# CropGuard GH — Dataset Kit

Everything you need to assemble the training dataset and understand both systems.

## Contents
- **DATASET_GUIDE.md** — which datasets to download, from where, under what licence, how they map to the 55 classes, and how to build the `data/` folder. **Start here.**
- **class_names.txt** — the canonical 55 class names (must match the training folders and `recommendations.json`).
- **scripts/download_dataset.py** — lists every source, auto-downloads the Kaggle sets, prints manual links for the rest.
- **scripts/prepare_dataset.py** — maps the downloaded raw folders into the 55 class folders and splits 70/15/15 into `train/val/test`.
- **docs/STANDALONE_HTML_DOCUMENTATION.md** — full docs for the single-file browser app (`cropguard.html`).
- **docs/BACKEND_SYSTEM_DOCUMENTATION.md** — full docs for the training + FastAPI + React stack.

## Quick path
```bash
python scripts/download_dataset.py --out ./raw_downloads   # then unzip everything
python scripts/prepare_dataset.py --raw ./raw_downloads --out ./data
cd ../cropguard-system/backend && python train.py --data ../../data --arch efficientnet
```