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README.md

@@ -51,22 +51,21 @@ configs:
     - 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}
+ @misc{doherty2025leafyspurge,
+  title={Leafy Spurge Dataset},
+  author={
+    Doherty, Kyle and 
+    Gurinas, Max and 
+    Samsoe, Erik and 
+    Casper, Charles and 
+    Larkin, Beau and 
+    Ramsey, Philip and 
+    Trabucco, Brandon and 
+    Salakhutdinov, Ruslan
+  },
+  year={2025},
+  howpublished = {\url{https://huggingface.co/datasets/kylewdoherty/leafy-spurge}},
+  doi={10.57967/hf/2508},
   }
 date_published: 2024-05-02
 language:
@@ -79,40 +78,53 @@ size_categories:
 
 # 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)
+This dataset comprises 1.3 cm resolution aerial images of grasslands in western Montana, USA, captured by a commercial drone. Many scenes contain leafy spurge (\textit{Euphorbia esula}), introduced to North America, now widespread in rangeland ecosystems, which is highly invasive and damaging to crop production and biodiversity. Technicians surveyed 1000 points in the study area, noting spurge presence or absence, and recorded each point’s position with precision global navigation satellite systems. We extracted crops from an orthoimage at these locations. We publicly release these images and metadata as a Hugging Face Dataset, accessible in one line of code. Our aim is to invite the research community to develop classifiers as early warning systems for spurge invasion. We established baselines for state-of-the-art vision models, achieving 0.85 test accuracy, demonstrating the feasibility yet difficulty of this classification task.
 
+Please visit out
 # Data loading and pre-processing
 
-As a Hugging Face dataset, you may load the Leafy Spurge training set as follows:
-```python 
+#datasets module documentation at:
+#https://huggingface.co/docs/datasets/en/quickstart
 from datasets import load_dataset
 
-ds = load_dataset('mpg-ranch/leafy_spurge', 'context', split='train')
-ds['image'][405]
+#39x39 pixel train and test data
+crop_train = load_dataset('mpg-ranch/leafy_spurge', 'crop', split='train') 
+crop_test = load_dataset('mpg-ranch/leafy_spurge', 'crop', split='test') 
+
+#1024x1024 pixel train and test data
+context_train = load_dataset('mpg-ranch/leafy_spurge', 'context', split='train') 
+context_test = load_dataset('mpg-ranch/leafy_spurge', 'context', split='test') 
+
+#unlabelled orthomosaic
+orthomosaic = load_dataset('mpg-ranch/leafy_spurge', 'unlabelled', split='train') 
+
+# Get the first observation from the crop training set
+first_observation = crop_train[0]
+
+# Extract the image and metadata
+image = first_observation['image']
+metadata = {key: value for key, value in first_observation.items() if key != 'image'}
+
+# Print the metadata and show image
+print("Metadata for the first observation:")
+for key, value in metadata.items():
+    print(f"{key}: {value}")
 ```
-<img src="https://huggingface.co/datasets/mpg-ranch/leafy_spurge/resolve/main/doc_figures/full_size_tile.png" width="1024px" height="1024px">
+<img src="https://huggingface.co/datasets/mpg-ranch/leafy_spurge/resolve/main/data/crop/train/present/0_0.tif" width="39px" height="39px">
 
 # 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}
+@misc{huggingface2025leafyspurge,
+  title = {Leafy Spurge Dataset},
+  author = {{Doherty, Kyle} and {Gurinas, Max} and {Samsoe, Erik} and {Casper, Charles} and {Larkin, Beau} and {Ramsey, Philip} and {Trabucco, Brandon} and {Salakhutdinov, Ruslan}},
+  year = {2025},
+  howpublished = {\url{https://huggingface.co/datasets/kylewdoherty/leafy-spurge}},
+  doi = {10.57967/hf/2508},
 }
+```
+
+Note:
+This dataset accompanies our manuscript entitled “Ground-truthed and high-resolution drone images of the leafy spurge weed plant (\textit{Euphorbia esula})”, which has been provisionally accepted (pending minor revisions) at Scientific Data. Upon final publication, we will update this citation to reflect the journal-assigned DOI.