[data request] <ISIC 2019>

• Name of dataset: ISIC 2019
• URL of dataset: https://challenge2019.isic-archive.com/data.html
• License of dataset: Creative Commons Attribution-NonCommercial 4.0 International License
• Short description of dataset and use case(s): For the ISIC 2019 grand challenge, the International Skin Imaging foundation released a data set containing 25,331 dermoscopic images that characterize 8 different types of skin cancers. Each image has a ground truth classification of Melanoma, Melanocytic nevus, Basal cell carcinoma, Actinic keratosis, Benign keratosis, Dermatofibroma, Vascular lesion, Squamous cell carcinoma, or None of the others. There is additional metadata for most, but not all images. This metadata includes information on patient age, patient sex, general anatomic site of dermoscopic image, and common lesion identifier. This dataset could be used to train image classification networks to identify the most common types of skin cancer from dermoscopic images

Folks who would also like to see this dataset in tensorflow/datasets, please thumbs-up so the developers can know which requests to prioritize.

And if you'd like to contribute the dataset (thank you!), see our guide to adding a dataset.

Start with docs/add_dataset.md, then inspect the ISIC 2019 data page linked in the issue for access, metadata, and licensing details. Follow the dataset contribution guide to determine the required TFDS changes; done means the ISIC 2019 dataset is added with its stated classifications and available metadata.