appdevforall/CodeOnTheGo
Jan 2026 – Feb 2026
2 Months active
Languages Used
JSONKotlinXML
Technical Skills
Android DevelopmentBuild ConfigurationComputer VisionFirebase IntegrationImage ProcessingKotlin
avestaadfa
PROFILE
Avestaadfa
Avestan Arimani contributed to the appdevforall/CodeOnTheGo repository by developing and enhancing on-device computer vision and AI features using Kotlin, XML, and Firebase. Over two months, Avestan delivered a computer vision module that generates XML layouts from images, integrates zoom and analytics, and supports offline inference through llama.cpp and a dynamic Kotlin loader. They improved detection reliability by implementing ROI-based filtering and upgraded OCR capabilities via dependency and manifest updates. Their work addressed stability issues such as image rotation and memory management, while UI/UX improvements provided better user feedback during long-running tasks, demonstrating depth in Android development and machine learning integration.
Overall Statistics
Feature vs Bugs
40%Features
Repository Contributions
7Total
Bugs
3
Commits
7
Features
2
Lines of code
2,894
Activity Months2
Your Network
29 peopleSame Organization
@appdevforall.org9
Shared Repositories
20
Work History
February 2026
2 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for appdevforall/CodeOnTheGo: Delivered two core improvements that enhance detection reliability and OCR readiness. ROI-based Detection Filtering fixes margin false positives by constraining detections to a defined Region of Interest, reducing noise in the detection pipeline. OCR capability was enhanced by updating the OCR dependency to a beta version and adding AndroidManifest metadata to enable OCR capabilities, unlocking downstream text-recognition features. These changes improve overall system reliability, reduce manual review effort, and position the product for OCR-driven workflows. Technologies demonstrated include ROI-based image processing, ML Kit dependency management, and AndroidManifest integration, supported by commits 968c73b55822d97fa74be74226c0b8323b224b11 and 14b4632ff92c3606c368249c5ebadd21e89235ab.
2 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for appdevforall/CodeOnTheGo: Delivered two core improvements that enhance detection reliability and OCR readiness. ROI-based Detection Filtering fixes margin false positives by constraining detections to a defined Region of Interest, reducing noise in the detection pipeline. OCR capability was enhanced by updating the OCR dependency to a beta version and adding AndroidManifest metadata to enable OCR capabilities, unlocking downstream text-recognition features. These changes improve overall system reliability, reduce manual review effort, and position the product for OCR-driven workflows. Technologies demonstrated include ROI-based image processing, ML Kit dependency management, and AndroidManifest integration, supported by commits 968c73b55822d97fa74be74226c0b8323b224b11 and 14b4632ff92c3606c368249c5ebadd21e89235ab.
February 2026
January 2026
5 Commits • 1 Features
Jan 1, 2026Summary for 2026-01: This month delivered on-device computer vision improvements and strengthened on-device AI capabilities, with a focus on reliability, performance, and business value. Key CV feature delivery includes XML layout generation from images, zoom, and analytics integration, enabling faster UI generation and better tracking of CV events. We also introduced a local LLM pathway by integrating the llama.cpp module with a Kotlin LLamaAndroid wrapper and a dynamic loader (LlmInferenceEngine), enabling offline inference and improved responsiveness. Build stability and memory safety were enhanced by preventing TFLite compression in release builds and fixing image rotation and resource leaks in the CV pipeline; relative llama.cpp submodule paths improve portability. Telemetry and observability were improved through Firebase CV analytics and SLF4J-based logging, providing better insight into model performance and events. Finally, UI/UX improvements for the AI agent experience (cancelling state, progress updates) improve user feedback during long-running tasks.
January 2026
5 Commits • 1 Features
Jan 1, 2026Summary for 2026-01: This month delivered on-device computer vision improvements and strengthened on-device AI capabilities, with a focus on reliability, performance, and business value. Key CV feature delivery includes XML layout generation from images, zoom, and analytics integration, enabling faster UI generation and better tracking of CV events. We also introduced a local LLM pathway by integrating the llama.cpp module with a Kotlin LLamaAndroid wrapper and a dynamic loader (LlmInferenceEngine), enabling offline inference and improved responsiveness. Build stability and memory safety were enhanced by preventing TFLite compression in release builds and fixing image rotation and resource leaks in the CV pipeline; relative llama.cpp submodule paths improve portability. Telemetry and observability were improved through Firebase CV analytics and SLF4J-based logging, providing better insight into model performance and events. Finally, UI/UX improvements for the AI agent experience (cancelling state, progress updates) improve user feedback during long-running tasks.
Activity
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Quality Metrics
Correctness85.8%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
JSONKotlinXML
Technical Skills
Android DevelopmentBuild ConfigurationComputer VisionFirebase IntegrationImage ProcessingKotlinMachine LearningMobile AnalyticsUI DevelopmentUI/UX Design
Repositories Contributed To
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