---
dataset_info:
- config_name: augmented
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Black Spot
          '1': Dry Leaf
          '2': Healthy Leaf
          '3': Leaf Holes
  splits:
  - name: train
    num_bytes: 400562967
    num_examples: 10000
  download_size: 400801970
  dataset_size: 400562967
- config_name: raw
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Black Spot
          '1': Dry Leaf
          '2': Healthy Leaf
          '3': Leaf Holes
  splits:
  - name: train
    num_bytes: 5570900810
    num_examples: 3113
  download_size: 5571111871
  dataset_size: 5570900810
configs:
- config_name: augmented
  data_files:
  - split: train
    path: augmented/train-*
- config_name: raw
  data_files:
  - split: train
    path: raw/train-*
  default: true
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
---
# Roseleafset Disease Classification

RoseLeafSet is a set of close-up smartphone photos of rose leaves collected in rose nurseries around Savar, Dhaka, Bangladesh, between October 30 and November 6, 2024, labelled into four foliar conditions: black spot, dry leaf, healthy leaf and leaf holes. Images were taken with a Vivo IQOO Z9x phone at 3264 x 2448 pixels. The default raw config holds the 3,113 original photos (class-imbalanced: 1,288 black spot, 324 dry leaf, 818 healthy, 683 leaf holes); the augmented config holds the authors' class-balanced augmented set of 2,500 images per class (10,000 total), derived from contrast-enhanced, padded versions of the originals.  The dataset contains raw and augmented versions.  
The raw dataset contains 3,113 images.  
Images per class:
- Black Spot: 1,288
- Dry Leaf: 324
- Healthy Leaf: 818
- Leaf Holes: 683

The augmented dataset contains 10,000 images.  
Images per class:
- Black Spot: 2,500
- Dry Leaf: 2,500
- Healthy Leaf: 2,500
- Leaf Holes: 2,500


This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

## Citation

```bibtex
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```

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The dataset itself can be cited as:

Jinia, J. T., Rahman, M. S., Mojumdar, M. U., &amp; Bijoy, M. H. I. (2025). *RoseLeafSet: Real-World Leaf Image Dataset for AI-Based Agricultural Solutions* [Dataset]. Mendeley Data. https://doi.org/10.17632/9G668BFHY5.3


*This dataset was reformatted from its original format to match HuggingFace standards.*