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This is the PyTorch implementation of the <a href="https://arxiv.org/abs/2107.07651">BLIP paper</a>. The code has been tested on PyTorch 1.9 and 1.10.
Catalog:
- [x] Inference demo
- [ ] Inference demo
- [x] Pre-trained and finetuned checkpoints
- [x] Finetuning code for Image-Text Retrieval, Image Captioning, VQA, and NLVR2
- [x] Pre-training code
- [x] Download of bootstrapped image-text dataset
- [x] Download of bootstrapped image-text datasets
### Inference demo (Image Captioning and VQA):
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### Pre-trained checkpoints:
Num. pre-train images | BLIP w/ ViT-B | BLIP w/ ViT-B and CapFilt-L | BLIP w/ ViT-L
--- | --- | --- | ---
--- | :---: | :---: | :---:
14M | <a href="https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_14M.pth">Download</a>| - | -
129M | <a href="https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base.pth">Download</a>| <a href="https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model*_base.pth">Download</a> | <a href="https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_large.pth">Download</a>
### Finetuned checkpoints:
Task | BLIP w/ ViT-B | BLIP w/ ViT-B and CapFilt-L | BLIP w/ ViT-L
--- | :---: | :---: | :---:
Image-Text Retrieval (COCO) | <a href="https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_retrieval_coco.pth">Download</a>| - | <a href="https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_large_retrieval_coco.pth">Download</a>
Image-Text Retrieval (Flickr30k) | <a href="https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_retrieval_flickr.pth">Download</a>| - | <a href="https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_large_retrieval_flickr.pth">Download</a>
Image Captioning (COCO) | - | <a href="https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model*_base_caption.pth">Download</a>| <a href="https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_large_caption.pth">Download</a> |
VQA | <a href="https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_vqa.pth">Download</a>| - | -
NLVR2 | <a href="https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_nlvr.pth">Download</a>| - | -
### Image-Text Retrieval:
1. Download COCO or Flickr30k datasets from the original websites, and set 'image_root' in configs/retrieval_{dataset}.yaml accordingly.
2. To evaluate the finetuned BLIP model on COCO, run: