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alfabill commited on
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Update app.py

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  1. app.py +1 -1
app.py CHANGED
@@ -208,7 +208,7 @@ with gr.Blocks(css=css) as demo:
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  gr.Markdown("We introduce TR0N, a simple and efficient method to add any type of conditioning to pre-trained generative models. For this demo, we add two types of conditioning to a StyleGAN2 model pre-trained on images of human faces. First, we add text-conditioning to turn StyleGAN2 into a text-to-face model. Second, we add image semantic conditioning to StyleGAN2 to enable face-to-face interpolation. For more details and results on many other generative models, please refer to our paper linked above.")
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  with gr.Tab("Text-to-face generation") as text_to_face_generation_demo:
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- text_to_face_generation_input = gr.Textbox(label="Enter your prompt", placeholder="e.g. A man with a beard and glasses", max_lines=1)
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  text_to_face_generation_button = gr.Button("Generate")
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  text_to_face_generation_output = gr.Image(label="Generated image", elem_id="image-gen")
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  text_to_face_generation_examples = gr.Examples(examples=examples_text, fn=text_to_face_generate, inputs=text_to_face_generation_input, outputs=text_to_face_generation_output)
 
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  gr.Markdown("We introduce TR0N, a simple and efficient method to add any type of conditioning to pre-trained generative models. For this demo, we add two types of conditioning to a StyleGAN2 model pre-trained on images of human faces. First, we add text-conditioning to turn StyleGAN2 into a text-to-face model. Second, we add image semantic conditioning to StyleGAN2 to enable face-to-face interpolation. For more details and results on many other generative models, please refer to our paper linked above.")
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  with gr.Tab("Text-to-face generation") as text_to_face_generation_demo:
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+ text_to_face_generation_input = gr.Textbox(label="Enter your prompt", placeholder="e.g. A man with a beard and glasses", max_lines=1, api_name=prompt)
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  text_to_face_generation_button = gr.Button("Generate")
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  text_to_face_generation_output = gr.Image(label="Generated image", elem_id="image-gen")
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  text_to_face_generation_examples = gr.Examples(examples=examples_text, fn=text_to_face_generate, inputs=text_to_face_generation_input, outputs=text_to_face_generation_output)