Multilabel-Portrait-18K

Multilabel-Portrait-18K is a multi-label portrait classification dataset designed to analyze and categorize different styles of portrait images. It supports classification into the following four portrait types:

• 0 — Anime Portrait
• 1 — Cartoon Portrait
• 2 — Real Portrait
• 3 — Sketch Portrait

This dataset is ideal for training and evaluating machine learning models in the domain of portrait-style classification. The goal is to enable accurate recognition of artistic and real-world portraits for applications such as image generation, enhancement, style transfer, and content moderation.

Use Cases

• Multi-label classification for style recognition
• Pretraining or fine-tuning portrait classifiers
• Improving filters and sorting in creative AI applications
• Enhancing deepfake detection via portrait-style understanding
• Style-transfer or portrait enhancement tools

Dataset Details

• Total Samples: 18,000 portrait images
• Labels: Multi-label format (each image may have more than one label)
• Label Schema:
  • 0: Anime Portrait [4,444]
  • 1: Cartoon Portrait [4,444]
  • 2: Real Portrait [4,444]
  • 3: Sketch Portrait [4,444]

Format

The dataset is typically provided in either:

• A directory structure grouped by label
• Or a .csv / .json file containing filename and labels fields

Example (.csv):

filename,label
portrait_001.jpg,"[0, 3]"
portrait_002.jpg,"[2]"
portrait_003.jpg,"[1, 2]"