Hair Type Dataset

Dataset Contents

• Total Images: Thousands of labeled images.
• Formats: JPEG and PNG, with standard dimensions.
• Annotations: Each image comes with metadata, including hair length, color, and style attributes.

Hair Type Categories

1. Straight Hair
   Features images of hair that is smooth, shiny, and lacks any curl or wave. Commonly seen in Asian and Caucasian ethnic groups, straight hair is often characterized by its sleekness and ease of styling.
2. Wavy Hair
   A category that includes hair with loose waves and slight bends. This type of hair can be seen across various ethnicities and serves as a middle ground between straight and curly.
3. Curly Hair
   Well-defined curls form this category. The dataset includes images of different curl patterns, from loose ringlets to tighter coils. This type of hair is commonly seen in people of diverse ethnic backgrounds.
4. Kinky Hair
   Kinky hair, often referred to as coily or Afro-textured, consists of very tight curls or coils. This hair type is predominantly associated with African heritage and is highly textured.
5. Dreadlocks
   While not a natural hair type, dreadlocks are a unique hairstyle formed through the matting and twisting of hair. The dataset includes a variety of dreadlock styles, offering valuable data for systems design to recognize unique hair formations.

Dataset Applications

• Beauty and Fashion Technology
  Enables virtual hair try-ons, personalized hairstyle suggestions, and product recommendations base on hair texture and type.
• Facial Recognition Systems
  Enhances accuracy in identifying individuals with diverse hair types by ensuring algorithms are train on inclusive data.
• Health and Dermatology Research
  Supports AI models that assess scalp health, hair conditions, and hair loss patterns across various hair types.

Diversity and Inclusivity

The Hair Type Dataset ensures representation from different ethnic groups and includes images of men, women, and children, making it one of the most diverse datasets for hair-related machine learning tasks. It offers detail annotations to improve the accuracy of hair type classification across a broad spectrum of individuals.