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import gradio as gr
# from PIL import Image
from transformers.utils import logging
from transformers import BlipForConditionalGeneration, AutoProcessor
logging.set_verbosity_error()
model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
def caption_image(image):
inputs = processor(image, return_tensors="pt")
out = model.generate(**inputs)
caption = processor.decode(out[0], skip_special_tokens=True)
return caption
gr.Interface(caption_image, gr.inputs.Image(), "text").launch()
# gr.Interface(caption_image, image_input, caption_output).launch()
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