Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor
A web-based labeling tool for creating AI training datasets from bitmap images and point clouds, developed for autonomous driving research.
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The tool supports manual annotation of 2D images and 3D point clouds for semantic segmentation. It runs as a Meteor application with a React frontend and renders point clouds using three.js. Labels are exported for use in training machine learning models for autonomous driving applications.
Frequently asked
- What is Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor?
- A web-based labeling tool for creating AI training datasets from bitmap images and point clouds, developed for autonomous driving research.
- Is semantic-segmentation-editor open source?
- Yes — Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor is open source, released under the MIT license.
- What language is semantic-segmentation-editor written in?
- Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor is primarily written in JavaScript.
- How popular is semantic-segmentation-editor?
- Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor has 2k stars on GitHub.
- Where can I find semantic-segmentation-editor?
- Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor is on GitHub at https://github.com/Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor.