Encord Annotate allows you to efficiently label visual data, manage large-scale annotation teams, and ensure high-quality data for machine learning applications through customizable workflows and quality control tools. Get started with Annotate to streamline your labeling processes and produce top-tier training data.

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When to use Encord Annotate?

Encord Annotate is designed to support your machine learning pipeline by providing tools to efficiently turn unlabeled data into labeled data that can be used to train models. Encord Annotate diagram

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What data does Encord Annotate Support?

Annotate supports various data formats and modalities, providing the tools to efficiently label large Datasets. It is optimized for high performance, even with extensive datasets and complex labeling tasks.
Single ImageImage GroupImage SequenceVideoAudioDocumentsText
Supported file formats.jpeg .png .webp .avif .bmp .tiff* .tif*.jpeg .png .webp .avif .bmp .tiff* .tif*.jpeg .png .webp .avif .bmp.mp4 .mov* .webm .mkvmpeg x-wav flac.pdf.html, .json, .xml, .txt, and many more
* TIFF and MOV files are only supported in Safari due to Chromium browser limitations. We recommend using Chrome for all other workflows. More info here.
Familiarize yourself with our Best Practices before getting started with Encord Annotate

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Getting Started with Encord Annotate

Familiarize yourself with our Best Practices before getting started with Encord Annotate
The easiest way to get started is to follow the steps outlined in our Getting Started guide for Annotate.
  1. Import your data
  2. Create Dataset
  3. Create Ontology
  4. Create Project
  5. Label your data