
prithivMLmods/facial-age-detection
Image Classification
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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.
Total Images: 9,165
Image Size: 200x200 pixels
Format: Parquet
Modality: Image
Split:
train
: 9,165 imagesThe dataset includes 8 age group classes:
labels_list = [
'age 01-10',
'age 11-20',
'age 21-30',
'age 31-40',
'age 41-55',
'age 56-65',
'age 66-80',
'age 80 +'
]
Each image is labeled with one of the above age categories.
You can load this dataset using the Hugging Face datasets
library:
from datasets import load_dataset
dataset = load_dataset("prithivMLmods/Face-Age-10K")
To access individual samples:
sample = dataset["train"][0]
image = sample["image"]
label = sample["label"]