DeepLabCut/DeepLabCut
Dec 2024 – Feb 2025
2 Months active
Languages Used
PythonMarkdownYAML
Technical Skills
CI/CDComputer VisionDebuggingDeep LearningMachine LearningTesting
Niels Poulsen
PROFILE
Niels Poulsen
Worked on DeepLabCut/DeepLabCut, focusing on improving reliability, numerical robustness, and test coverage in computer vision workflows. Addressed issues with snapshot path handling by ensuring compatibility between Path objects and torch.save, preventing unpickling errors and stabilizing CI processes. Enhanced numerical consistency by standardizing NaN handling in detector snapshots and loss metrics. Delivered a feature aligning crop sampling and HRNet backbone padding to 32-pixel divisors, and integrated the CSPNext_M network into evaluation tests. Expanded pose evaluation API test coverage and refined indexing for pcutoff values. Contributed to documentation clarity, utilizing Python, YAML, and deep learning frameworks throughout the development process.
Overall Statistics
Feature vs Bugs
20%Features
Repository Contributions
6Total
Bugs
4
Commits
6
Features
1
Lines of code
57
Activity Months2
Your Network
135 peopleShared Repositories
13
Alexander MathisMember
Andrew J SpenceMember
Cyril AchardMember
Cyril AchardMember
Yaroslav HalchenkoMember
Jaap de RuyterMember
Zelin2001Member
Mark HarfoucheMember
Mackenzie MathisMember
Work History
February 2025
3 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary highlighting key features delivered, major bug fixes, and impact for DeepLabCut/DeepLabCut. This period focused on aligning data processing with 32-pixel crop sampling, ensuring HRNet backbones use 32 padding divisors, and expanding test coverage for pose evaluation API, while improving docs for onboarding.
3 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary highlighting key features delivered, major bug fixes, and impact for DeepLabCut/DeepLabCut. This period focused on aligning data processing with 32-pixel crop sampling, ensuring HRNet backbones use 32 padding divisors, and expanding test coverage for pose evaluation API, while improving docs for onboarding.
February 2025
December 2024
3 Commits
Dec 1, 2024December 2024: Focused on reliability and numerical robustness in DeepLabCut/DeepLabCut. Delivered two bug fixes that improve test stability and model evaluation consistency, directly enhancing developer productivity and user experience.
December 2024
3 Commits
Dec 1, 2024December 2024: Focused on reliability and numerical robustness in DeepLabCut/DeepLabCut. Delivered two bug fixes that improve test stability and model evaluation consistency, directly enhancing developer productivity and user experience.
Activity
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Quality Metrics
Correctness88.4%
Maintainability90.0%
Architecture86.6%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonYAML
Technical Skills
API TestingCI/CDComputer VisionConfiguration ManagementDebuggingDeep LearningDeep Learning FrameworksDocumentationMachine LearningPythonTesting
Repositories Contributed To
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