OpenHUTB/nn
Sep 2025 – Dec 2025
3 Months active
Languages Used
MarkdownNumPyPythonTensorFlowC++
Technical Skills
Autonomous Driving SystemsComputer VisionDeep LearningDocumentationMachine LearningNumPy
aasdar
PROFILE
Aasdar
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
20Total
Bugs
0
Commits
20
Features
6
Lines of code
5,715
Activity Months3
Your Network
159 people
Work History
December 2025
15 Commits • 2 Features
Dec 1, 20252025-12 OpenHUTB/nn Monthly Summary: Delivered end-to-end Vehicle Detection System (YOLOv4) core with data pipeline, model integration, training and prediction scripts, and VOCdevkit-ready dataset structure, enabling production-ready vehicle detection. Built Vehicle Detection Evaluation Utilities (get_gt_txt.py, get_dr_txt.py) with dataset support and documentation, enabling automated mAP evaluation. Reorganized dataset and code structure with VOCdevkit folder, training scripts (train.py), and dataset artifacts; deprecated outdated components to reduce technical debt. Strengthened documentation and code quality with extensive in-line comments and READMEs. Established scalable workflow for reproducibility and future enhancements with pre-trained weights, dataset references, and evaluation tooling.
15 Commits • 2 Features
Dec 1, 20252025-12 OpenHUTB/nn Monthly Summary: Delivered end-to-end Vehicle Detection System (YOLOv4) core with data pipeline, model integration, training and prediction scripts, and VOCdevkit-ready dataset structure, enabling production-ready vehicle detection. Built Vehicle Detection Evaluation Utilities (get_gt_txt.py, get_dr_txt.py) with dataset support and documentation, enabling automated mAP evaluation. Reorganized dataset and code structure with VOCdevkit folder, training scripts (train.py), and dataset artifacts; deprecated outdated components to reduce technical debt. Strengthened documentation and code quality with extensive in-line comments and READMEs. Established scalable workflow for reproducibility and future enhancements with pre-trained weights, dataset references, and evaluation tooling.
December 2025
October 2025
2 Commits • 1 Features
Oct 1, 2025Month: 2025-10 - Delivered end-to-end Vehicle Detection and Tracking System for OpenHUTB/nn, enabling automated traffic analysis through YOLOv3-based detection, line-based vehicle counting, and real-time visualization. Implemented SORT-based multi-object tracking with IOU association, KalmanBoxTracker, and a Track manager to reliably link detections across frames. Added core components (main.py, yolov3.py, sort.py), integrated video input processing, and visualization; removed non-core lane_detection components to streamline maintenance. Updated README and zero-downtime refactors for clearer API and testability.
October 2025
2 Commits • 1 Features
Oct 1, 2025Month: 2025-10 - Delivered end-to-end Vehicle Detection and Tracking System for OpenHUTB/nn, enabling automated traffic analysis through YOLOv3-based detection, line-based vehicle counting, and real-time visualization. Implemented SORT-based multi-object tracking with IOU association, KalmanBoxTracker, and a Track manager to reliably link detections across frames. Added core components (main.py, yolov3.py, sort.py), integrated video input processing, and visualization; removed non-core lane_detection components to streamline maintenance. Updated README and zero-downtime refactors for clearer API and testability.
September 2025
3 Commits • 3 Features
Sep 1, 2025September 2025 (OpenHUTB/nn): Delivered three core items: readability improvements for TensorFlow 2.0 exercise comparisons, a new OpenCV-based lane and path detection prototype, and a refactor narrowing the project to vehicle detection with lane-detection components removed. No explicit critical bug fixes were logged this month; the work focused on feature delivery, readability, and maintainability, resulting in clearer validation of custom vs. TensorFlow results and a cleaner, more focused codebase. This set of changes enhances testability, accelerates prototyping of perception features, and reduces ongoing maintenance overhead.
3 Commits • 3 Features
Sep 1, 2025September 2025 (OpenHUTB/nn): Delivered three core items: readability improvements for TensorFlow 2.0 exercise comparisons, a new OpenCV-based lane and path detection prototype, and a refactor narrowing the project to vehicle detection with lane-detection components removed. No explicit critical bug fixes were logged this month; the work focused on feature delivery, readability, and maintainability, resulting in clearer validation of custom vs. TensorFlow results and a cleaner, more focused codebase. This set of changes enhances testability, accelerates prototyping of perception features, and reduces ongoing maintenance overhead.
September 2025
Activity
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Quality Metrics
Correctness87.8%
Maintainability85.0%
Architecture85.0%
Performance83.0%
AI Usage31.0%
Skills & Technologies
Programming Languages
C++MarkdownNumPyPythonTensorFlow
Technical Skills
Autonomous Driving SystemsComputer VisionData AnnotationData ProcessingDeep LearningDocumentationKalman FiltersMachine LearningModel EvaluationNumPyObject DetectionObject TrackingOpenCVPyTorchPython
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