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DAISEE Dataset
Load the DAISEE dataset fast with one line of code. 9068 video clips of 4 emotional states with different intensities. Stream DAISEE while training ML models.

DAiSEE dataset

What is DAiSEE Dataset?

The DAiSEE dataset is the first multi-label video classification dataset. It is made up of 9068 video snippets captured from 112 users. The videos recognize the user's state of boredom, confusion, engagement, and frustration. The dataset has four levels of labels (very low, low, high, and very high) for each of the affective states. The labels were crowd annotated and correlated with a gold standard annotation created using a team of expert psychologists.

Download DAiSEE Dataset in Python

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

Load DAISEE Dataset Training Subset in Python

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import hub
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ds = hub.load("hub://activeloop/daisee-train")
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Load DAISEE Dataset Testing Subset in Python

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import hub
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ds = hub.load("hub://activeloop/daisee-test")
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Load DAISEE Dataset Validation Subset in Python

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import hub
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ds = hub.load("hub://activeloop/daisee-validation")
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DAISEE Dataset Structure

DAISEE Data Fields

  • video: tensor representing video file.
  • boredom: tensor to classify boredom from very low to very high.
  • engagement: tensor to classify engagement from very low to very high.
  • confusion: tensor to classify confusion from very low to very high.
  • frustration: tensor to classify frustration from very low to very high.
  • gender: tensor to classify based on the gender of the speaker.

DAISEE Data Splits

How to use DAISEE Dataset with PyTorch and TensorFlow in Python

Train a model on DAISEE 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 DAISEE dataset with TensorFlow in Python

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dataloader = ds.tensorflow()
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Additional Information about DAISEE Dataset

DAISEE Dataset Description

ADAISEE Dataset Curators

Abhay Gupta, Arjun D'Cunha, Kamal Awasthi, Vineeth Balasubramanian

DAISEE 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!

DAISEE Dataset Citation Information

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@article{Gupta2016DAISEEDF,
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title={DAISEE: Dataset for Affective States in E-Learning Environments},
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author={Abhay Gupta and Richik Jaiswal and Sagar Adhikari and Vineeth N. Balasubramanian},
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journal={ArXiv},
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year={2016},
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volume={abs/1609.01885}
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}
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DAISEE Dataset FAQs

What is the DAISEE dataset for Python?

DAiSEE is a multi-label video classification dataset comprising 9,068 video clips from 112 people. It is a popular dataset for identifying various emotional states (boredom, confusion, engagement, and frustration) in real-life situations. The dataset was developed to provide a springboard for further research in the field of feature extraction and context-based inference.
How to download the DAISEE dataset in Python?
You can load DAISEE dataset fast with one line of code using the open-source package Activeloop Hub in Python. See detailed instructions on how to load DAISEE dataset training subset and testing subset in Python.

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

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