Project-AgML/Plant_leaf_diseases_dataset_classification

Plant Leaf Diseases Dataset Classification

This dataset provides real RGB images of sweet potato leaves affected by various diseases, captured in a controlled laboratory environment in Tainan, Taiwan. Images were acquired using Fujifilm GFX100s and X100F cameras, offering high-resolution visual data for agricultural disease detection research. The dataset contains raw and augmented versions.
The raw dataset contains 55,448 images.
Images per class:

• Apple___Apple_scab: 630
• Apple___Black_rot: 621
• Apple___Cedar_apple_rust: 275
• Apple___healthy: 1,645
• Background_without_leaves: 1,143
• Blueberry___healthy: 1,502
• Cherry___Powdery_mildew: 1,052
• Cherry___healthy: 854
• Corn___Cercospora_leaf_spot Gray_leaf_spot: 513
• Corn___Common_rust: 1,192
• Corn___Northern_Leaf_Blight: 985
• Corn___healthy: 1,162
• Grape___Black_rot: 1,180
• Grape___Esca_(Black_Measles): 1,383
• Grape___Leaf_blight_(Isariopsis_Leaf_Spot): 1,076
• Grape___healthy: 423
• Orange___Haunglongbing_(Citrus_greening): 5,507
• Peach___Bacterial_spot: 2,297
• Peach___healthy: 360
• Pepper,_bell___Bacterial_spot: 997
• Pepper,_bell___healthy: 1,478
• Potato___Early_blight: 1,000
• Potato___Late_blight: 1,000
• Potato___healthy: 152
• Raspberry___healthy: 371
• Soybean___healthy: 5,090
• Squash___Powdery_mildew: 1,835
• Strawberry___Leaf_scorch: 1,109
• Strawberry___healthy: 456
• Tomato___Bacterial_spot: 2,127
• Tomato___Early_blight: 1,000
• Tomato___Late_blight: 1,909
• Tomato___Leaf_Mold: 952
• Tomato___Septoria_leaf_spot: 1,771
• Tomato___Spider_mites Two-spotted_spider_mite: 1,676
• Tomato___Target_Spot: 1,404
• Tomato___Tomato_Yellow_Leaf_Curl_Virus: 5,357
• Tomato___Tomato_mosaic_virus: 373
• Tomato___healthy: 1,591

The augmented dataset contains 61,486 images.
Images per class:

• Apple___Apple_scab: 1,000
• Apple___Black_rot: 1,000
• Apple___Cedar_apple_rust: 1,000
• Apple___healthy: 1,645
• Background_without_leaves: 1,143
• Blueberry___healthy: 1,502
• Cherry___Powdery_mildew: 1,052
• Cherry___healthy: 1,000
• Corn___Cercospora_leaf_spot Gray_leaf_spot: 1,000
• Corn___Common_rust: 1,192
• Corn___Northern_Leaf_Blight: 1,000
• Corn___healthy: 1,162
• Grape___Black_rot: 1,180
• Grape___Esca_(Black_Measles): 1,383
• Grape___Leaf_blight_(Isariopsis_Leaf_Spot): 1,076
• Grape___healthy: 1,000
• Orange___Haunglongbing_(Citrus_greening): 5,507
• Peach___Bacterial_spot: 2,297
• Peach___healthy: 1,000
• Pepper,_bell___Bacterial_spot: 1,000
• Pepper,_bell___healthy: 1,478
• Potato___Early_blight: 1,000
• Potato___Late_blight: 1,000
• Potato___healthy: 1,000
• Raspberry___healthy: 1,000
• Soybean___healthy: 5,090
• Squash___Powdery_mildew: 1,835
• Strawberry___Leaf_scorch: 1,109
• Strawberry___healthy: 1,000
• Tomato___Bacterial_spot: 2,127
• Tomato___Early_blight: 1,000
• Tomato___Late_blight: 1,909
• Tomato___Leaf_Mold: 1,000
• Tomato___Septoria_leaf_spot: 1,771
• Tomato___Spider_mites Two-spotted_spider_mite: 1,676
• Tomato___Target_Spot: 1,404
• Tomato___Tomato_Yellow_Leaf_Curl_Virus: 5,357
• Tomato___Tomato_mosaic_virus: 1,000
• Tomato___healthy: 1,591

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

Citation

@article{yang2026label,
  title={Label-Free Deep Learning with Feature Adaptation for Crop Anomaly Detection on Small Datasets},
  author={Yang, Ming-Der and Lee, Tzu-Han and Tseng, Hsin-Hung and Su, Tung-Ching and Hsu, Yu-Chun},
  journal={Agriculture},
  volume={16},
  pages={854},
  year={2026},
  publisher={MDPI}
}

The dataset itself can be cited as:

J, A. R. U. N. P. A. N. D. I. A. N. (2019). Data for: Identification of Plant Leaf Diseases Using a 9-layer Deep Convolutional Neural Network [Dataset]. Mendeley. https://doi.org/10.17632/TYWBTSJRJV.1

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