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Datasets:
fondant-ai
/
datacomp-small-clip

Tasks:
Image-to-Text
Image-to-Image
Modalities:
Text
Formats:
parquet
Size:
10M - 100M
Tags:
images
CLIP
embeddings
FAISS
Libraries:
Datasets
Dask
Croissant
License:
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metadata
license: cc-by-4.0
configs:
  - config_name: embeddings
    data_files: data/*.parquet
  - config_name: id_mapping
    data_files: id_mapping/*.parquet
task_categories:
  - image-to-text
  - image-to-image
tags:
  - images
  - CLIP
  - embeddings
  - FAISS
size_categories:
  - 1M<n<10M

Dataset Card for fondant-ai/datacomp-small-clip

This is a dataset containing image urls and their CLIP embeddings, based on the datacomp_small dataset, and processed with fondant.

Dataset Details

Dataset Description

Large (image) datasets are often unwieldy to use due to their sheer size. Assume for instance that we would like to extract all the cat images from such a dataset. We would have to look at every image to classify if it's a cat image or not. And if we want to extract all the dog images next, we again need to look at every image.

Instead, we can look at every image once, and calculate a (CLIP) embedding representing its content. Combining these embeddings into an index, we can efficiently search through the dataset with a query, finding specific images, without having to look at each one.

CLIP index

This is what LAION did for their LAION-5b dataset, which made it possible to use, like we did in our ControlNet example. Unfortunately, the LAION-5b dataset and index have been taken offline (temporarily) and there aren't any alternatives. This is why we built an index for the Datacomp-12M dataset. While it is a lot smaller than LAION-5b, it should already enable a lot of use cases again, and can hopefully be the start towards building indices for more and larger datasets.

  • License: cc-by-4.0

Dataset Sources

Uses

We provide an example use case which uses the FAISS index of this dataset to create a dataset of interior design images, used for the fine-tuning of a ControlNet model:

Dataset Structure

The data repository is structured as follows:

  • data/: The dataset containing ids, urls, and CLIP embeddings
  • faiss: The faiss index
  • id_mapping/: The mapping of the faiss ids to the original urls

Terms and Conditions

Under no circumstances can Fondant be held liable by a third party for (i) the accuracy or correctness of the content, (ii) an alleged infringement of intellectual property rights or (iii) any other alleged claim, action, injunction or suit resulting from the publication or use of the dataset.

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