| --- |
| 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. |
|
|
| --- |
|
|
| ## 🎯 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 |
|
|
| --- |
|
|
| ## 📖 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) |
| ``` |
|
|
| --- |
|
|
|
|
| ## 📌 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} |
| } |
| ``` |
|
|
| --- |
|
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|
