app.py

# import gradio as gr
# import numpy as np


# def gennerateImage(input_array,eps):
#     eps = eps / 100
#     mask = np.random.random(input_array.shape)
#     mask = mask * 2 - 1 # 将mask的值转换为-1到1之间
#     noise_img = (input_array * (1 + mask * eps)).astype(np.uint8) % 255
#     return noise_img

# demo = gr.Interface(
#     gennerateImage, 
#     inputs=[
#         gr.Image(),
#         gr.Slider(1, 10, 3)
#     ],
#     outputs="image"
#     )

# demo.launch()

import gradio as gr
import numpy as np
import time

# define core fn, which returns a generator {steps} times before returning the image
def my_generator(steps):
    for i in range(steps):
        time.sleep(1)
        yield i
    yield steps


demo = gr.Interface(my_generator, inputs=gr.Slider(1, 10, 3), outputs="number")
 
# define queue - required for generators
demo.queue()

demo.launch()