roboflow/supervision
Jul 2025 – Jul 2025
1 Month active
Languages Used
MarkdownPython
Technical Skills
Backend DevelopmentBug FixBug FixingCode RefactoringComputer VisionData Annotation
Ashp116
PROFILE
Ashp116
Ashwin Patel contributed to the roboflow/supervision repository by developing robust backend utilities and enhancing visualization tools for computer vision workflows. He implemented a box_iou utility in Python, focusing on both accuracy and comprehensive documentation, and introduced a SplineAnnotator to enable smooth, hyperparameter-driven trajectory visualization. Ashwin unified smoothing logic in the TraceAnnotator, allowing configurable trace line smoothing for improved data annotation and visualization. He also fixed a variable naming bug in the move_oriented_boxes function, ensuring correct geometric transformations. His work emphasized code refactoring, documentation, and pre-commit hygiene, resulting in more reliable model evaluation pipelines and streamlined developer onboarding.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
11Total
Bugs
1
Commits
11
Features
3
Lines of code
316
Activity Months1
Your Network
22 people
Work History
July 2025
11 Commits • 3 Features
Jul 1, 2025July 2025 highlights major progress in the roboflow/supervision module focused on robust utilities, enhanced visualization, and quality improvements. Key features delivered include a new box_iou utility with comprehensive documentation and strengthened robustness; a SplineAnnotator for smooth trajectory visualization with hyperparameter-driven smoothing; and unified TraceAnnotator smoothing integration via a configurable smooth flag. A bug fix corrected the input variable name for sv.move_oriented_boxes to ensure proper box movement, plus documentation improvements and pre-commit hygiene. These changes improve tracking accuracy, visualization reliability, and developer onboarding, delivering measurable business value in model evaluation pipelines and UI-assisted analytics.
11 Commits • 3 Features
Jul 1, 2025July 2025 highlights major progress in the roboflow/supervision module focused on robust utilities, enhanced visualization, and quality improvements. Key features delivered include a new box_iou utility with comprehensive documentation and strengthened robustness; a SplineAnnotator for smooth trajectory visualization with hyperparameter-driven smoothing; and unified TraceAnnotator smoothing integration via a configurable smooth flag. A bug fix corrected the input variable name for sv.move_oriented_boxes to ensure proper box movement, plus documentation improvements and pre-commit hygiene. These changes improve tracking accuracy, visualization reliability, and developer onboarding, delivering measurable business value in model evaluation pipelines and UI-assisted analytics.
July 2025
Activity
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Quality Metrics
Correctness93.6%
Maintainability97.2%
Architecture91.0%
Performance81.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
Backend DevelopmentBug FixBug FixingCode RefactoringComputer VisionData AnnotationData VisualizationDocumentationGeometryImage ProcessingPython DevelopmentSoftware Development
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