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--- |
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license: apache-2.0 |
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task_categories: |
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- image-classification |
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size_categories: |
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- 10K<n<100K |
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tags: |
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- Anime |
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- Cartoon |
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- Realistic |
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- Sketch |
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- Portrait |
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- art |
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--- |
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# **Multilabel-Portrait-18K** |
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**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: |
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- **0** — Anime Portrait |
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- **1** — Cartoon Portrait |
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- **2** — Real Portrait |
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- **3** — Sketch Portrait |
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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. |
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## **Use Cases** |
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- Multi-label classification for style recognition |
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- Pretraining or fine-tuning portrait classifiers |
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- Improving filters and sorting in creative AI applications |
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- Enhancing deepfake detection via portrait-style understanding |
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- Style-transfer or portrait enhancement tools |
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## **Dataset Details** |
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- **Total Samples**: 18,000 portrait images |
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- **Labels**: Multi-label format (each image may have more than one label) |
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- **Label Schema**: |
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- `0`: Anime Portrait [4,444] |
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- `1`: Cartoon Portrait [4,444] |
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- `2`: Real Portrait [4,444] |
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- `3`: Sketch Portrait [4,444] |
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## **Format** |
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The dataset is typically provided in either: |
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- A directory structure grouped by label |
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- Or a `.csv` / `.json` file containing `filename` and `labels` fields |
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Example (`.csv`): |
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```csv |
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filename,label |
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portrait_001.jpg,"[0, 3]" |
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portrait_002.jpg,"[2]" |
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portrait_003.jpg,"[1, 2]" |
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``` |
