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