Datasets:
Update README.md
Browse files
README.md
CHANGED
|
@@ -11,4 +11,45 @@ tags:
|
|
| 11 |
- Realistic
|
| 12 |
- Sketch
|
| 13 |
- Portrait
|
| 14 |
-
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 11 |
- Realistic
|
| 12 |
- Sketch
|
| 13 |
- Portrait
|
| 14 |
+
---
|
| 15 |
+
|
| 16 |
+
# **Multilabel-Portrait-18K**
|
| 17 |
+
|
| 18 |
+
**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:
|
| 19 |
+
|
| 20 |
+
- **0** — Anime Portrait
|
| 21 |
+
- **1** — Cartoon Portrait
|
| 22 |
+
- **2** — Real Portrait
|
| 23 |
+
- **3** — Sketch Portrait
|
| 24 |
+
|
| 25 |
+
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.
|
| 26 |
+
|
| 27 |
+
## **Use Cases**
|
| 28 |
+
- Multi-label classification for style recognition
|
| 29 |
+
- Pretraining or fine-tuning portrait classifiers
|
| 30 |
+
- Improving filters and sorting in creative AI applications
|
| 31 |
+
- Enhancing deepfake detection via portrait-style understanding
|
| 32 |
+
- Style-transfer or portrait enhancement tools
|
| 33 |
+
|
| 34 |
+
## **Dataset Details**
|
| 35 |
+
- **Total Samples**: 18,000 portrait images
|
| 36 |
+
- **Labels**: Multi-label format (each image may have more than one label)
|
| 37 |
+
- **Label Schema**:
|
| 38 |
+
- `0`: Anime Portrait
|
| 39 |
+
- `1`: Cartoon Portrait
|
| 40 |
+
- `2`: Real Portrait
|
| 41 |
+
- `3`: Sketch Portrait
|
| 42 |
+
|
| 43 |
+
## **Format**
|
| 44 |
+
The dataset is typically provided in either:
|
| 45 |
+
- A directory structure grouped by label
|
| 46 |
+
- Or a `.csv` / `.json` file containing `filename` and `labels` fields
|
| 47 |
+
|
| 48 |
+
Example (`.csv`):
|
| 49 |
+
|
| 50 |
+
```csv
|
| 51 |
+
filename,label
|
| 52 |
+
portrait_001.jpg,"[0, 3]"
|
| 53 |
+
portrait_002.jpg,"[2]"
|
| 54 |
+
portrait_003.jpg,"[1, 2]"
|
| 55 |
+
```
|