nizzad/CardamomQV-880

📦 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

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📌 To Use the Model

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:

@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}
}

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