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tifa-benchmark
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promptcap-coco-vqa

Image-to-Text
Transformers
PyTorch
English
ofa
visual-question-answering
image-captioning
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yushihu commited on
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Update README.md

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@@ -27,7 +27,8 @@ pip install promptcap
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  ## Captioning Pipeline
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  Please follow the prompt format, which will give the best performance.
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- Generate a prompt-guided caption by following
 
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  ```python
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  import torch
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  from promptcap import PromptCap
@@ -85,7 +86,7 @@ question = "what year was this taken?"
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  image = "dvds.jpg"
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  ocr = "yip AE Mht juor 02/14/2012"
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- print(vqa_model.vqa(prompt, image, ocr=ocr))
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  ```
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  Because of the flexibility of Unifiedqa, PromptCap also supports multiple-choice VQA
 
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  ## Captioning Pipeline
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  Please follow the prompt format, which will give the best performance.
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+
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+ Generate a prompt-guided caption by following:
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  ```python
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  import torch
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  from promptcap import PromptCap
 
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  image = "dvds.jpg"
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  ocr = "yip AE Mht juor 02/14/2012"
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+ print(vqa_model.vqa(question, image, ocr=ocr))
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  ```
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  Because of the flexibility of Unifiedqa, PromptCap also supports multiple-choice VQA