pytorch/vision
Feb 2025 – Feb 2025
1 Month active
Languages Used
C++Python
Technical Skills
Bounding Box RepresentationComputer VisionImage TransformationsPyTorchUnit Testing
Antoine Simoulin
PROFILE
Antoine Simoulin
Antoine Simoulin developed support for rotated bounding box formats in the pytorch/vision repository, enabling more advanced oriented-object detection workflows. He designed and implemented conversion logic for new formats such as XYWHR, CXCYWHR, and XYXYXYXY, integrating these into existing utilities and ensuring compatibility with image transformations. Using Python and PyTorch, Antoine updated core modules and expanded the unit test suite to validate the new functionality across various scenarios. His work demonstrated a thorough approach to feature delivery, from initial design through comprehensive testing, and addressed the need for flexible bounding box representation in computer vision applications without introducing regressions.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
461
Activity Months1
Work History
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 performance and contribution summary for pytorch/vision focusing on feature delivery and quality improvements. Key outcomes include feature delivery for rotated bounding box formats (XYWHR, CXCYWHR, XYXYXYXY), comprehensive test updates, and solid execution across the codebase.
1 Commits • 1 Features
Feb 1, 2025February 2025 performance and contribution summary for pytorch/vision focusing on feature delivery and quality improvements. Key outcomes include feature delivery for rotated bounding box formats (XYWHR, CXCYWHR, XYXYXYXY), comprehensive test updates, and solid execution across the codebase.
February 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
Bounding Box RepresentationComputer VisionImage TransformationsPyTorchUnit Testing
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