OpenwaterHealth/OpenLIFU-python
Nov 2024 – Nov 2024
1 Month active
Languages Used
Python
Technical Skills
Algorithm DevelopmentObject-Oriented ProgrammingSoftware FrameworksTesting
Loic Tetrel
PROFILE
Loic Tetrel
Developed the initial virtual fitting framework for the OpenwaterHealth/OpenLIFU-python repository, focusing on a scalable foundation for future algorithmic enhancements. Designed and implemented the VirtualFit class in Python, enabling parameterized search ranges, steps, and thresholds to support flexible virtual fitting experiments. Incorporated object-oriented programming principles to structure utilities for generating search grids and analyzing transducer positions, while establishing basic logging for improved observability. The work included placeholders for skin extraction and plane fitting, guiding subsequent development. Added a unit test to validate the core run method, ensuring a reliable baseline for future testing and integration with downstream software pipelines.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
192
Activity Months1
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Work History
November 2024
1 Commits • 1 Features
Nov 1, 2024Month: 2024-11 — OpenLIFU-python development focused on establishing a reusable virtual fitting framework and laying the groundwork for future capabilities. Key work centered on designing a VirtualFit class with parameterized search ranges, steps, and thresholds, plus utilities to generate a search grid and analyze transducer positions. The effort includes basic logging, placeholders for skin extraction and plane fitting, and a unit test ensuring that the core run path executes. This work provides a scalable foundation for iteration, testing, and integration with downstream pipelines, enabling quicker validation of virtual fitting strategies.
1 Commits • 1 Features
Nov 1, 2024Month: 2024-11 — OpenLIFU-python development focused on establishing a reusable virtual fitting framework and laying the groundwork for future capabilities. Key work centered on designing a VirtualFit class with parameterized search ranges, steps, and thresholds, plus utilities to generate a search grid and analyze transducer positions. The effort includes basic logging, placeholders for skin extraction and plane fitting, and a unit test ensuring that the core run path executes. This work provides a scalable foundation for iteration, testing, and integration with downstream pipelines, enabling quicker validation of virtual fitting strategies.
November 2024
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Algorithm DevelopmentObject-Oriented ProgrammingSoftware FrameworksTesting
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