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# Written On: 10 Feb 2025
# Last Updaate: 10 Feb 2025
#from transformers.utils import logging
#logging.set_verbosity_error()
#import warnings
#warnings.filterwarnings("ignore",
# message="Using the model-agnostic default `max_length`")
import gradio as gr
from transformers import pipeline
pipe = pipeline("image-to-text",
model="Salesforce/blip-image-captioning-base")
def launch(input):
out = pipe(input)
return out[0]['generated_text']
iface = gr.Interface(launch,
inputs=gr.Image(type='pil'),
outputs="text")
iface.launch(share=True)
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