Magically faster Semantic Segmentation annotation

Annotate images for Semantic Segmentation dramatically faster with our AI assisted interactive annotation tool.

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We call it Magic Segment

Automatic semantic segmentation use cases

Create object boundaries in a few clicks

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 for a variety of object types - small objects, large structures, as well as objects without a differentiated boundary.

Instance segmentation

Instance Segmentation annotation

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.

Slash project management overhead

Drastically reduce management overhead through efficient project management, detailed reports, easy-to-setup QA workflows and much more.

  • Task management

    Stay on top of your annotation tasks with Projects, tasks and batches. Divide tasks into batches to quickly divide work, and combine tasks into projects to keep everything organized.

  • User permissions

    Assign roles to your team members and control who can do what in your projects.

  • 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
  • Multi-annotator setup

    Get your data labeled by multiple annotators and use consensus metrics to choose the best annotations.

  • Honeypot setup

    Setup honeypot to assign accurate Quality metrics to your annotation tasks.

  • Quality metric

    Dive deep into your dataset with automatically calculated Quality metrics like IoU, accuracy, confusion matrix etc.

QA Workflow
  • 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.

  • Detailed project reports

    See the status of your labeling tasks in a central place, and identify potential bottlenecks in your workflow.

  • 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

Just looking to get your data labeled ?

Want to get your datasets labeled quickly? Or need a hand accelerating your data labeling efforts?

Leave the hassle of data labeling to us. Just share your data with our team, and we will handle the rest.

Semantic segmentation annotation services