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# Dataset Card for Fondant's free to use images
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Changelog](#changelog)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [How to use it](#how-to-use-it)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
- [Terms of Use for Dataset](#terms-of-use-for-the-dataset)
## Dataset Desricption
- **Homepage:** https://www.fondant.ai/
- **Repository:** https://github.com/ml6team/fondant
- **Paper:** N/A
- **Leaderboard:** N/A
- **Point of Contact:** [email protected]
## Changelog
|Release|Description|
|-|-|
|v1.0| Initial release of the [TODO:dataset name]
## Dataset Summary
[Dataset name] contains 25 million image URLs available for use under [Creative Commons](https://creativecommons.org/) license obtained from the [Common Crawl web corpus](https://commoncrawl.org/). The dataset was created as part of [Fondant](https://fondant.ai), a open-source framework for building composable data preparation pipelines for training (and fine-tuning) foundation models.
## Supported Tasks and Leaderboards
## How to use it
```python
from datasets import load_dataset
# full dataset
ds = load_dataset("fondantai/cc-25m")
# dataset streaming (will only download the data as needed)
ds = load_dataset("fondantai/cc-25m", streaming=True)
print(next(iter(dataset))) #TODO: add int ids?
```
### Utilizing the dataset in a fondant pipeline
We have prepared a sample fondant pipeline that reduces the dataset to PNG files and subsequently
downloads the images.
To execute the pipeline locally, you must have [docker compose](https://docs.docker.com/compose/) installed on your local
system.
Furthermore, you will need to install Fondant by running:
```
pip install fondant[pipelines]
```
Afterward, you can clone the GitHub repository, navigate to the `examples/pipelines/filter-cc-25m`, and initiate the
pipeline by executing:
```bash
fondant run pipeline --local
```
To visually inspect the results quickly, you can use:
```bash
fondant explore --base_path ./data
```
## Dataset Structure
### Data Instances
Each data instance corresponds to one image. The URL of the image is in the `image_url` feature, and other features (`alt_text`, `webpage_url`, etc) provide some metadata. Note that images have been deduplicated only based on their URLs and not embeddings.
### Data Fields
- `image_url` (string): image url to download the image
- `alt_text` (string): alternative text of the image
- `webpage_url` (string): webpage source of the image
- `license_type` (string): creative commons licence type of the image
- `license_location` (string): location of the license on the webpage
- `surt_url` (string): sort friendly image url with top level domain as the prefix
## Data Splits
The dataset has no splits and all data is loaded as a [TODO: check split name - train?] split by default. If you want to setup a custom train-test split beware that the dataset may contain duplicates which can cause leakage into the test split.
## Dataset Creation
### Curation Rationale
[TODO: insert intro from FAQ doc]
### Source Data
#### Initial Data Collection and Normalization
##### License detection
#### Who are the source language producers?
### Personal and Sensitive Information
The released dataset may contain sensitive information such as names, emails and addresses that have previously been published to the Internet. In the event that the dataset contains personal information, researchers should only use public, non-personal information in support of conducting and publishing their [open-access](https://en.wikipedia.org/wiki/Open_access) research. Personal information should not be used for spamming purposes, including sending unsolicited emails or selling of personal information. Complaints, removal requests, and "do not contact" requests can be sent to [email protected].
The PII filtering pipeline for this dataset is still a work in progress. Researchers that wish to contribute to the anonymization pipeline of the project can join [here](https://github.com/ml6team/fondant/tree/main#-contributing).
### Opting out of [dataset name]
We are giving the public the ability to have their image removed from the dataset upon request. The process for submitting and enacting removal requests will keep evolving throughout the project as we receive feedback and build up more data governance tools.
If you'd like to have your data removed from the dataset, [contact us](mailto:[email protected]).
## Considerations for Using the Data
### Discussion of Biases
### Other Known Limitations
## Additional Information
### Dataset Curators
1. Sharon Grundmann, ML6, [email protected]
2. Robbe Sneyders, ML6, [email protected]
3. Matthias Richter, ML6, [email protected]
### Licensing Information
[Dataset name] is a collection of images with various Creative Commons licenses. Any use of all or part of the images gathered in [dataset name] must abide by the terms of the original licenses, including attribution clauses when relevant. We facilitate this by providing provenance information for each data point.
The list of Creative Commons license types included in the dataset can be found [here](https://creativecommons.org/about/cclicenses/).
### Citation Information
```
[TODO]
```
### Contributions
[More Information Needed]
## Terms of Use for the [Dataset] |