appdevforall/CodeOnTheGo
Jan 2026 – Feb 2026
2 Months active
Languages Used
JSONKotlinXML
Technical Skills
Android DevelopmentBuild ConfigurationComputer VisionFirebase IntegrationImage ProcessingKotlin
avestaadfa
PROFILE
Avestaadfa
Worked on the appdevforall/CodeOnTheGo repository, delivering computer vision and AI-driven features for Android using Kotlin, XML, and Firebase. Developed on-device XML layout generation from images, integrated zoom and analytics for computer vision events, and enabled local LLM inference through llama.cpp with a Kotlin wrapper for offline AI tasks. Improved build stability by addressing TFLite model compression and memory management issues. Enhanced detection reliability by implementing ROI-based filtering and updated OCR capabilities via dependency and manifest changes. Focused on UI/UX improvements for AI agent feedback, leveraging machine learning, image processing, and mobile analytics to support robust, responsive user experiences.
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
33 peopleSame Organization
@appdevforall.org9
Shared Repositories
24
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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