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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 generate_caption(image): | |
inputs = processor(image, return_tensors="pt") | |
outputs = model.generate(**inputs) | |
caption = processor.decode(outputs[0], skip_special_tokens=True) | |
return caption | |
interface = gr.Interface( | |
fn=generate_caption, | |
inputs=gr.Image(type="pil"), | |
outputs="text", | |
title="Image-to-Text Captioning", | |
description="Upload an image to generate a caption!" | |
) | |
interface.launch() |