CACD Dataset

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Visualization of the CACD dataset in Deep Lake UI

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. 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 Deep Lake open-source with just one line of code

Load CACD Dataset Training Subset in Python

				
					import deeplake
ds = deeplake.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

The CACD dataset training set is composed of 163,446 images.

How to use CACD Dataset with PyTorch and TensorFlow in Python

Train a model on CACD dataset with PyTorch in Python

Let’s use Deep Lake 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

Homepage: https://bcsiriuschen.github.io/CARC/
Paper: Bor-Chun Chen, Chu-Song Chen, Winston H. Hsu. Cross-Age Reference Coding for Age-Invariant Face Recognition and Retrieval, ECCV 2014 [Pdf]
Point of Contact: [email protected]

CACD Dataset Curators

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

CACD Dataset Licensing information

Deep Lake 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

				
					@inproceedings{chen14cross,
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 Datasets 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 the CACD dataset fast with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to load the Load CACD dataset training subset in Python.

How can i use 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 Deep Lake 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.