Label Studio

What is Label Studio?

Label Studio is an open-source data labeling tool designed to prepare training data for computer vision, natural language processing, speech, voice, and video models. It offers flexibility for labeling all types of data.

Added on June 01 2023

Provides Website. Over 83.6K monthly visits.

Website
AI Developer Tools
83.6K

Website Traffic

Last Month's Visits:
83.6K (13.3K)
Last 3 Month's Visits:
232.3K (19.1K)
Last 6 Month's Visits:
495.7K (4.7K)
Total Visitors
Visitors Growth

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How to install?

How to use Label Studio?

To use Label Studio, you can follow these steps: 1. Install the Label Studio package through pip, brew, or clone the repository from GitHub. 2. Launch Label Studio using the installed package or Docker. 3. Import your data into Label Studio. 4. Choose the data type (images, audio, text, time series, multi-domain, or video) and select the specific labeling task (e.g., image classification, object detection, audio transcription). 5. Start labeling your data using customizable tags and templates. 6. Connect to your ML/AI pipeline and use webhooks, Python SDK, or API for authentication, project management, and model predictions. 7. Explore and manage your dataset in the Data Manager with advanced filters. 8. Support multiple projects, use cases, and users within the Label Studio platform.

Label Studio's Core Features

Flexible data labeling for all data types
Support for computer vision, natural language processing, speech, voice, and video models
Customizable tags and labeling templates
Integration with ML/AI pipelines via webhooks, Python SDK, and API
ML-assisted labeling with backend integration
Connectivity to cloud object storage (S3 and GCP)
Advanced data management with the Data Manager
Support for multiple projects and users
Trusted by a large community of Data Scientists

Label Studio's Use Cases

#1 Preparing training data for computer vision models
#2 Preparing training data for natural language processing models
#3 Preparing training data for speech and voice models
#4 Preparing training data for video models
#5 Classification of images, audio, text, and time series data
#6 Object detection and tracking in images and videos
#7 Semantic segmentation of images
#8 Speaker diarization and emotion recognition in audio
#9 Audio transcription
#10 Document classification and named entity extraction
#11 Question answering and sentiment analysis
#12 Time series analysis and event recognition
#13 Dialogue processing and optical character recognition
#14 Multi-domain applications requiring various types of data labeling

Label Studio Traffic

Visit Over Time

Monthly Visits
83.6K
Avg.Visit Duration
00:06:12
Page per Visit
3.74
Bounce Rate
45.71%
Feb 2023 - Jan 2024 All Traffic

Geography

Top 5 Regions

United States
33.12%
China
14.17%
India
5.10%
Korea
5.03%
Germany
4.36%
Feb 2023 - Jan 2024 Desktop Only

Traffic Sources

Direct
46.84%
Search
46.80%
Referrals
4.87%
Social
1.36%
Mail
0.13%
Display Ads
0.00%
Feb 2023 - Jan 2024 Worldwide Desktop Only

FAQ from Label Studio

Can Label Studio handle different types of data?
Can I integrate Label Studio with my ML/AI pipeline?
Does Label Studio support ML-assisted labeling?
Can I connect Label Studio to cloud object storage?
Is Label Studio suitable for multi-project and multi-user environments?

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