
Developed visualization enhancements for the neuroinformatics-unit/movement repository, enabling bounding boxes and pose data to be rendered as Napari shapes layers. The work involved implementing robust data conversion routines for both pose and bounding box datasets, ensuring accurate and flexible visualization within the Napari plugin framework. Separate shapes layers were architected for each dataset, supporting clearer data organization and analysis. Documentation and tests were updated to reflect the new features, promoting reproducibility and reliability in movement studies. The project was delivered using Python and leveraged skills in data visualization, plugin development, and testing, with a focus on improving analysis workflows.
2025-07 monthly summary for neuroinformatics-unit/movement. Delivered visualization enhancements enabling bounding boxes to be rendered as Napari shapes layers, with robust data conversion for both pose and bounding box datasets, and architecture to maintain separate layers per dataset. Updated documentation and tests to reflect new functionality. No major bugs fixed this month. This work improves data visualization, accelerates analysis workflows, and enhances reproducibility for movement studies.
2025-07 monthly summary for neuroinformatics-unit/movement. Delivered visualization enhancements enabling bounding boxes to be rendered as Napari shapes layers, with robust data conversion for both pose and bounding box datasets, and architecture to maintain separate layers per dataset. Updated documentation and tests to reflect new functionality. No major bugs fixed this month. This work improves data visualization, accelerates analysis workflows, and enhances reproducibility for movement studies.

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