README.md

metadata

license: apache-2.0
task_categories:
  - image-classification
language:
  - en
tags:
  - fine-grained-classification
  - agricultural-vision
  - adulteration-detection
  - food-quality
  - saffron
size_categories:
  - n<1K

SaffronVerify Dataset

Dataset Summary

SaffronVerify is a fine-grained image classification dataset for saffron quality grading. It contains images of saffron across three quality categories — from premium grade to adulterated samples — intended for training computer vision models to detect saffron purity and adulteration.

Dataset Structure

The dataset follows the standard ImageFolder layout and is split into training and validation sets.

saffron-verify/
├── train/
│   ├── mogra/
│   ├── lacha/
│   └── adulterated/
└── val/
    ├── mogra/
    ├── lacha/
    └── adulterated/

Splits

Split	Description
train	80% of total images
val	20% of total images

Classes

Label	Original Class	Description
mogra	class A	Premium grade saffron — deep red, fully intact stigmas
lacha	class B	Mixed grade — contains yellow styles along with red stigmas
adulterated	class C	Adulterated saffron — broken threads, debris, foreign matter

Image Format

• All images are saved as JPEG (.jpg) at quality 95
• All images are converted to RGB (3-channel)
• Input sources included .jpg, .png, and .webp originals

Loading the Dataset

from datasets import load_dataset

ds = load_dataset("Arko007/saffron-verify")
print(ds)
# DatasetDict({
#     train: Dataset({features: ['image', 'label'], num_rows: ...})
#     val:   Dataset({features: ['image', 'label'], num_rows: ...})
# })

print(ds["train"].features["label"].names)
# ['adulterated', 'lacha', 'mogra']

Intended Use

This dataset is intended for:

• Training image classifiers for saffron quality grading
• Research on agricultural product adulteration detection
• Benchmarking fine-grained food quality classification models

Preprocessing

• Dataset was preprocessed using a custom Python pipeline
• Random train/val split with seed 42 for reproducibility
• Images sequentially renamed per class per split (e.g. mogra_001.jpg)
• RGBA images composited to RGB prior to saving

License

This dataset is released under the MIT License.

Citation

If you use this dataset in your work, please cite:

@dataset{saffronverify2026,
  author    = {Arko007},
  title     = {SaffronVerify: Saffron Quality Classification Dataset},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/Arko007/saffron-verify}
}