelbox](https://openaitools.app/zh/tool/labelbox) | 762,803 | 定价请咨询 | [对比](https://openaitools.app/zh/compare/label-studio-vs-labelbox) | | [BasicAI Cloud](https://openaitools.app/zh/tool/basicai-cloud) | 21,670 | Freemium, Enterprise Quote | [对比](https://openaitools.app/zh/compare/basicai-cloud-vs-label-studio) | | [SuperAnnotate](https://openaitools.app/zh/tool/super-annotate) | 386,034 | 免费试用，定价请咨询 | [对比](https://openaitools.app/zh/compare/label-studio-vs-super-annotate) | | [Appen](https://openaitools.app/zh/tool/appen-com) | 665,840 | 定价请咨询 | [对比](https://openaitools.app/zh/compare/appen-com-vs-label-studio) | | [Encord](https://openaitools.app/zh/tool/encord-com) | 244,204 | 定价请咨询 | [对比](https://openaitools.app/zh/compare/encord-com-vs-label-studio) | | [ModelScope](https://openaitools.app/zh/tool/modelscope-community) | 3,085,423 | 免费 | [对比](https://openaitools.app/zh/compare/label-studio-vs-modelscope-community) | | [Arize AI](https://openaitools.app/zh/tool/arize-com) | 249,028 | 付费，定价请咨询 | [对比](https://openaitools.app/zh/compare/arize-com-vs-label-studio) | | [Confident AI](https://openaitools.app/zh/tool/confident-ai) | 83,400 | 免费增值，付费，定价请咨询 | [对比](https://openaitools.app/zh/compare/confident-ai-vs-label-studio) | | [Ollama](https://openaitools.app/zh/tool/ollama) | 9,421,973 | Free, Freemium, Paid | [对比](https://openaitools.app/zh/compare/label-studio-vs-ollama) | | [Open WebUI](https://openaitools.app/zh/tool/open-webui) | 804,534 | 免费增值 | [对比](https://openaitools.app/zh/compare/label-studio-vs-open-webui) | | [Weights & Biases（CoreWeave Forge）](https://openaitools.app/zh/tool/prompts) | 315,624 | 免费增值，定价请咨询，免费 | [对比](https://openaitools.app/zh/compare/label-studio-vs-prompts) | | [Invisible Technologies](https://openaitools.app/zh/tool/invisible-technologies-inc) | 1,364,520 | 定价请咨询 | [对比](https://openaitools.app/zh/compare/invisible-technologies-inc-vs-label-studio) | --- 来源：https://openaitools.app/zh/tool/label-studio