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--- |
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pipeline_tag: image-to-text |
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tags: |
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- image-captioning |
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languages: |
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- en |
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license: bsd-3-clause |
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--- |
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```python |
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import requests |
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from PIL import Image |
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from transformers import BlipProcessor, BlipForConditionalGeneration |
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processor = BlipProcessor.from_pretrained("Revrse/icon-captioning-model") |
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model = BlipForConditionalGeneration.from_pretrained("Revrse/icon-captioning-model") |
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img_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/demo.jpg' |
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raw_image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB') |
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# conditional image captioning |
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text = "a photography of" |
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inputs = processor(raw_image, text, return_tensors="pt") |
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out = model.generate(**inputs) |
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print(processor.decode(out[0], skip_special_tokens=True)) |
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# unconditional image captioning |
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inputs = processor(raw_image, return_tensors="pt") |
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out = model.generate(**inputs) |
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print(processor.decode(out[0], skip_special_tokens=True)) |
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``` |
