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---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: idx
    dtype: int64
  - name: label
    dtype: string
  - name: longitude
    dtype: float64
  - name: latitude
    dtype: float64
  - name: easting
    dtype: float64
  - name: northing
    dtype: float64
  - name: elevation
    dtype: float64
  - name: time
    dtype: int64
  - name: cluster
    dtype: int64
configs:
- config_name: context
  drop_labels: false
  data_files:
  - split: train
    path:
    - data/context/train/**/*.tif
    - data/context/train/metadata.csv
  - split: test
    path:
    - data/context/test/**/*.tif
    - data/context/test/metadata.csv
- config_name: crop
  drop_labels: false
  data_files:
  - split: train
    path:
    - data/crop/train/**/*.tif
    - data/crop/train/metadata.csv
  - split: test
    path:
    - data/crop/test/**/*.tif
    - data/crop/test/metadata.csv
- config_name: unlabelled
  data_files:
  - split: train
    path:
    - data/orthomosaic/*.tif
license: cc-by-4.0
citation_bibtex: |
  @misc{doherty2024leafy,
    title={Leafy Spurge Dataset: Real-world Weed Classification Within Aerial Drone Imagery},
    author={
      Kyle Doherty and 
      Max Gurinas and 
      Erik Samsoe and 
      Charles Casper and 
      Beau Larkin and 
      Philip Ramsey and 
      Brandon Trabucco and 
      Ruslan Salakhutdinov
    },
    year={2024},
    eprint={2405.03702},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
  }
date_published: 2024-05-02
language:
- en
pretty_name: Leafy Spurge Dataset
size_categories:
- n<1K
---
<img src="https://huggingface.co/datasets/mpg-ranch/leafy_spurge/resolve/main/doc_figures/spurge_photo_2_panel.png" width="100%">

# Background

Leafy Spurge Dataset is a collection of top-down aerial images of grasslands in western Montana, USA. We surveyed a 150-hectare study area with a DJI Mavic 3M Drone from 50m above the ground surface and we assembled the images into a contiguous orthomosaic using Drone Deploy software. Many scenes in the study area contain a weed plant, leafy spurge (*Euphorbia esula*), which upsets the ecology of areas throughout North America. Botanists visited 1000 sites in the study area and gathered ground truth of leafy spurge presence/absence within 0.5 x 0.5 m plots. The position of these plots was referenced within the orthomosaic and these areas were cropped from the larger image. The resulting processed data are 1024 x 1024 pixel .tif files, though note the labelled areas correspond to the 39 x 39 pixel square (half-meter side length) found at the center of these crops. We include the context around the ground truth areas for experimental purposes. Our primary objective in serving these data is to invite the research community to develop classifiers that are effective early warning systems of spurge invasion at the highest spatial resolution possible. 

[Please refer to our data release paper on Arxiv for further details.](https://arxiv.org/abs/2405.03702)

# Data loading and pre-processing

As a Hugging Face dataset, you may load the Leafy Spurge training set as follows:
```python 
from datasets import load_dataset

ds = load_dataset('mpg-ranch/leafy_spurge', 'context', split='train')
ds['image'][405]
```
<img src="https://huggingface.co/datasets/mpg-ranch/leafy_spurge/resolve/main/doc_figures/full_size_tile.png" width="1024px" height="1024px">

# Suggested Citation

Please cite our dataset using the following BibTex entry:

```bibtex
@misc{doherty2024leafy,
  title={Leafy Spurge Dataset: Real-world Weed Classification Within Aerial Drone Imagery},
  author={
    Kyle Doherty and 
    Max Gurinas and 
    Erik Samsoe and 
    Charles Casper and 
    Beau Larkin and 
    Philip Ramsey and 
    Brandon Trabucco and 
    Ruslan Salakhutdinov
  },
  year={2024},
  eprint={2405.03702},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
}