
During October 2025, Cau developed end-to-end CVAT folder export support for the docling-eval repository, enabling scalable conversion of entire CVAT export folders into DocLingDocument objects. They engineered a robust pipeline for processing CVAT deliveries, merging annotation XMLs and orchestrating workflows with improved error handling and reporting. Using Python and Pandas, Cau enhanced reading order validation for complex, multi-page documents, delivering more granular validation and correct handling of merged elements. They also addressed bounding box scaling for table cells, applying consistent transformations across documents. This work improved data integrity, reduced manual intervention, and enabled reliable, large-scale annotation processing workflows.

October 2025 performance summary for docling-eval: Delivered end-to-end capabilities for CVAT folder exports by adding folder-mode support to convert entire CVAT export folders into DocLingDocument objects, enabling scalable, folder-structured annotation workflows. Implemented a CVAT deliveries pipeline with merging annotation XMLs, orchestration, and robust error handling for visualizations, significantly improving throughput and reliability of CVAT deliveries processing. Enhanced reading order validation for multipage and complex structures, delivering more granular validation reports and correct handling of merged elements and exclusions. Resolved bounding box scaling for table cells with a consistent storage_scale transformation across table items, improving annotation accuracy and downstream rendering. Overall, these changes reduce manual intervention, improve data integrity, and enable scalable processing of richer CVAT exports across folders and multi-page documents.
October 2025 performance summary for docling-eval: Delivered end-to-end capabilities for CVAT folder exports by adding folder-mode support to convert entire CVAT export folders into DocLingDocument objects, enabling scalable, folder-structured annotation workflows. Implemented a CVAT deliveries pipeline with merging annotation XMLs, orchestration, and robust error handling for visualizations, significantly improving throughput and reliability of CVAT deliveries processing. Enhanced reading order validation for multipage and complex structures, delivering more granular validation reports and correct handling of merged elements and exclusions. Resolved bounding box scaling for table cells with a consistent storage_scale transformation across table items, improving annotation accuracy and downstream rendering. Overall, these changes reduce manual intervention, improve data integrity, and enable scalable processing of richer CVAT exports across folders and multi-page documents.
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