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import os | |
os.system('python install.py') | |
import gradio as gr | |
from pipeline.run_pipeline import * | |
''' | |
时间优化 | |
并发优化 | |
''' | |
# from run import * | |
# ''' | |
# 把一些文件移动到此文件路径下 | |
# ''' | |
# text = "A person is cutting a birthday cake with two red candles that spell out \"21\". The surface of the cake is round, and there is a balloon in the room. The person is using a silver knife to cut the cake." | |
# image_path = "/newdisk3/wcx/val2014/COCO_val2014_000000297425.jpg" | |
pipeline = Pipeline(type="image-to-text", api_key="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") | |
# res,claim_list = pipeline.run(text=text, image_path=image_path,type="image-to-text") | |
# print(res) | |
def get_response(text, filepath, type): | |
res, claim_list = pipeline.run(text=text, image_path=filepath, type=type) | |
return claim_list, res | |
demo = gr.Interface( | |
fn=get_response, | |
inputs=[gr.Textbox(placeholder="Input I2T model's response or T2I model's prompt", label="text input"), gr.Image(type="filepath", label="image input"), gr.Radio(['image-to-text','text-to-image'], label='task type', value='image-to-text')], | |
outputs=[gr.Textbox(label="claim list"), gr.Textbox(label="detect results")], | |
) | |
demo.queue().launch(share=True) | |