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Update app.py
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import os
import io
import IPython.display
from PIL import Image
import base64
from transformers import pipeline
import gradio as gr
import warnings
warnings.filterwarnings("ignore")
task = "image-to-text"
model = "nlpconnect/vit-gpt2-image-captioning"
image_captioner = pipeline("image-to-text", model = model)
def captioner(image):
result = image_captioner(image)
return result[0]['generated_text']
gr.close_all()
demo = gr.Interface(fn=captioner,
inputs=[gr.Image(label="Upload image", type="pil")],
outputs=[gr.Textbox(label="Caption")],
title="Image Captioning with {model}",
description=f"Caption any image using the {model} model",
allow_flagging="never",
)
demo.launch()