OpenHUTB/nn
Sep 2025 – Dec 2025
4 Months active
Languages Used
PythonMarkdown
Technical Skills
CNNData AugmentationDeep LearningFile ManagementImage ClassificationKeras
实验604黄光达
PROFILE
实验604黄光达
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
13Total
Bugs
0
Commits
13
Features
8
Lines of code
9,966
Activity Months4
Your Network
159 people
Work History
December 2025
4 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for OpenHUTB/nn focused on delivering real-time drone perception and navigation enhancements while improving maintainability through targeted cleanup. The work enabled faster decision-making in dynamic environments and established reusable workflows for forecasting and path planning, setting a strong foundation for scalable autonomous missions.
4 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for OpenHUTB/nn focused on delivering real-time drone perception and navigation enhancements while improving maintainability through targeted cleanup. The work enabled faster decision-making in dynamic environments and established reusable workflows for forecasting and path planning, setting a strong foundation for scalable autonomous missions.
December 2025
November 2025
3 Commits • 2 Features
Nov 1, 2025November 2025 — OpenHUTB/nn delivered core autonomous perception capabilities and streamlined ML data workflows, enabling faster iteration and clearer data pipelines for production readiness. Key features include a real-time Drone Visual Navigation System powered by a pretrained CNN for image classification and navigation decisions, plus a dataset organization function that categorizes training images by usage scenario and clarifies dataset download links in the README.
November 2025
3 Commits • 2 Features
Nov 1, 2025November 2025 — OpenHUTB/nn delivered core autonomous perception capabilities and streamlined ML data workflows, enabling faster iteration and clearer data pipelines for production readiness. Key features include a real-time Drone Visual Navigation System powered by a pretrained CNN for image classification and navigation decisions, plus a dataset organization function that categorizes training images by usage scenario and clarifies dataset download links in the README.
October 2025
4 Commits • 2 Features
Oct 1, 2025Month: 2025-10 — OpenHUTB/nn. Delivered a Drone Perception: Image Classification Module using a pre-trained ResNet18, including data loading, preprocessing, model evaluation, and training-progress visualization. Updated README to specify environment requirements (Python version, PyTorch, NumPy, PIL, scikit-learn, matplotlib) to streamline setup and onboarding. Executed internal codebase improvements, including refactoring the Gaussian basis function in linear_regression-tf2.0.py with clearer logic and comments, and performed repository housekeeping (file renaming and directory restructuring) to enhance maintainability. These efforts advance drone-perception capabilities, reduce setup friction for new contributors, and improve code quality and collaboration efficiency.
4 Commits • 2 Features
Oct 1, 2025Month: 2025-10 — OpenHUTB/nn. Delivered a Drone Perception: Image Classification Module using a pre-trained ResNet18, including data loading, preprocessing, model evaluation, and training-progress visualization. Updated README to specify environment requirements (Python version, PyTorch, NumPy, PIL, scikit-learn, matplotlib) to streamline setup and onboarding. Executed internal codebase improvements, including refactoring the Gaussian basis function in linear_regression-tf2.0.py with clearer logic and comments, and performed repository housekeeping (file renaming and directory restructuring) to enhance maintainability. These efforts advance drone-perception capabilities, reduce setup friction for new contributors, and improve code quality and collaboration efficiency.
October 2025
September 2025
2 Commits • 2 Features
Sep 1, 2025Month: 2025-09 — Focused on improving maintainability of the drone perception module and delivering a deployable image classification workflow using transfer learning. Key work includes a file organization refactor for the drone perception module and the addition of a MobileNetV2-based image classification script with data preprocessing, augmentation, early stopping, and model checkpointing. These changes reduce future maintenance effort and accelerate ML experimentation and potential deployment.
September 2025
2 Commits • 2 Features
Sep 1, 2025Month: 2025-09 — Focused on improving maintainability of the drone perception module and delivering a deployable image classification workflow using transfer learning. Key work includes a file organization refactor for the drone perception module and the addition of a MobileNetV2-based image classification script with data preprocessing, augmentation, early stopping, and model checkpointing. These changes reduce future maintenance effort and accelerate ML experimentation and potential deployment.
Activity
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Quality Metrics
Correctness82.4%
Maintainability83.0%
Architecture80.0%
Performance80.0%
AI Usage35.4%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
3D modelingCNNCode RefactoringComputer VisionComputer visionData AugmentationData ManagementData PreprocessingData ProcessingDeep LearningDocumentationDrone NavigationFile ManagementImage ClassificationImage Processing
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