Datasets ⭐
CACD Dataset
Load the CACD dataset in Python fast with one line of code. CACD has 160,000 images of 2,000 celebrities. Stream CACD while training in PyTorch & TensorFlow.
Visualization of CACD dataset on the Activeloop Platform

CACD dataset

What is CACD Dataset?

The Cross-Age Celebrity Dataset (CACD) has 163,446 images from 2,000 celebrities. The dataset allows you to estimate the age of a celebrity on a given image as you can subtract the birth year of the individual from the year the photo was taken in. The images in the CACD dataset were collected with search engines that used celebrity names and the years 2004 through 2013 as keywords.

Download CACD Dataset in Python

Instead of downloading the CACD dataset in Python, you can effortlessly load it in Python via our open-source package Hub with just one line of code.

Load CACD Dataset Training Subset in Python

import hub
ds = hub.load('hub://activeloop/cacd')

CACD Dataset Structure

CACD Data Fields

  • images: tensor containing the image of the celebrity's face.
  • keypoints: tensor to represent facial points.

CACD Data Splits

How to use CACD Dataset with PyTorch and TensorFlow in Python

Train a model on CACD dataset with PyTorch in Python

Let's use Hub's built-in PyTorch one-line dataloader to connect the data to the compute:
dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)

Train a model on CACD dataset with TensorFlow in Python

dataloader = ds.tensorflow()

Additional Information about CACD Dataset

CACD Dataset Description

CACD Dataset Curators

Bor-Chun Chen, Chu-Song Chen, Winston H. Hsu

CACD Dataset Licensing Information

Hub users may have access to a variety of publicly available datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets. It is your responsibility to determine whether you have permission to use the datasets under their license.
If you're a dataset owner and do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thank you for your contribution to the ML community!

CACD Dataset Citation Information

Author = {Bor-Chun Chen and Chu-Song Chen and Winston H. Hsu},
Booktitle = {Proceedings of the European Conference on Computer Vision ({ECCV})},
Title = {Cross-Age Reference Coding for Age-Invariant Face Recognition and Retrieval},
Year = {2014}

CACD Dataset FAQs

What is the CACD dataset for Python?

The Cross-Age Celebrity Dataset (CACD) contains 163,446 pictures of 2,000 celebrities. The images were obtained from the Internet. The dataset is often used for cross-age face recognition and retrieval.
How to download the CACD dataset in Python?
You can load CACD dataset fast with one line of code using the open-source package Activeloop Hub in Python. See detailed instructions on how to load CACD dataset training subset in Python.

How can I use the CACD dataset in PyTorch or TensorFlow?

You can stream the CACD dataset while training a model in PyTorch or TensorFlow with one line of code using the open-source package Activeloop Hub in Python. See detailed instructions on training a model on the CACD dataset with PyTorch or training a model on the CACD dataset with TensorFlow in Python.