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README.md

@@ -36,4 +36,39 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- image-classification
+size_categories:
+- n<1K
 ---
+# Escayard Vine Esca
+
+EscaYard's ground-level part: 253 geotagged smartphone photographs of individual grapevines in two vineyards (B7 and B9) in Tomiño, Pontevedra, Galicia, Spain, taken on 14 and 15 July 2022 at midday and in the evening with an iPhone X and a Xiaomi Poco smartphone, each labelled for visible Esca symptoms (tiger-stripe leaves): 50 vines YES, 203 NO. The source datasheet also gives the number of grape clusters counted on 42 vines, the vineyard, the time of day, the device, and the vine's RTK GNSS position (ETRS89 / UTM zone 29N, EPSG:25829), kept here as columns. Seven NO rows are marked in the source as photos that were missing and copied from the previous vine with similar characteristics (photo_copied). The record's UAV multispectral orthomosaics, LiDAR point clouds and trunk-location shapefile are not included. The dataset contains 253 images across 2 classes: NO, YES.  
+Images per class:
+- NO: 203
+- YES: 50
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+## Citation
+
+```bibtex
+@article{vlez2024escayard,
+  title={EscaYard: Precision viticulture multimodal dataset of vineyards affected by Esca disease consisting of geotagged smartphone images, phytosanitary status, UAV 3D point clouds and Orthomosaics},
+  author={Vélez, Sergio and Ariza-Sentís, Mar and Valente, João},
+  journal={Data in Brief},
+  volume={54},
+  pages={110497},
+  year={2024},
+  publisher={Elsevier}
+}
+```
+
+
+The dataset itself can be cited as:
+
+Vélez, S., Ariza-Sentís, M., &amp; Valente, J. (2023). *Precision viticulture dataset for detailed vineyard mapping composed of geotagged smartphone ground images, phytosanitary status, UAV orthomosaics, 3D point clouds, and RTK GNSS data - Northern Spain, July 2022* [Dataset]. Zenodo. https://doi.org/10.5281/ZENODO.10362568
+
+
+*This dataset was reformatted from its original format to match HuggingFace standards.*