purdue-arc/sphero-swarm
Feb 2025 – Feb 2025
1 Month active
Languages Used
NumPyOpenCVPythonSciPy
Technical Skills
Computer VisionImage ProcessingObject DetectionObject TrackingOpenCVPython Development
Naunidha Singh
PROFILE
Naunidha Singh
Worked on the purdue-arc/sphero-swarm repository to enhance perception capabilities for autonomous control and experimental validation. Developed robust LED detection using OpenCV and Python, integrating it into the perception pipeline to improve object-level tracking and experiment reproducibility. Implemented ball tracking and visualization features, enabling more effective perception experiments and streamlined validation with new test and demo video assets. Updated the LED perception script to support multiple video inputs and improved visualization, facilitating faster iteration cycles. Addressed minor runtime issues in the tracking script to reduce onboarding friction. The work focused on computer vision, image processing, and video processing techniques.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
1
Lines of code
190
Activity Months1
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Work History
February 2025
4 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for purdue-arc/sphero-swarm focused on enhancing perception capabilities for autonomous control and experimental validation. Delivered robust LED perception improvements with OpenCV-based detection, integrated ball tracking, and prepared perception-demo assets to accelerate experiments. Implemented small, targeted fixes to streamline runtime and improve reproducibility. The work aligns with our goals of reliable perception, repeatable experiments, and faster iteration cycles.
4 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for purdue-arc/sphero-swarm focused on enhancing perception capabilities for autonomous control and experimental validation. Delivered robust LED perception improvements with OpenCV-based detection, integrated ball tracking, and prepared perception-demo assets to accelerate experiments. Implemented small, targeted fixes to streamline runtime and improve reproducibility. The work aligns with our goals of reliable perception, repeatable experiments, and faster iteration cycles.
February 2025
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Quality Metrics
Correctness75.0%
Maintainability75.0%
Architecture60.0%
Performance50.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
NumPyOpenCVPythonSciPy
Technical Skills
Computer VisionImage ProcessingObject DetectionObject TrackingOpenCVPython DevelopmentVideo Processing
Repositories Contributed To
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