Description:

This dataset contains augmented images of six different dermatological conditions. Each category includes 399 images, providing a balanced dataset ideal for training machine learning models, particularly in the field of medical image analysis.

Categories:

1. Acne: A common skin condition that occurs when hair follicles become clogged with oil and dead skin cells, leading to pimples, blackheads, or whiteheads.
2. Carcinoma: A type of skin cancer that begins in the basal or squamous cells. The images in this category may show various stages and forms of skin carcinoma.
3. Eczema: A condition that makes the skin red, inflamed, itchy, and sometimes results in blisters. The images depict different manifestations of eczema.
4. Keratosis: A skin condition characterized by rough, scaly patches on the skin caused by excessive growth of keratin. This category includes images of various types of keratosis, such as actinic keratosis.
5. Milia: Small, white, benign bumps that typically appear on the face, especially around the eyes and on the cheeks. The images show different instances of this condition.
6. Rosacea: A chronic skin condition that causes redness and visible blood vessels in your face. This category contains images depicting the typical characteristics of rosacea.

Dataset Details:

Total Images: 2,394
Images per Category: 399
Image Format: JPEG
Image Size: Variable.
Augmentation Techniques: The images have been augmented using techniques such as rotation, flipping, zooming, and brightness adjustment to enhance the diversity of the dataset and improve model generalization.