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WIDER Face Dataset
Load WIDER Face dataset in Python fast. 32,203 facial images in 61 event classes. Stream WIDER Face dataset while training ML models in PyTorch & TensorFlow.
Visualization of Wider face dataset in Activeloop Platform

WIDER FACE dataset

What is WIDER FACE Dataset?

The WIDER FACE dataset is a face detection benchmark dataset. The images in this dataset were selected from the publicly available WIDER dataset. The WIDER FACE dataset was organized based on 61 event classes. For each event class, data such as training, validation, and testing were randomly selected from the WIDER dataset. Similar to MALF and Caltech datasets, the WIDER FACE does not release the bounding box ground truth for the test images.

Download WIDER FACE Dataset in Python

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

Load WIDER Face Dataset Training Subset in Python

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import hub
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ds = hub.load("hub://activeloop/wider-face-train")
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Load WIDER Face Dataset Validation Subset in Python

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import hub
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ds = hub.load("hub://activeloop/wider-face-val")
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Load WIDER Face Dataset Testing Subset in Python

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import hub
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ds = hub.load("hub://activeloop/wider-face-test")
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WIDER FACE Dataset Structure

WIDER Face Data Fields

  • image: tensor containing the face image.
  • boxes: tensor representing bounding boxes.
  • poses: tensor to distinguish types of poses.
  • expressions: tensor to distinguish between 'exaggerate_expression' and 'typical expression'.
  • illuminations: tensor to distinguish between 'normal illumination' and 'extreme illumination'.
  • occlusions: tensor to distinguish 'no occlusion', 'partial occlusion', and 'heavy occlusion'
  • validities: tensor checks if the image is valid or invalid.
  • blurs: tensor to distinguish 'clear', 'normal blur', 'heavy blur' images.

WIDER Face Data Splits

How to use WIDER Face Dataset with PyTorch and TensorFlow in Python

Train a model on WIDER Face dataset with PyTorch in Python

Let's use Hub's built-in PyTorch one-line dataloader to connect the data to the compute:
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dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)
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Train a model on WIDER Face dataset with TensorFlow in Python

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dataloader = ds.tensorflow()
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Additional Information about WIDER Face Dataset

WIDER Face Dataset Description

WIDER Face Dataset Curators

Yang, Shuo and Luo, Ping and Loy, Chen Change and Tang, Xiaoou

WIDER Face 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!

WIDER Face Dataset Citation Information

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@inproceedings{yang2016wider,
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Author = {Yang, Shuo and Luo, Ping and Loy, Chen Change and Tang, Xiaoou},
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Booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
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Title = {WIDER FACE: A Face Detection Benchmark},
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Year = {2016} }
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WIDER Face Dataset FAQs

What is the WIDER Face dataset for Python?

The WIDER FACE dataset is commonly used as a Face Detection Benchmark. it contains 32,203 images and labels 393,703 faces with a high degree of variability in scale, poses, and occlusion. The database is split into training (40%), validation (10%), and testing (50%) sets. The images in the dataset are divided into three levels (easy, medium, and hard) according to the difficulties of the image detection.
How to download the WIDER Face dataset in Python?
You can load WIDER Face dataset fast with one line of code using the open-source package Activeloop Hub in Python. See detailed instructions on how to load WIDER Face dataset training subset and testing subset in Python.

How can I use WIDER Face dataset in PyTorch or TensorFlow?

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