README.md

---
task_categories:
- feature-extraction
- image-classification
tags:
- biology
pretty_name: cardomomqv-880
size_categories:
- n<1K
---


# 📦 Cardamom Quality Grading with Computer Vision (YOLOv8)

This Hugging Face model is trained on our **Cardamom Quality Grading** dataset, designed to automatically assess the quality of cardamom spice using computer vision techniques.

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## 🎯 Model Purpose

The model performs **quality grading** on cardamom, classifying it into defined categories using YOLOv8. It's ideal for researchers and practitioners in:

- Agricultural automation
- Food quality control
- Computer vision in agritech

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## 📖 Dataset & Reference

This work is based on the research paper:

**Computer Vision Technique for Quality Grading of Cardamom Spice**  
Ahamed Ahnaf, Mohamed Rafeek, A. R. M. Nizzad, Nazaar Fathima Mafaza  
*2025 International Research Conference on Smart Computing and Systems Engineering (SCSE)*  
DOI: [10.1109/SCSE65633.2025.11031046](https://doi.org/10.1109/SCSE65633.2025.11031046)

---


## 📌 To Use the Model

```python
from transformers import VisionModel

model = VisionModel.from_pretrained("nizzad/CardamomQV-880")
results = model.predict(image="cardamom_sample.jpg")
print(results)
```

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## 📌 Citation

If you use this model or dataset in your work, please cite our publication:

```bibtex
@INPROCEEDINGS{11031046,
  author={Ahamed Ahnaf and Mohamed Rafeek and A. R. M. Nizzad and Nazaar Fathima Mafaza},
  booktitle={2025 International Research Conference on Smart Computing and Systems Engineering (SCSE)},
  title={Computer Vision Technique for Quality Grading of Cardamom Spice},
  year={2025},
  pages={1-6},
  doi={10.1109/SCSE65633.2025.11031046}
}
```

---