Datasets:
Tasks:
Image Feature Extraction
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
License:
Update README.md
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README.md
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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:** cc-by-4.0
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### Dataset Sources
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<!-- Provide the basic links for the dataset. -->
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the dataset is intended to be used. -->
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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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### Source Data
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#### Data Collection and Processing
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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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#### Annotation process
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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 Needed]
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**APA:**
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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 [optional]
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[More Information Needed]
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## Dataset Card Authors [optional]
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## Dataset Card
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- **Curated by:** Jacob Marks
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- **Language(s) (NLP):** en
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- **License:** cc-by-4.0
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### Dataset Sources
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- **Demo:** https://try.fiftyone.ai/datasets/emojis/samples
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## Dataset Creation
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### Curation Rationale
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Emojis sit at the intersection between textual and visual, providing a fascinating test-bed for exploring multimodal search and reranking techniques. This dataset was constructed to facilitate these experiments. For connected projects, check out:
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- [Emoji Search CLI Library](https://github.com/jacobmarks/emoji_search)
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- [Semantic Emoji Search Plugin for FiftyOne](https://github.com/jacobmarks/emoji-search-plugin)
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### Source Data
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Samples in this dataset were constructed from rows in the Kaggle [Full Emoji Image Dataset](https://www.kaggle.com/datasets/subinium/emojiimage-dataset)
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#### Data Collection and Processing
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The base64-encoded images in the original csv were upscaled by 10x using [Real-ESRGAN](https://replicate.com/nightmareai/real-esrgan).
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OpenAI's CLIP-VIT-B/32 model was used to embed these images (vision encoder), the emoji names (text encoder), and the unicode sequences (text encoder). These embeddings were used to construct [Brain Runs](https://docs.voxel51.com/user_guide/brain.html) for performing similarity and semantic searches, as well as visualizing the structure of the dataset using UMAP dimensionality reduction.
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## Dataset Card Authors
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[Jacob Marks](https://huggingface.co/jamarks)
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