Datasets:
beans

Task Categories: image-classification
Languages: English
Multilinguality: monolingual
Size Categories: 1K<n<10K
Language Creators: expert-generated
Annotations Creators: expert-generated
Source Datasets: original
Licenses: mit
Dataset Preview
Go to dataset viewer
image_file_path (string)image (image)labels (class label)
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End of preview (truncated to 100 rows)

Dataset Card for Beans

Dataset Summary

Beans leaf dataset with images of diseased and health leaves.

Supported Tasks and Leaderboards

  • image-classification: Based on a leaf image, the goal of this task is to predict the disease type (Angular Leaf Spot and Bean Rust), if any.

Languages

English

Dataset Structure

Data Instances

A sample from the training set is provided below:

{
    'image_file_path': '/root/.cache/huggingface/datasets/downloads/extracted/0aaa78294d4bf5114f58547e48d91b7826649919505379a167decb629aa92b0a/train/bean_rust/bean_rust_train.109.jpg',
    'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=500x500 at 0x16BAA72A4A8>,
    'labels': 1
}

Data Fields

The data instances have the following fields:

  • image_file_path: a string filepath to an image.
  • image: A PIL.Image.Image object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0].
  • labels: an int classification label.

Class Label Mappings:

{
  "angular_leaf_spot": 0,
  "bean_rust": 1,
  "healthy": 2,
}

Data Splits

train validation test
# of examples 1034 133 128

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

@ONLINE {beansdata,
    author="Makerere AI Lab",
    title="Bean disease dataset",
    month="January",
    year="2020",
    url="https://github.com/AI-Lab-Makerere/ibean/"
}

Contributions

Thanks to @nateraw for adding this dataset.

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Models trained or fine-tuned on beans