LFPW Dataset

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Visualization of the LFPW train Dataset in the Deep Lake UI

LFPW dataset

What is LFPW Dataset?

The Labeled Face Parts-in-the-Wild (LFPW) dataset consists of 1,432 faces gathered from images acquired from the web using simple text queries on sites such as google.com, flickr.com, and yahoo.com. The LFPW dataset was used to showcase a novel approach to localizing parts in photos of human faces. Each image was labeled by three Amazon MTurk workers, with 29 fiducial points included in the dataset.

Download LFPW Dataset in Python

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

Load LFPW Dataset Training Subset in Python

				
					import deeplake
ds = deeplake.load("hub://activeloop/LFPW-train")

Load LFPW Dataset Testing Subset in Python

				
					import deeplake
ds = deeplake.load("hub://activeloop/LFPW-test")

LFPW Dataset Structure

LFPW Data Fields

images: tensor containing the face image.
keypoints: tensor to identify various key points from the face

LFPW Data Splits

The LFPW dataset training set is composed of 808.
The LFPW dataset training set is composed of 224.

How to use LFPW Dataset with PyTorch and TensorFlow in Python

Train a model on the LFPW 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 the LFPW dataset with TensorFlow in Python

				
					dataloader = ds.tensorflow()

Additional Information about LFPW Dataset

LFPW Dataset Description

Homepage: https://neerajkumar.org/databases/lfpw/
Paper: “Localizing Parts of Faces Using a Consensus of Exemplars,”
Peter N. Belhumeur, David W. Jacobs, David J. Kriegman, Neeraj Kumar,
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
June 2011.
Point of Contact: N/A

LFPW Dataset Curators

Peter N. Belhumeur, David W. Jacobs, David J. Kriegman, Neeraj Kumar

LFPW 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!

LFPW Dataset Citation Information

				
					@inproceedings{,
  title = {Localizing Parts of Faces Using a Consensus of Exemplars},
  author = {Peter N. Belhumeur, David W. Jacobs, David J. Kriegman, Neeraj Kumar},
  booktitle = {Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
June 2011.},
  year = {2011} 
}

LFPW Dataset FAQs

What is the LFPW dataset for Python?

The Labeled Face Parts-in-the-Wild (LFPW) dataset comprises 1,432 faces assembled from pictures downloaded by querying search engines like Google, Yahoo, and Flickr.

What is the LFPW dataset used for?

This dataset is great for training and testing models for face detection, particularly for recognizing facial attributes such as finding people with brown hair, smiling, or wearing glasses. Images cover large pose variations, background clutter, and diverse people, supported by a large number of images and rich annotations.

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

You can stream the LFPW 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 how to train a model on the LFPW dataset with PyTorch in Python or train a model on the LFPW dataset with TensorFlow in Python.