Datasets:
File size: 3,868 Bytes
d83e640 4a42423 de12fd2 4a42423 d83e640 28e9c23 de12fd2 d83e640 de12fd2 28e9c23 8ba9723 de12fd2 28e9c23 de12fd2 b6dd68a bdbff2b 8336629 0335c10 b6dd68a 98e0999 54f95d0 728fd1e 98e0999 709dc99 cb96ee9 cf12b0d b49e612 cf12b0d 343b91d 026a75a cf12b0d 755336b c14b77c 755336b c14b77c 312289d b631dcb c14b77c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 |
---
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}
}
|