Update app.py
Browse files
app.py
CHANGED
@@ -5,8 +5,7 @@ import gradio as gr
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generator = Text2Image(
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img_height=512,
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img_width=512,
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jit_compile=False
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)
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def txt2img(prompt, guide, steps, Temp):
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img = generator.generate(prompt,
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@@ -21,5 +20,5 @@ iface = gr.Interface(fn=txt2img, inputs=[
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gr.Textbox(label = 'Input Text Prompt'),
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gr.Slider(2, 20, value = 9, label = 'Guidence Scale'),
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gr.Slider(10, 100, value = 50, step = 1, label = 'Number of Iterations'),
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gr.Slider(.01, 100, value=1)], outputs = 'image',title='Stable Diffusion with Keras and TensorFlow CPU or GPU', description='Now Using Keras and TensorFlow with Stable Diffusion. This allows very complex image generation with less code footprint, and less text.')
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iface.launch()
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generator = Text2Image(
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img_height=512,
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img_width=512,
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jit_compile=False)
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def txt2img(prompt, guide, steps, Temp):
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img = generator.generate(prompt,
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gr.Textbox(label = 'Input Text Prompt'),
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gr.Slider(2, 20, value = 9, label = 'Guidence Scale'),
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gr.Slider(10, 100, value = 50, step = 1, label = 'Number of Iterations'),
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gr.Slider(.01, 100, value=1)], outputs = 'image',title='Stable Diffusion with Keras and TensorFlow CPU or GPU', description='Now Using Keras and TensorFlow with Stable Diffusion. This allows very complex image generation with less code footprint, and less text.', footer='About Keras: Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result as fast as possible is key to doing good research. https://keras.io/about/')
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iface.launch()
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