Datasets:

Project-AgML
/

orange_leaf_HLB_classification

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': HLB
            '1': healthy
  splits:
    - name: train
      num_bytes: 1191138744
      num_examples: 324
  download_size: 1191169096
  dataset_size: 1191138744
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - n<1K

Orange Leaf Hlb Classification

This dataset contains RGB images of orange leaves captured in a laboratory setting using multiple smartphone models. It is designed for computer vision research focused on detecting Huanglongbing disease and differentiating diseased leaves from non-diseased ones. The dataset contains 324 images across 2 classes: HLB, healthy.
Images per class:

HLB: 195
healthy: 129

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

Citation

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