OpenHUTB/nn
Apr 2026 – Apr 2026
1 Month active
Languages Used
BatchfilePython
Technical Skills
AnacondaData CollectionMachine LearningNeural NetworksPythonPython programming
LUOrj2005
PROFILE
Luorj2005
Worked on the OpenHUTB/nn repository to enhance simulation workflows by delivering three new features and addressing one bug. Focused on improving accessibility through Chinese localization and standardizing the project entry point for easier onboarding and maintenance. Developed data visualization and camera-follow capabilities for CARLA simulations, leveraging Python and data visualization techniques to improve operator observability. Optimized data collection performance by removing unnecessary graphical displays, reducing resource usage, and stabilizing data recording. Automated PilotNet experiment runs within the Anaconda environment, streamlining user workflows. Demonstrated proficiency in Python, automation, and simulation development while emphasizing maintainability and operational efficiency throughout the project.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
6Total
Bugs
1
Commits
6
Features
3
Lines of code
1,574
Activity Months1
Your Network
263 peopleWork History
April 2026
6 Commits • 3 Features
Apr 1, 2026April 2026 monthly summary for OpenHUTB/nn focusing on delivering localization, visualization, performance optimization, and workflow automation. Highlights include Chinese localization and project-entry standardization for better accessibility and maintainability; CARLA data visualization and camera-follow enhancements improving observability and operator experience; data collection performance optimization by removing pygame display to reduce resource usage; and PilotNet automation script in Anaconda to streamline running experiments.
6 Commits • 3 Features
Apr 1, 2026April 2026 monthly summary for OpenHUTB/nn focusing on delivering localization, visualization, performance optimization, and workflow automation. Highlights include Chinese localization and project-entry standardization for better accessibility and maintainability; CARLA data visualization and camera-follow enhancements improving observability and operator experience; data collection performance optimization by removing pygame display to reduce resource usage; and PilotNet automation script in Anaconda to streamline running experiments.
April 2026
Activity
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Quality Metrics
Correctness96.8%
Maintainability86.6%
Architecture86.6%
Performance90.0%
AI Usage26.8%
Skills & Technologies
Programming Languages
BatchfilePython
Technical Skills
AnacondaData CollectionMachine LearningNeural NetworksPythonPython programmingautomationdata collectiondata visualizationfull stack developmentgame developmentmachine learningscriptingsimulationsimulation development
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