| # YFCC100M subset from OpenAI | |
| Subset of [YFCC100M](https://arxiv.org/abs/1503.01817) used by OpenAI for [CLIP](https://github.com/openai/CLIP/blob/main/data/yfcc100m.md), filtered to contain only the images that we could retrieve. | |
| | Split | train | validation | | |
| | --- | --- | --- | | |
| | Number of samples | 14,808,859 | 16,374 | | |
| | Size | 1.9 TB | 2.1 GB | | |
| Features: | |
| * from the original dataset: `title`, `description`, `photoid`, `uid`, `unickname`, `datetaken`, `dateuploaded`, `capturedevice`, `usertags`, `machinetags`, `longitude`, `latitude`, `accuracy`, `pageurl`, `downloadurl`, `licensename`, `licenseurl`, `serverid`, `farmid`, `secret`, `secretoriginal`, `ext`, `marker`, `key` | |
| * `img`: image content, can be loaded with `PIL.Image.open(io.BytesIO(item['img']))` | |
| * `title_clean` and `description_clean`: derived from `title` and `description` using `clean_text` function detailed below | |
| ```python | |
| def clean_text(text): | |
| # decode url | |
| text = urllib.parse.unquote_plus(text) | |
| # remove html tags | |
| text = re.sub('<[^<]+?>', '', text) | |
| # remove multiple spaces + "\r" + "\n" + "\t" | |
| text = " ".join(text.split()) | |
| return text | |
| ``` |