import gradio as gr
import os.path

import torch
import cv2
import numpy as np
from PIL import Image

def output(image_path):
    pil_image = Image.open(image_path).convert("RGB")
    image = np.array(pil_image)[:, :, [2, 1, 0]]
    output_path = 'output'
    caption = 'person . mask'
    flag = False
    save_image_path = os.path.join(output_path,os.path.split(image_path)[-1])
    return save_image_path

with gr.Blocks() as demo:
    gr.Markdown("<h1><center>Demo</center></h1>")
    img_obj = gr.Image(value ='image/test.jpg',type = "filepath",label='object_img')
    btn = gr.Button("Submit",variant="primary")
    img_output = gr.Image(type = "filepath",label='output_img')
    btn.click(fn=output,inputs=[img_obj],
    outputs=[img_output],
    )

demo.launch(share=True)