Datasets:

Project-AgML
/

LeLePhid_classification

dataset_info:
  features:
    - name: image
      dtype: image
    - name: mask
      dtype: image
  splits:
    - name: train
      num_bytes: 25331768
      num_examples: 665
  download_size: 25359634
  dataset_size: 25331768
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-segmentation
size_categories:
  - n<1K

Lelephid Classification

This dataset provides real RGB images of aphid-infested lemon leaves captured in field conditions in Junín, Ecuador. Collected using a handheld smartphone camera during the December to May period, it offers a practical resource for developing semantic segmentation models focused on agricultural disease detection. The dataset contains 665 images with pixel-level mask annotations.

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

Citation

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The dataset itself can be cited as:

Parraga-Alava, J. (2021). LeLePhid: An Images Dataset for Aphids Detection and Infestation Severity on Lemons Leaf [Dataset]. Mendeley Data. https://doi.org/10.17632/TNDHS2ZNG4.1

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