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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+
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+ # Face-Age-10K Dataset
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+
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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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+
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+ ## Dataset Details
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+
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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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+
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+ * `train`: 9,165 images
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+
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+ ## Labels
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+
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+ The dataset includes 8 age group classes:
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+
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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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+
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+ Each image is labeled with one of the above age categories.
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+
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+ ## Usage
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+
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+ You can load this dataset using the Hugging Face `datasets` library:
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ dataset = load_dataset("prithivMLmods/Face-Age-10K")
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+ ```
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+
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+ To access individual samples:
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+
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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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+ ```