The Dataset
+Wake Vision is a large, high-quality binary image classifcation dataset for person detection:
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+
- Over 6 million high-quality images +
- Two training sets (Large & Quality) +
- High quality validation and test sets +
Fine-Grain Benchmark Suite
+Wake Vision also incorporates a comprehensive fine-grained benchmark to assess fairness and robustness across:
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- Perceived gender +
- Perceived age +
- Subject distance +
- Lighting conditions +
- Depictions (e.g., drawings, digital renderings) +
Access the Dataset
-Get started using the dataset from your preferred source:
- -About
-- "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. -
-- 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." -
- -Diverse Examples
-Older Person
+ +About Wake Vision
+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.
+ +Access The Dataset
+ + +Key Features
+TinyML Focus
+TinyML relevant usescase and tractable task.
Near Person
+Two Training Sets
+Ideal foundation for data-centric AI research
Bright Image
+Diverse Scenarios
+Wide range of person detection use cases
+High-Quality Test and Val
+Manually labeled to ensure reliable evaluation
Example Images
+Predominantly Female Person
Depicted Person
Young Person
Seeking Sponsors
-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.
- -Contact Us
-If you have any questions or need further information, please feel free to reach out to us at the following - email addresses:
--
-
- Email: emjn@dtu.dk -
- Email: cbanbury@g.harvard.edu -
License
+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 @@ + + + + + + +Access the Dataset
+Get started using the dataset from your preferred source:
+ +About
++ "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. +
++ 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." +
+ +Diverse Examples
+Older Person
+Near Person
+Bright Image
+Predominantly Female Person
+Depicted Person
+Young Person
+Seeking Sponsors
+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.
+ +Contact Us
+If you have any questions or need further information, please feel free to reach out to us at the following + email addresses:
+-
+
- Email: emjn@dtu.dk +
- Email: cbanbury@g.harvard.edu +