Project-AgML/ct_pestnet_crop_pest_classification_2

Ct Pestnet Crop Pest Classification 2

This dataset comprises real-world field images capturing crop pests under natural agricultural conditions. Collected using ground-based RGB imaging platforms, it provides diverse pest visualizations relevant to in-field crop monitoring and pest identification tasks. The dataset contains 4,508 images across 40 classes: 0, 1, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 2, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 3, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 4, 5, 6, 7, 8, 9.
Images per class:

• 0: 87
• 1: 92
• 10: 138
• 11: 156
• 12: 117
• 13: 169
• 14: 175
• 15: 150
• 16: 110
• 17: 73
• 18: 68
• 19: 93
• 2: 150
• 20: 72
• 21: 61
• 22: 238
• 23: 187
• 24: 78
• 25: 61
• 26: 100
• 27: 98
• 28: 50
• 29: 141
• 3: 71
• 30: 114
• 31: 79
• 32: 68
• 33: 133
• 34: 88
• 35: 130
• 36: 90
• 37: 147
• 38: 146
• 39: 135
• 4: 101
• 5: 66
• 6: 116
• 7: 101
• 8: 133
• 9: 126

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

Citation

@article{li2026ct,
  title={CT-PestNet: A novel crop pest classification model based on cross-scale feature distillation enhancement and vision transformer with local token interaction},
  author={Li, Youming and Cao, Weilin and Zhang, Liqiang},
  journal={PLOS One},
  volume={21},
  pages={e0356061},
  year={2026},
  publisher={Public Library of Science}
}

The dataset itself can be cited as:

Cao, W. (2026). D0 dataset (Version 1) [Dataset]. figshare. https://doi.org/10.6084/M9.FIGSHARE.31768975.V1

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