openvinotoolkit/training_extensions
Aug 2025 – Aug 2025
1 Month active
Languages Used
JavaScriptSCSSTypeScripttsx
Technical Skills
CSS ModulesFront End DevelopmentFrontend DevelopmentReactState ManagementTypeScript
Camilo
PROFILE
Camilo
Developed a foundational data collection workflow for the openvinotoolkit/training_extensions repository, focusing on accelerating machine learning dataset creation. Built a gallery-based interface using React and TypeScript, enabling users to curate data through a multi-select grid-list and per-item annotation with real-time status indicators. Leveraged CSS Modules for modular UI components and implemented state management to support batch labeling and efficient status tracking. Established a maintainable folder structure to streamline onboarding and future enhancements. This work reduced labeling friction and improved data quality, laying the groundwork for scalable input pipelines and supporting faster, higher-quality model training within the project’s ecosystem.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
1,275
Activity Months1
Your Network
28 peopleWork History
August 2025
3 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08 (openvinotoolkit/training_extensions): Delivered a foundational end-to-end data collection workflow to accelerate ML dataset creation. Implemented a Gallery-based data curation interface with multi-select grid-list and per-item annotation (accept/reject) plus visible status indicators. This work establishes a scalable input pipeline for training data and reduces labeling friction, enabling faster, higher-quality model training.
3 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08 (openvinotoolkit/training_extensions): Delivered a foundational end-to-end data collection workflow to accelerate ML dataset creation. Implemented a Gallery-based data curation interface with multi-select grid-list and per-item annotation (accept/reject) plus visible status indicators. This work establishes a scalable input pipeline for training data and reduces labeling friction, enabling faster, higher-quality model training.
August 2025
Activity
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Quality Metrics
Correctness86.6%
Maintainability83.4%
Architecture83.4%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaScriptSCSSTypeScripttsx
Technical Skills
CSS ModulesFront End DevelopmentFrontend DevelopmentReactState ManagementTypeScriptUI Components
Repositories Contributed To
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