- Description:
The original citrus dataset contains 759 images of healthy and unhealthy citrus fruits and leaves. However, for now we only export 594 images of citrus leaves with the following labels: Black Spot, Canker, Greening, and Healthy. The exported images are in PNG format and have 256x256 pixels.
Dataset URL: https://data.mendeley.com/datasets/3f83gxmv57/2 License: http://creativecommons.org/licenses/by/4.0
Source code:
tfds.image_classification.CitrusLeaves
Versions:
0.1.1
: Citrus Leaves dataset0.1.2
(default): Website URL update
Download size:
63.87 MiB
Dataset size:
37.89 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
594 |
- Feature structure:
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=uint8),
'image/filename': Text(shape=(), dtype=string),
'label': ClassLabel(shape=(), dtype=int64, num_classes=4),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
image | Image | (None, None, 3) | uint8 | |
image/filename | Text | string | ||
label | ClassLabel | int64 |
Supervised keys (See
as_supervised
doc):('image', 'label')
Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):
- Citation:
@article{rauf2019citrus,
title={A citrus fruits and leaves dataset for detection and classification of
citrus diseases through machine learning},
author={Rauf, Hafiz Tayyab and Saleem, Basharat Ali and Lali, M Ikram Ullah
and Khan, Muhammad Attique and Sharif, Muhammad and Bukhari, Syed Ahmad Chan},
journal={Data in brief},
volume={26},
pages={104340},
year={2019},
publisher={Elsevier}
}