Datasets:
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---
license: apache-2.0
task_categories:
- image-classification
size_categories:
- 10K<n<100K
tags:
- Anime
- Cartoon
- Realistic
- Sketch
- Portrait
- art
---
# **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`):
```csv
filename,label
portrait_001.jpg,"[0, 3]"
portrait_002.jpg,"[2]"
portrait_003.jpg,"[1, 2]"
``` |