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