| import gradio as gr | |
| import numpy as np | |
| import time | |
| # define core fn, which returns a generator {steps} times before returning the image | |
| def fake_diffusion(steps): | |
| for _ in range(steps): | |
| time.sleep(1) | |
| image = np.random.random((600, 600, 3)) | |
| yield image | |
| image = "https://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg" | |
| yield image | |
| demo = gr.Interface(fake_diffusion, inputs=gr.Slider(1, 10, 3), outputs="image") | |
| # define queue - required for generators | |
| demo.queue() | |
| demo.launch() | |