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---
license: apache-2.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
language:
- en
tags:
- Gender
- Classification
- Male
- Female
- art
- medical
---
# Realistic-Portrait-Gender-1024px
**Dataset Type:** Image Classification
**Task:** Gender Classification (Female vs. Male Portraits)
**Size:** \~3,200 images
**Image Resolution:** 1024px x 1024px
**License:** Apache 2.0
## Dataset Summary
The **Realistic-Portrait-Gender-1024px** dataset consists of high-resolution (1024px) realistic portraits labeled by perceived gender identity: `female` or `male`. It is designed for image classification tasks, particularly for training and evaluating gender classification models.
## Supported Tasks
* **Binary Gender Classification**
Predict whether a given portrait represents a male or female individual.
## Dataset Structure
| Feature | Type | Description |
| ------- | -------- | --------------------------------- |
| image | Image | RGB portrait image (1024x1024 px) |
| label | Category | `0 = female`, `1 = male` |
**Split:**
* `train`: Entire dataset is provided under a single training split.
## Example Usage
```python
from datasets import load_dataset
dataset = load_dataset("prithivMLmods/Realistic-Portrait-Gender-1024px")
image, label = dataset['train'][0]['image'], dataset['train'][0]['label']
```
## Labels
* `0` — female portrait
* `1` — male portrait
## License
This dataset is distributed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). |