datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SCIN-Dermatology-Raw-Images
SCIN-Dermatology-Raw-Images
This dataset contains 6,517 patient-submitted photographs organized into 3,061 clinical cases of common skin diseases. The source images are curated from the public Google Skin Condition Image Network (SCIN) corpus, cleansed of quality and gradability conflicts, and paired with complete patient-reported demographics, clinical symptoms, and dermatologist gradings.
Dataset Structure
This repository follows the standard Hugging Face… See the full description on the dataset page: https://huggingface.co/datasets/HawkFranklin-Research/SCIN-Dermatology-Raw-Images.CleanPatrick
CleanPatrick: A Benchmark for Data Cleaning
Welcome to CleanPatrick, the first large-scale benchmark designed for data cleaning in the image domain.
Built on the Fitzpatrick17k dermatology dataset, CleanPatrick is a dataset for measuring the performance in detecting three major data quality issues:
off-topic samples, near-duplicates, and label errors.
Overview
CleanPatrick consists of dermatological images annotated with over 500,000 binary labels across three data… See the full description on the dataset page: https://huggingface.co/datasets/Digital-Dermatology/CleanPatrick.dermatology-dataset-acne-redness-and-bags-under-the-eyes
Skin Defects Dataset
The dataset contains images of individuals with various skin conditions: acne, skin redness, and bags under the eyes. Each person is represented by 3 images showcasing their specific skin issue. The dataset encompasses diverse demographics, age, ethnicities, and genders.
The dataset is created on the basis of Facial Skin Condition Dataset
Types of defects in the dataset: acne, skin redness & bags under the eyes
Acne photos: display different… See the full description on the dataset page: https://huggingface.co/datasets/UniqueData/dermatology-dataset-acne-redness-and-bags-under-the-eyes.