Overview:

The Label Studio ML backend is an SDK that allows users to wrap their machine learning code and turn it into a web server. This web server can be connected to Label Studio, a platform for automating labeling tasks and retrieving pre-annotations from machine learning models. The ML backend has several use cases, including pre-annotating data with a model, using active learning to select relevant data for labeling, interactive (AI-assisted) labeling, and model fine-tuning based on recently annotated data. If users only need to load static pre-annotated data into Label Studio, running an ML backend may not be necessary and they can import the pre-annotated data instead.

Features:

Web server: The ML backend allows users to wrap their machine learning code into a web server.
Automated labeling: Users can automate labeling tasks by connecting the ML backend to Label Studio.
Pre-annotations: The ML backend can dynamically retrieve pre-annotations from the machine learning model.
Model fine-tuning: Users can fine-tune their machine learning models based on recently annotated data.
Active learning: The ML backend supports active learning to select the most relevant data for labeling.
Interactive labeling: Label Studio provides AI-assisted labeling through the ML backend.

Summary:

The Label Studio ML backend is an SDK that allows users to wrap their machine learning code into a web server and automate labeling tasks through Label Studio. It supports pre-annotations, active learning, interactive labeling, and model fine-tuning. Users can install the ML backend by following the installation guide and connecting it to Label Studio for a seamless labeling experience.

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Label Studio Ml Backend