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README.md

@@ -22,4 +22,41 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- image-classification
+size_categories:
+- 1K<n<10K
 ---
+# Pea Seed Viability Classification
+
+This dataset provides real RGB images of pea seeds collected in a laboratory environment in Beijing, China. The images were captured using a fixed-position MV-EM120C CCD camera under controlled conditions, offering a standardized resource for agricultural computer vision research on seed viability assessment. The dataset contains 3,000 images across 2 classes: dead, live.  
+Images per class:
+- dead: 1,500
+- live: 1,500
+
+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{men2026rapid,
+  title={Rapid Seed Viability Detection Using Laser Speckle Weighted Generalized Difference with Improved Residual Networks},
+  author={Men, Sen and Zhang, Junhao and Liu, Xinhong and Sun, Tianyi and Liu, Wei},
+  journal={Agronomy},
+  volume={16},
+  pages={81},
+  year={2026},
+  publisher={MDPI}
+}
+```
+
+
+The dataset itself can be cited as:
+
+Sen Men. (2025). *Rapid Seed Viability Detection Using Laser Speckle Weighted Generalized Difference with Improved Residual Networks* [Dataset]. Zenodo. https://doi.org/10.5281/ZENODO.18041269
+
+
+*This dataset was reformatted from its original format to match HuggingFace standards.*