import gradio as gr
import numpy as np
import time

def fake_diffusion(input_img, steps):
    # for i in range(steps):
    #     time.sleep(1)
    #     image = np.random.random((600, 600, 3))
    #     yield image
    image = np.ones((1000,1000,3), np.uint8)
    image[:] = [255, 124, 0]
    # yield input_img
    return image


demo = gr.Interface(fake_diffusion, inputs=[gr.Image(type="filepath"), gr.Slider(1, 10, 3)], outputs="image")

if __name__ == "__main__":
    demo.launch()