# 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)