#导入gradio
import gradio as gr
#导入transformers相关包
from transformers import *

# import webbrowser
# # 打开指定的URL
# webbrowser.open('http://127.0.0.1:7860')

#通过Interface加载pipeline并启动服务
gr.Interface.from_pipeline( pipeline("image-to-text",model="Salesforce/blip-image-captioning-base")).launch(share=True)

# import numpy as np
# import gradio as gr


# def flip_text(x):
#     return x[::-1]


# def flip_image(x):
#     return np.fliplr(x)


# with gr.Blocks() as demo:
#     gr.Markdown("Flip text or image files using this demo.")
#     with gr.Tab("Flip Text"):
#         text_input = gr.Textbox()
#         text_output = gr.Textbox()
#         text_button = gr.Button("Flip")
#     with gr.Tab("Flip Image"):
#         with gr.Row():
#             image_input = gr.Image()
#             image_output = gr.Image()
#         image_button = gr.Button("Flip")

#     with gr.Accordion("Open for More!"):
#         gr.Markdown("Look at me...")

#     text_button.click(flip_text, inputs=text_input, outputs=text_output)
#     image_button.click(flip_image, inputs=image_input, outputs=image_output)

# demo.launch(share=True)