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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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language: |
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- en |
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tags: |
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- age |
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- 10,000 |
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- image |
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- video |
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- art |
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- synthetic |
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- image-classification |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Face-Age-10K Dataset |
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The **Face-Age-10K** dataset consists of over 9,000 facial images annotated with age group labels. It is designed for training machine learning models to perform **age classification** from facial features. |
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## Dataset Details |
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* **Total Images**: 9,165 |
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* **Image Size**: 200x200 pixels |
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* **Format**: Parquet |
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* **Modality**: Image |
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* **Split**: |
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* `train`: 9,165 images |
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## Labels |
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The dataset includes 8 age group classes: |
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```python |
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labels_list = [ |
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'age 01-10', |
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'age 11-20', |
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'age 21-30', |
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'age 31-40', |
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'age 41-55', |
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'age 56-65', |
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'age 66-80', |
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'age 80 +' |
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] |
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``` |
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Each image is labeled with one of the above age categories. |
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## Usage |
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You can load this dataset using the Hugging Face `datasets` library: |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("prithivMLmods/Face-Age-10K") |
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``` |
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To access individual samples: |
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```python |
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sample = dataset["train"][0] |
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image = sample["image"] |
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label = sample["label"] |
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``` |
