
Worked on enhancing non-live video analysis capabilities in the Purdue-Artificial-Intelligence-in-Music/Evaluator-code repository by developing per-frame extraction utilities for offline evaluation. Implemented getVideoAnnotations and getVideoBitmaps functions in Kotlin to provide frame-level detection results and timestamped bitmaps, leveraging FFmpegKit for video processing. Introduced asynchronous, multi-threaded processing using Kotlin Coroutines to improve throughput and scalability, with configurable concurrency for flexible resource management. Refactored the codebase to iterate frames based on frames per second, optimizing data flow for offline analysis. Documented memory usage considerations for bitmap extraction, ensuring users can manage resource constraints effectively during high-volume video processing tasks.
Month: 2025-09 — Focused on non-live video analysis enhancements and concurrency improvements in Purdue-Artificial-Intelligence-in-Music/Evaluator-code to enable richer offline evaluation and scalable processing.
Month: 2025-09 — Focused on non-live video analysis enhancements and concurrency improvements in Purdue-Artificial-Intelligence-in-Music/Evaluator-code to enable richer offline evaluation and scalable processing.

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