IBM/terratorch
Nov 2024 – Dec 2024
2 Months active
Languages Used
PythonShellYAML
Technical Skills
Batch processingComputer VisionDeep LearningDistributed computingMachine LearningMachine learning
Takao Moriyama
PROFILE
Takao Moriyama
Moriyama contributed to IBM/terratorch by developing scalable model training and object detection workflows over a two-month period. He implemented Slurm-based batch processing scripts in Python and Shell to enable distributed training on the Sen1Floods11 dataset, supporting multi-node and multi-GPU environments. Moriyama also established a foundational object detection framework, introducing modular configuration management in YAML and model factories for flexible detector benchmarking. He refactored configuration logic, improved optimizer handling with AdamW, and enhanced parameter freezing for training efficiency. His work addressed both feature development and bug fixes, resulting in more reproducible, maintainable, and efficient deep learning pipelines within the repository.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
5Total
Bugs
1
Commits
5
Features
3
Lines of code
827
Activity Months2
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Work History
December 2024
3 Commits • 1 Features
Dec 1, 2024December 2024: Delivered key improvements to IBM/terratorch's Object Detection workflow, including a configuration refactor, optimizer tuning (AdamW in YAML), a wrapper bug fix, and parameter freezing enhancements. These changes improve training stability, efficiency, and model correctness, enabling faster iteration and clearer configuration management.
3 Commits • 1 Features
Dec 1, 2024December 2024: Delivered key improvements to IBM/terratorch's Object Detection workflow, including a configuration refactor, optimizer tuning (AdamW in YAML), a wrapper bug fix, and parameter freezing enhancements. These changes improve training stability, efficiency, and model correctness, enabling faster iteration and clearer configuration management.
December 2024
November 2024
2 Commits • 2 Features
Nov 1, 2024November 2024: Delivered two core capabilities in IBM/terratorch that advance scalable model training and detector workflows: Slurm-based batch training scripts for Sen1Floods11 and a foundational object detection task framework.
November 2024
2 Commits • 2 Features
Nov 1, 2024November 2024: Delivered two core capabilities in IBM/terratorch that advance scalable model training and detector workflows: Slurm-based batch training scripts for Sen1Floods11 and a foundational object detection task framework.
Activity
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Quality Metrics
Correctness96.0%
Maintainability84.0%
Architecture92.0%
Performance84.0%
AI Usage24.0%
Skills & Technologies
Programming Languages
PythonShellYAML
Technical Skills
Batch processingComputer VisionDeep LearningDistributed computingMachine LearningMachine learningModel TrainingObject DetectionPyTorchShell scriptingconfiguration managementmachine learningobject detection
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