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addobosz

PROFILE

Addobosz

Worked on the GHOST-Science-Club/tree-classification-irim repository to deliver a flexible, multi-architecture image classification framework over two months. Migrated the core model from ResNet to Vision Transformer, integrating pre-trained ImageNet weights and configurable layer freezing to balance accuracy and efficiency. Developed a model factory and configuration-driven system supporting ResNet18, InceptionV3, and ViT, with adaptive preprocessing and architecture-aware initialization. Enhanced Inception training by enabling auxiliary logits and robust output handling, improving stability across models. Used Python, PyTorch, and YAML to implement these features, focusing on maintainability, cross-architecture compatibility, and streamlined experimentation for future development and deployment.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

13Total
Bugs
0
Commits
13
Features
3
Lines of code
288
Activity Months2

Your Network

5 people

Work History

April 2025

10 Commits • 2 Features

Apr 1, 2025

Delivered a configurable, multi-architecture image classifier framework and Inception-specific training optimizations for the GHOST-Science-Club/tree-classification-irim repo in April 2025. Implemented a model factory and config-driven classifier to support ResNet18, InceptionV3, and ViT with architecture-aware preprocessing and initialization. Added Inception-specific training enhancements to enable auxiliary logits and robust handling of Inception outputs, improving stability and cross-architecture compatibility. Completed extensive local testing across architectures, updated configuration (config.yaml), and resolved quality issues (flake8) to raise reliability and maintainability. This work accelerates future feature delivery and enables broader deployment with lower risk.

March 2025

3 Commits • 1 Features

Mar 1, 2025

March 2025 monthly summary for the GHOST-Science-Club/tree-classification-irim workstream. The team delivered a migration from a ResNet-based classifier to a Vision Transformer (ViT) with a robust training setup, improving potential accuracy through transfer learning and streamlined experimentation. Cleaned legacy code to reduce maintenance overhead and ensure training updates target the correct ViT heads.

Activity

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Quality Metrics

Correctness86.2%
Maintainability90.8%
Architecture84.6%
Performance81.6%
AI Usage21.6%

Skills & Technologies

Programming Languages

PythonYAML

Technical Skills

Bug FixingCode RefactoringComputer VisionConfiguration ManagementDeep LearningImage PreprocessingMachine LearningModel ArchitectureModel TrainingPyTorchPyTorch LightningPythonTransformers

Repositories Contributed To

1 repo

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

GHOST-Science-Club/tree-classification-irim

Mar 2025 Apr 2025
2 Months active

Languages Used

PythonYAML

Technical Skills

Code RefactoringComputer VisionDeep LearningMachine LearningPyTorchPyTorch Lightning