Datasets:

SalmaneExploring
/

pad-ufes-20

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 246, in _split_generators
                  raise ValueError(
              ValueError: `file_name`, `*_file_name`, `file_names` or `*_file_names` must be present as dictionary key in metadata files
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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PAD-UFES-20

This dataset repository mirrors PAD-UFES-20 for reproducible teledermatology experiments in mlops-teledermatology.

PAD-UFES-20 contains smartphone clinical images of skin lesions plus tabular metadata. The dataset includes 2,298 images from 1,373 patients and 1,641 skin lesions. The labels used by this project are:

ACK: Actinic keratosis
BCC: Basal cell carcinoma
MEL: Melanoma
NEV: Nevus
SCC: Squamous cell carcinoma, including Bowen's disease/SCC in situ
SEK: Seborrheic keratosis

Source And License

Original dataset:

Pacheco, A. G. C. et al. PAD-UFES-20: a skin lesion dataset composed of patient data and clinical images collected from smartphones. Data in Brief, 32, 106221, 2020.
Mendeley Data: https://data.mendeley.com/datasets/zr7vgbcyr2
Kaggle mirror: https://www.kaggle.com/datasets/mahdavi1202/skin-cancer

The Kaggle mirror lists the license as Creative Commons Attribution 4.0 International (CC BY 4.0). Keep this attribution and cite the original paper when using the data.

Intended Use

This mirror supports research and education around image-based skin lesion classification, model evaluation, and MLOps reproducibility.

This dataset and any models trained from it are not medical devices and should not be used for autonomous diagnosis. In this project, predictions are framed as triage support for clinician review.

Repository Layout

The project downloader accepts either extracted images or ZIP archives. The preferred Hugging Face layout is:

metadata.csv
all_images/
  imgs_part_1/*.png
  imgs_part_2/*.png
  imgs_part_3/*.png
splits/
  train.csv
  val.csv
  test.csv
  label_mapping.json
  class_weights.json
  preprocessing_summary.json

If you upload the original archives instead, this layout also works:

metadata.csv
images/
  imgs_part_1.zip
  imgs_part_2.zip
  imgs_part_3.zip

Project Split Protocol

The mlops-teledermatology project regenerates patient-safe train, validation, and test manifests with:

python -m src.data.make_image_splits

The split algorithm groups by patient_id to avoid patient leakage and keeps portable image_rel_path values for Colab/Hugging Face workflows.

Limitations

Labels are imbalanced, with melanoma especially rare.
Several clinical metadata columns contain missing or unknown values.
Some classes are biopsy-proven for all samples while others include clinical diagnoses, so biopsed should not be used as a model feature in this project.
The images come from smartphone acquisition and vary substantially in resolution, lighting, and focus.

Citation

@article{pacheco2020padufes20,
  title = {PAD-UFES-20: A skin lesion dataset composed of patient data and clinical images collected from smartphones},
  author = {Pacheco, Andre G. C. and Lima, Gustavo R. and Salomao, Amanda S. and Krohling, Breno and Biral, Igor P. and de Angelo, Gabriel G. and Alves Jr., Fabio C. R. and Esgario, Jose G. M. and Simora, Alana C. and Castro, Pedro B. C. and Rodrigues, Filipe B. and Frasson, Paulo H. L. and Krohling, Renato A.},
  journal = {Data in Brief},
  volume = {32},
  pages = {106221},
  year = {2020}
}

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