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README.md

@@ -24,4 +24,33 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- image-segmentation
+size_categories:
+- n<1K
 ---
+# Appletreedataset Intertwined Segmentation
+
+This dataset provides real RGB images of intertwined apple trees in a field environment, capturing complex branch and fruit structures during the 2021 harvest season. Collected using a handheld iPhone 6 at a South Korean agricultural research facility, it offers a naturalistic representation of outdoor crop conditions for semantic segmentation tasks. The dataset contains 150 images with pixel-level mask annotations.
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+The original train/test/val split has been preserved in the `split` column.
+
+## Citation
+
+```bibtex
+@article{la2023deep,
+  title={Deep Learning-Based Segmentation of Intertwined Fruit Trees for Agricultural Tasks},
+  author={La, Young-Jae and Seo, Dasom and Kang, Junhyeok and Kim, Minwoo and Yoo, Tae-Woong and Oh, Il-Seok},
+  journal={Agriculture},
+  volume={13},
+  pages={2097},
+  year={2023},
+  publisher={MDPI}
+}
+```
+
+
+*This dataset was reformatted from its original format to match HuggingFace standards.*