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Evan Murray

PROFILE

Evan Murray

Developed and integrated a suite of features for the L42i/SPRAWL repository, focusing on spectral analysis, computer vision, and audio routing. Leveraged C++, OpenCV, and SuperCollider to implement camera tracking, spectral synthesis file generation, and a SuperCollider camera plugin, while standardizing initialization and connection workflows to streamline development and deployment. Introduced an automation playbook using YAML and shell scripting to orchestrate tasks, and enhanced connection handling with JackTrip support. Addressed workflow stability by fixing bugs related to variable definitions and error handling. The work reduced setup friction, improved reliability, and enabled end-to-end spectral and camera-driven audio processing pipelines.

Overall Statistics

Feature vs Bugs

77%Features

Repository Contributions

23Total
Bugs
3
Commits
23
Features
10
Lines of code
2,002
Activity Months1

Your Network

74 people

Same Organization

@gatech.edu
67

Shared Repositories

7
Ebranchek3Member
hwindishMember
anwaldtMember
BensonZhao2002Member
knordestMember
John WiseMember
Kenny, Orlando AntonioMember

Work History

November 2024

23 Commits • 10 Features

Nov 1, 2024

November 2024 monthly summary for L42i/SPRAWL: - Delivered a robust set of features spanning spectral analysis, computer vision, audio routing, and automation; enhanced initialization and connectivity workflows to improve developer velocity and platform reliability. - Implementations span spectral synthesis file generation, Evan scripts with working JackTrip, OpenCV-based camera tracking (single-file refactor with library imports and cleanup), camera data structures and detectors, and a SuperCollider camera plugin. Standardized capture initialization via Cap Open, introduced an automation playbook, and expanded connection handling (including Jack connections). Final spectral feature integration completed. - These changes enable end-to-end spectral analysis, camera-driven tracking, and reliable JackTrip connectivity, ready for production deployment and future feature expansion. Key outcomes include reduced setup friction, faster feature delivery, and improved stability across vision, audio, and automation pipelines.

Activity

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Quality Metrics

Correctness86.2%
Maintainability85.2%
Architecture81.8%
Performance76.6%
AI Usage20.0%

Skills & Technologies

Programming Languages

C++CMakeGitMarkdownSCSuperColliderYAML

Technical Skills

AnsibleAudio EngineeringAudio NetworkingAudio Plugin DevelopmentAudio ProgrammingAudio SynthesisBuild System ConfigurationC++C++ DevelopmentCMakeCode RefactoringComputer VisionConfiguration ManagementDSPDevOps

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

L42i/SPRAWL

Nov 2024 Nov 2024
1 Month active

Languages Used

C++CMakeGitMarkdownSCSuperColliderYAML

Technical Skills

AnsibleAudio EngineeringAudio NetworkingAudio Plugin DevelopmentAudio ProgrammingAudio Synthesis