diff --git a/index.html b/index.html index de72447..8499606 100644 --- a/index.html +++ b/index.html @@ -1,122 +1,266 @@ - - Wake Vision - + Wake Vision Dataset + -
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Wake Vision Dataset

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The Dataset

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Wake Vision is a large, high-quality binary image classifcation dataset for person detection:

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  • Over 6 million high-quality images
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  • Two training sets (Large & Quality)
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  • High quality validation and test sets
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Fine-Grain Benchmark Suite

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Wake Vision also incorporates a comprehensive fine-grained benchmark to assess fairness and robustness across:

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  • Perceived gender
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  • Perceived age
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  • Subject distance
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  • Lighting conditions
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  • Depictions (e.g., drawings, digital renderings)
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Access the Dataset

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Get started using the dataset from your preferred source:

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- Quickstart - arXiv - TensorFlow - Datasets - Hugging Face - Datasets - Raw - Dataset at Harvard Dataverse
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About

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- "Wake Vision" is a large, high-quality dataset featuring over 6 million images, significantly exceeding the scale and diversity of current tinyML datasets (100x). This dataset includes images with annotations of whether each image contains a person. Additionally, it incorporates a comprehensive fine-grained benchmark to assess fairness and robustness, covering perceived gender, perceived age, subject distance, lighting conditions, and depictions. -

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- The Wake Vision labels are derived from Open Image's annotations which are licensed by Google LLC under CC BY 4.0 license. The images are listed as having a CC BY 2.0 license. Note from Open Images: "while we tried to identify images that are licensed under a Creative Commons Attribution license, we make no representations or warranties regarding the license status of each image and you should verify the license for each image yourself." -

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Diverse Examples

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- Older Person -

Older Person

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About Wake Vision

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Wake Vision is a state-of-the-art person detection dataset specifically created for TinyML applications. It provides a comprehensive collection of high-quality images and precise annotations to train and evaluate machine learning models for efficient person detection on embedded and edge devices.

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Access The Dataset

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Key Features

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TinyML Focus

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TinyML relevant usescase and tractable task.

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- Near Person -

Near Person

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Two Training Sets

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Ideal foundation for data-centric AI research

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- Bright Image -

Bright Image

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Diverse Scenarios

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Wide range of person detection use cases

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High-Quality Test and Val

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Manually labeled to ensure reliable evaluation

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Example Images

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Predominantly Female Person -

Predominantly Female Person

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Depicted Person -

Depicted Person

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Young Person -

Young Person

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Seeking Sponsors

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We are currently seeking sponsors to support the ongoing development and expansion of the Wake Vision - dataset. If you are interested in contributing and becoming a part of this innovative project, please - contact us for more information on how you can help shape the future of TinyML research.

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Contact Us

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If you have any questions or need further information, please feel free to reach out to us at the following - email addresses:

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License

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The Wake Vision labels are derived from Open Image's annotations which are licensed by Google LLC under CC BY 4.0 license. The images are listed as having a CC BY 2.0 license. Note from Open Images: "while we tried to identify images that are licensed under a Creative Commons Attribution license, we make no representations or warranties regarding the license status of each image and you should verify the license for each image yourself."

+ + + - \ No newline at end of file diff --git a/index_old.html b/index_old.html new file mode 100644 index 0000000..de72447 --- /dev/null +++ b/index_old.html @@ -0,0 +1,122 @@ + + + + + + + Wake Vision + + + + +
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Access the Dataset

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Get started using the dataset from your preferred source:

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+ Quickstart + arXiv + TensorFlow + Datasets + Hugging Face + Datasets + Raw + Dataset at Harvard Dataverse +
+
+
+

About

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+ "Wake Vision" is a large, high-quality dataset featuring over 6 million images, significantly exceeding the scale and diversity of current tinyML datasets (100x). This dataset includes images with annotations of whether each image contains a person. Additionally, it incorporates a comprehensive fine-grained benchmark to assess fairness and robustness, covering perceived gender, perceived age, subject distance, lighting conditions, and depictions. +

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+ The Wake Vision labels are derived from Open Image's annotations which are licensed by Google LLC under CC BY 4.0 license. The images are listed as having a CC BY 2.0 license. Note from Open Images: "while we tried to identify images that are licensed under a Creative Commons Attribution license, we make no representations or warranties regarding the license status of each image and you should verify the license for each image yourself." +

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Diverse Examples

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+ Older Person +

Older Person

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+ Near Person +

Near Person

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+ Bright Image +

Bright Image

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+ Predominantly Female Person +

Predominantly Female Person

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+ Depicted Person +

Depicted Person

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+ Young Person +

Young Person

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Seeking Sponsors

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We are currently seeking sponsors to support the ongoing development and expansion of the Wake Vision + dataset. If you are interested in contributing and becoming a part of this innovative project, please + contact us for more information on how you can help shape the future of TinyML research.

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Contact Us

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If you have any questions or need further information, please feel free to reach out to us at the following + email addresses:

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