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README.md
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# PMC-OA
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**News: We
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[中文文档](./README.zh.md)
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## Daraset Structure
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**PMC-OA** (seperated images, separated caption).
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- `train.jsonl`: metafile of train set
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- `valid.jsonl`: metafile of valid set
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- `test.jsonl`: metafile of test set
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- `images.zip`: images folder
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## Sample
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A row in `
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```python
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{
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"image": "PMC212319_Fig3_4.jpg",
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"caption": "A. Real time image of the translocation of ARF1-GFP to the plasma membrane ...",
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"pmcid": "PMC212319",
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"url_name": "1471-2121-4-13-3.jpg"
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}
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```
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- image: path to the image
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- caption: corresponding to the image
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- pmcid: source paper's PMCID of the image
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- url_name: image name in the web link
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# PMC-OA Dataset
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**News: We have released the PMC-OA dataset. You can choose the subset specifically.**
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[中文文档](./README.zh.md)
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## Daraset Structure
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**PMC-OA** (seperated images, separated caption).
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- `images.zip`: images folder
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- `pmc_oa.jsonl`: dataset file of pmc-oa
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- `pmc_oa_beta.jsonl`: dataset file of pmc-oa-beta
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~~- `train.jsonl`: metafile of train set~~
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~~- `valid.jsonl`: metafile of valid set~~
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~~- `test.jsonl`: metafile of test set~~
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The difference between PMC-OA & PMC-OA-Beta lies in the methods of processing captions.
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In PMC-OA, we utilize ChatGPT to help us divide compound captions into seperate ones.
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While PMC-OA-Beta keeps all the compound ones without division.
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## Sample
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A row in `pmc_oa.jsonl` is shown bellow,
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```python
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{
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"image": "PMC212319_Fig3_4.jpg",
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"caption": "A. Real time image of the translocation of ARF1-GFP to the plasma membrane ...",
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}
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```
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- image: path to the image
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- caption: corresponding to the image
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