Datasets:
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README.md
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# Note: other available arguments include ''max_samples'', etc
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dataset = load_from_hub("
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# Launch the App
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# Load the dataset
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# Note: other available arguments include 'max_samples', etc
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dataset = load_from_hub("
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# Launch the App
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session = fo.launch_app(dataset)
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### Dataset Description
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<!-- Provide a longer summary of what this dataset is. -->
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- **License:** [More Information Needed]
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### Dataset Sources
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- **Demo [optional]:** [More Information Needed]
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## Uses
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## Dataset Structure
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[More Information Needed]
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## Dataset Creation
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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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## Citation
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Dataset Card Authors [optional]
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[More Information Needed]
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## Dataset Card Contact
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# Note: other available arguments include ''max_samples'', etc
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dataset = load_from_hub("voxel51/hand-keypoints")
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# Launch the App
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# Load the dataset
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# Note: other available arguments include 'max_samples', etc
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dataset = load_from_hub("voxel51/hand-keypoints")
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# Launch the App
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session = fo.launch_app(dataset)
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### Dataset Description
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- **Curated by:** Tomas Simon, Hanbyul Joo, Iain Matthews, Yaser Sheikh
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- **Funded by:** Carnegie Mellon University
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- **Shared by:** [Harpreet Sahota](https://huggingface.co/harpreetsahota), Hacker-in-Residence at Voxel51
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- **License:** [More Information Needed]
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### Dataset Sources
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As part of their research, the authors created a dataset by manually annotating two publicly available image sets: the MPII Human Pose dataset and images from the New Zealand Sign Language (NZSL) Exercises. To date, they collected annotations for 1300 hands on the MPII set and 1500 on NZSL. This combined dataset was split into a training set (2000 hands) and a testing set (800 hands)
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- **Paper:** https://arxiv.org/abs/1704.07809
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- **Demo:** http://domedb.perception.cs.cmu.edu/handdb.html
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## Uses
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## Dataset Structure
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```text
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Name: hand_keypoints
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Media type: image
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Num samples: 846
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Persistent: True
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Tags: []
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Sample fields:
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id: fiftyone.core.fields.ObjectIdField
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filepath: fiftyone.core.fields.StringField
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tags: fiftyone.core.fields.ListField(fiftyone.core.fields.StringField)
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metadata: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.metadata.ImageMetadata)
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created_at: fiftyone.core.fields.DateTimeField
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last_modified_at: fiftyone.core.fields.DateTimeField
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right_hand: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.labels.Keypoints)
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body: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.labels.Keypoints)
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left_hand: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.labels.Keypoints)
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```
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## Dataset Creation
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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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## Citation
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```bibtex
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@inproceedings{simon2017hand,
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author = {Tomas Simon and Hanbyul Joo and Iain Matthews and Yaser Sheikh},
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booktitle = {CVPR},
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title = {Hand Keypoint Detection in Single Images using Multiview Bootstrapping},
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year = {2017}
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}
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```
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