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IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition
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IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition

This work was accepted by CVPR 2019 as a oral paper.

The IP102 datset contains more than $75,000$ images belongs to $102$ categories. A natural long-tailed distribution presents on it. In addition, we annotate $19,000$ images with bounding boxes for object detection. The IP102 has a hierarchical taxonomy and the insect pests which mainly affect one specific agricultural product are grouped into the same upper-level category.

File Structure

The IP102 dataset can be downloaded from Baidu (pw: meg3) or Google. The folders are arranged like this:

|	├── Images.tar
|	├── train.txt
|	├── val.txt
|	├── test.txt
|	├── VOC2007
|	│   ├── Annotations.tar
|	│   ├── ImageSets/Main
|	│   │   ├── trainval.txt
|	│   │   ├── test.txt
|	│   ├── JPEGImages.tar

The index and name of each insect pest sub-class in the IP102 dataset can be found in supplementary material or classes.txt.

Additional Information

If you find the IP102 helpful, please cite it as

  title={IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition},
  author={Xiaoping Wu and Chi Zhan and Yukun Lai and Ming-Ming Cheng and Jufeng Yang},
  booktitle={IEEE CVPR},

ATTN: This dataset is free for academic usage. For other purposes, please contact Xiaoping Wu (

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