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task_ids: []
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pretty_name:
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tags:
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- fiftyone
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- image-classification
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- object-detection
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- video
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This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 11980
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## Installation
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If you haven'
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```bash
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# Load the dataset
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# Note: other available arguments include '
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dataset = fouh.load_from_hub("
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# Launch the App
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session = fo.launch_app(dataset)
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```
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# Dataset Card for WLASL
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![image/png](dataset_preview.gif)
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This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 11980 samples.
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## Installation
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# Load the dataset
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# Note: other available arguments include 'max_samples', etc
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dataset = fouh.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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- **Curated by:**
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Language(s) (NLP):** en
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- **License:** other
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### Dataset Sources
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<!-- Provide the basic links for the dataset. -->
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- **Repository:**
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- **Paper
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## Uses
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### Direct Use
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<!-- This section describes suitable use cases for the dataset. -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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[More Information Needed]
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## Dataset Structure
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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[More Information Needed]
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## Dataset Creation
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### Curation Rationale
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<!-- Motivation for the creation of this dataset. -->
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[More Information Needed]
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### Source Data
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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#### Data Collection and Processing
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<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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[More Information Needed]
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#### Who are the source data producers?
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<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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[More Information Needed]
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### Annotations [optional]
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<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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[More Information Needed]
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#### Who are the annotators?
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<!-- This section describes the people or systems who created the annotations. -->
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[More Information Needed]
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#### Personal and Sensitive Information
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<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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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 [optional]
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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 [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
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size_categories:
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- 10K<n<100K
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task_categories:
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- video-classification
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task_ids: []
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pretty_name: World Level American Sign Language
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tags:
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- fiftyone
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- video
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- activity-recognition
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- asl
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- sign-language
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dataset_summary: >
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This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 11980
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samples.
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## Installation
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If you haven't already, install FiftyOne:
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```bash
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# Load the dataset
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# Note: other available arguments include 'max_samples', etc
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dataset = fouh.load_from_hub("Voxel51/WLASL")
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# Launch the App
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session = fo.launch_app(dataset)
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```
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---
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# Dataset Card for WLASL
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![image/png](dataset_preview.gif)
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This is a [FiftyOne](https://github.com/voxel51/fiftyone) video dataset with 11980 samples.
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## Installation
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# Load the dataset
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# Note: other available arguments include 'max_samples', etc
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dataset = fouh.load_from_hub("Voxel51/WLASL")
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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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WLASL is the largest video dataset for Word-Level American Sign Language (ASL) recognition, which features 2,000 common different words in ASL. The authors hope WLASL will facilitate the research in sign language understanding and eventually benefit the communication between deaf and hearing communities.
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- **Curated by:** Dongxu Li and Hongdong Li
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- **Language(s) (NLP):** en
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- **License:** other
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### Dataset Sources
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<!-- Provide the basic links for the dataset. -->
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- **Repository:** https://github.com/dxli94/WLASL
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- **Paper:** https://arxiv.org/abs/1910.11006
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- **Homepage:** https://dxli94.github.io/WLASL/
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- **Demo:** https://try.fiftyone.ai/datasets/asl-dataset/samples
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## Uses
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All the WLASL data is intended for academic and computational use only. No commercial usage is allowed. Licensed under the [Computational Use of Data Agreement](https://github.com/microsoft/Computational-Use-of-Data-Agreement/releases/tag/v1.0) (C-UDA)
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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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```bibtex
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@misc{li2020wordlevel,
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title={Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison},
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author={Dongxu Li and Cristian Rodriguez Opazo and Xin Yu and Hongdong Li},
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year={2020},
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eprint={1910.11006},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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@inproceedings{li2020transferring,
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title={Transferring cross-domain knowledge for video sign language recognition},
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author={Li, Dongxu and Yu, Xin and Xu, Chenchen and Petersson, Lars and Li, Hongdong},
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booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
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pages={6205--6214},
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year={2020}
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}
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```
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## Dataset Card Authors
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[Jacob Marks](https://huggingface.co/jamarks)
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