Repository Structure Overview
highway-vehicle-detection-code/
├── models/ # Trained model weights
│ ├── yolov8m_stage2_improved_best.pt # Final model (recommended)
│ └── yolov8m_stage1_smart_best.pt # Stage 1 model
├── training_runs/ # Complete training structure
│ ├── stage1_smart/
│ │ ├── args.yaml # Training arguments
│ │ └── weights/
│ │ └── last.pt # Last epoch weights
│ └── stage2_improved/
│ ├── args.yaml # Training arguments
│ ├── weights/
│ │ └── last.pt # Last epoch weights
│ ├── BoxF1_curve.png # F1 score curve
│ ├── BoxPR_curve.png # Precision-Recall curve
│ └── labels.jpg # Label distribution
├── training_logs/ # Training metrics and visualizations
│ ├── stage2_results.png # Training results
│ ├── stage2_confusion_matrix.png # Confusion matrix
│ ├── stage2_results.csv # Detailed metrics
│ └── stage2_val_batch0_pred.jpg # Validation samples
├── finetune_dataset/ # Fine-tuning dataset (92 images)
│ ├── images/ # Training images
│ ├── labels/ # Annotation files
│ ├── README.dataset.txt # Dataset info
│ ├── README.roboflow.txt # Roboflow info
│ └── README.md # Dataset overview
├── dataset_configs/ # Dataset configurations
│ ├── main_data.yaml # Main dataset config
│ └── finetune_data.yaml # Fine-tuning config
├── main.py # Main application
├── example_usage.py # Usage examples
├── requirements.txt # Dependencies
├── test_improved_model.bat # Testing script
├── PROJECT_REPORT.md # Complete documentation
├── TEAM_INSTRUCTIONS.md # Team setup guide
└── README.md # This file
Key Files
- models/: Ready-to-use trained models
- training_runs/: Complete training structure (like local runs/ folder)
- finetune_dataset/: The 92-image fine-tuning dataset
- main.py: Complete vehicle detection application
- External links: YouTube demo and Kaggle dataset