AI-assisted Semantic Segmentation labeling

Draw semantic segmentation masks dramatically faster with our AI assisted interactive annotation tool.

Start for free

We call it Magic Segment

Automatic semantic segmentation Use cases

Create object boundaries automatically

Draw object boundaries upto 5x quicker for a wide variety of use-cases without the need for custom training of ML models.

Don't stop at the first output

Magic segment is an interactive tool. Once a boundary is drawn, you can instruct the tool to include or exclude a region of the object and the boundary will be automatically adjusted.

Flexible to all use-cases

The tool's interactive nature allows it to be effective in a variety of object types - small objects, large structures as well as objects without a differentiated boundary.

Instance segmentation

Instance & Panoptic Segmentation

Identify and separate individual objects within an image by drawing object boundaries for each instance of the object.

Combine semantic and instance segmentation into a single image and create high quality datasets for Panoptic segmentation.

Layers
Arrange objects in layers and utilise masking.
Preview mask
Preview how the exported mask will look.
Export formats
Export as PNG masks, or a variety of JSON formats.

Get more done in less time

  • Divide work in batches

    Automatically divide your tasks into batches so the work can be divided evenly within your team.

  • Reviewers

    Assign labelers and reviewers to each batch to ensure high quality annotation.

  • Annotation modes

    Move your batches into Annotation, Validation or Completed modes to keep track of exactly how much work remains to be done

Annotation modes and batches
  • Task management

    Create tasks to start labeling. Then group related tasks into projects, and assign projects to your users

  • User permissions

    Assign different roles to your users to easily keep permissions in check.

Annotation project management
  • Mark issues

    Free-flowing communication is key to ensuring high quality annotations. Pin-point mistakes within your data with issues.

  • Chat with team-members

    Talk with your team-members right within an issue to get to the source of the problem.

  • Measure quality

    Use number of resolved and unresolved issues as a measure of the quality of annotations of a task.

Annotation modes and batches
  • Time your annotation tasks

    Know exactly how much time each member of your team spent annotating data.

  • Annotation mode breakdown

    See how much time your team spent in each of the 3 annotation modes. This information is available at batch as well as task level.

  • Share with all stakeholders

    Export the information as CSV and share it with your team or end customers.

Annotation analytics
  • Create releases

    Export your data as a release and name it so you can identify it later. Keep the last 5 releases so you can download them anytime.

  • Choose what to export

    Choose the batches you want to export, so you dont have to download everything everytime something is updated

  • Export formats

    Export your LIDAR annotations in KITTI format. More formats are coming very soon!

Annotation Releases