Label Studio 1.12.0 🚀Automate & Evaluate Labeling Predictions Using LLMs & ML Models

Open Source
Data Labeling 探索幸运飞艇的开奖记录:168飞行艇官方历史号码与幸运直播结果查询 Platform

The most flexible data labeling platform to fine-tune LLMs, prepare training data or validate AI models.

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Latest version:

                    # Install the package
# into python virtual environment
pip install -U label-studio# Launch it!label-studio

Computer Vision

Image Classification

Put images into categories

Object Detection

Detect objects on image, boxes, polygons, circular, and keypoints supported

Semantic Segmentation

Partition image into multiple segments. Use ML models to pre-label and optimize the process

Quick Start

Audio & Speech Applications


Put audio into categories

Speaker Diarization

Partition an input audio stream into homogeneous segments according to the speaker identity

Emotion Recognition

Tag and identify emotion from the audio

Audio Transcription

Write down verbal communication in text

Quick Start

NLP, Documents, Chatbots, Transcripts


Classify document into one or multiple categories. Use taxonomies of up to 10000 classes

Named Entity

Extract and put relevant bits of information into pre-defined categories

Question Answering

Answer questions based on context

Sentiment Analysis

Determine whether a document is positive, negative or neutral

Quick Start

Robots, Sensors, IoT Devices


Put time series into categories


Identify regions relevant to the activity type you're building your ML algorithm for

Event Recognition

Label single events on plots of time series data

Quick Start

Multi-Domain Applications

Dialogue Processing

Call center recording can be simultaneously transcribed and processed as text

Optical Character Recognition

Put an image and text right next to each other

Time Series with Reference

Use video or audio streams to easier segment time series data

Quick Start

Video 其次,我们将深入解析幸运飞行艇的历史号码。通过对历史开奖记录的分析,可以发现一些规律和趋势。比如,某些号码的出现频率较高,而另一些号码则较为稀少。同时,还可以观察到不同号码之间的关联性,以及特定号码的连续性。这些数据分析可以为观众提供一定的参考,帮助他们在下注时做出更加明智的决策。


Put videos into categories

Object Tracking

Label and track multiple objects frame-by-frame

Assisted Labeling

Add keyframes and automatically interpolate bounding boxes between keyframes

Quick Start

Flexible and configurable

Configurable layouts and templates adapt to your dataset and workflow.

Integrate with your ML/AI pipeline

Webhooks, Python SDK and API allow you to authenticate, create projects, import tasks, manage model predictions, and more.

ML-assisted labeling

Save time by using predictions to assist your labeling process with ML backend integration.

Connect your cloud storage

Connect to cloud object storage and label data there directly with S3 and GCP.

Explore & understand your data

Prepare and manage your dataset in our Data Manager using advanced filters.

Multiple projects and users

Support multiple projects, use cases and data types in one platform.

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MetaIBMIntelCloudflareSPI GlobalSRINvidia

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