---
license: mit
library_name: pytorch
pipeline_tag: image-classification
tags:
  - tree-species-classification
  - ecology
  - neon
  - deepforest
  - crop-model
---

# NEON Tree Genus Classification - RESNET18

A resnet18 model trained for tree genus classification on the NEON Tree Crown Dataset.
This model is designed for integration with [DeepForest](https://github.com/weecology/DeepForest) as a CropModel.

## Model Details

- **Architecture**: resnet18
- **Task**: Tree genus classification
- **Classes**: 60 genus classes
- **Input size**: 224x224 RGB images
- **Normalization**: ImageNet (mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
- **Dataset**: NEON Tree Crown Dataset (~48,000 tree crowns from 30 NEON sites)

## Usage with DeepForest

```python
from deepforest import CropModel

# Load model
model = CropModel.load_model("ritesh313/neon-tree-resnet18-genus")

# Use with DeepForest predictions
# (after running detection with main DeepForest model)
results = model.predict(image_crops)
```

## Direct PyTorch Usage

```python
import torch
from safetensors.torch import load_file
from torchvision import transforms

# Load model weights
state_dict = load_file("model.safetensors")

# Load config for label mapping
import json
with open("config.json") as f:
    config = json.load(f)

# Create your model architecture and load weights
# model.load_state_dict(state_dict)

# Preprocessing
preprocess = transforms.Compose([
    transforms.Resize((224, 224)),
    transforms.ToTensor(),
    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
])
```

## Training Details

- **Framework**: PyTorch Lightning
- **Optimizer**: AdamW
- **Learning Rate**: 1e-3
- **Scheduler**: ReduceLROnPlateau
- **Data Split**: 70/15/15 (train/val/test)
- **Seed**: 42

## Dataset

The model was trained on the NEON Tree Crown Dataset, which includes:
- 47,971 individual tree crowns
- 167 species / 60 genera
- 30 NEON sites across North America
- Multi-modal data: RGB, Hyperspectral, LiDAR (this model uses RGB only)

## Citation

If you use this model, please cite:

```bibtex
@software{neontreeclassification,
  author = {Chowdhry, Ritesh},
  title = {NeonTreeClassification: Multi-modal Tree Species Classification},
  url = {https://github.com/Ritesh313/NeonTreeClassification},
  year = {2026}
}
```

## License

MIT License