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# app.py
import gradio as gr
from transformers import BlipProcessor, BlipForConditionalGeneration
from PIL import Image
processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
def caption_image(image):
inputs = processor(images=image, return_tensors="pt")
out = model.generate(**inputs)
caption = processor.decode(out[0], skip_special_tokens=True)
return caption
gr.Interface(fn=caption_image, inputs=gr.Image(), outputs="text").launch()
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