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21 lines
463 B
Python
21 lines
463 B
Python
import gradio as gr
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import numpy as np
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import time
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def fake_diffusion(steps):
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for i 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 = np.ones((1000,1000,3), np.uint8)
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image[:] = [255, 124, 0]
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yield image
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demo = gr.Interface(fake_diffusion,
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inputs=gr.Slider(1, 10, 3, step=1),
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outputs="image")
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if __name__ == "__main__":
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demo.launch()
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