Live!Check out the Label Studio 2024 recap post
Back to integrations

Semi-Automated Bounded Box Labeling with OpenMMLab

Overview

OpenMMLab integrates with the Label Studio machine learning API to provide semi-automated bounded-box labeling using the library and the RTMDdet model. Quickly run pre-labeling on images with the integration, using standard COCO format, using MMDet’s algorithms and existing weight files. Thanks to Label Studio’s model refinement feature users can create a high-quality dataset with minimal effort compared to the manual annotation of images.

Benefits

Integrating OpenMMLab with Label Studio provides the following benefits:

  • Automated Labeling: get a quick start on your image labeling with automatic object detection
  • Standard COCO Format: bounding boxes are supplied using the standard COCO format.
  • Fast Integration: The machine learning connection is provided by the library, allowing for a rapid connection to Label Studio with minimal coding.

Related Integrations

Flair

Named entity recognition

Ultralytics YOLO

Computer vision models

Tesseract

Automated bounding box OCR

Scikit Learn

Machine learning toolkit