# 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