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import gradio as gr | |
from transformers import pipeline | |
# Rename 'text' to 'image' | |
def do_action(image): | |
# Use the blip model | |
pipe = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large") | |
result = pipe(image) | |
return result[0]['generated_text'] | |
# input image, output text | |
# can't use inputs="image" | |
# instead use inputs=gr.Image(type='pil') | |
iface = gr.Interface(fn=do_action, inputs=gr.Image(type='pil'), outputs="text") | |
iface.launch() |