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Create app.py
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app.py
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from huggingface_hub import from_pretrained_keras
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import keras_cv
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def generate_images(prompt: str, num_imgs_to_gen: int):
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"""
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This function is used to generate images using our fine-tuned keras dreambooth stable diffusion model.
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Args:
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prompt (str): The text input given by the user based on which images will be generated.
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num_imgs_to_gen (int): The number of images to be generated using given prompt.
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Returns:
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all_images (List): List of images that were generated using the model
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"""
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dreambooth_model = keras_cv.models.StableDiffusion(
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img_width=resolution, img_height=resolution, jit_compile=True,
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)
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loaded_diffusion_model = from_pretrained_keras("shivi/dreambooth_diffusion_model")
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dreambooth_model._diffusion_model = loaded_diffusion_model
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generated_img = dreambooth_model.text_to_image(
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prompt, batch_size=num_imgs_to_gen
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)
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return generated_img
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with gr.Blocks() as demo:
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gr.HTML("<h2 style=\"font-size: 2em; font-weight: bold\" align=\"center\">Keras Dreambooth - Pink Floyd Division Bell Demo</h2>")
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gr.Markdown("This model has been fine tuned to learn the concept of Division Bell from Pink Floyd's famous album `The Division Bell`")
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with gr.Row():
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with gr.Column():
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prompt = gr.Textbox(label="prompt")
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samples = gr.Slider(label="No. of Images",value=1)
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run = gr.Button(value="Run")
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with gr.Column():
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gallery = gr.Gallery(show_label=False)
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run.click(generate_images, inputs=[prompt,samples], outputs=gallery)
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gr.Examples([["A flower vase inspired by pink floyd division bell album cover", 1],
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["A pendant in the style of pink floyd division bell album cover",1],
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["A human skull inspired by pink floyd division bell album cover ",1],
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["picture of pink floyd division bell album cover with a starry night on Mars theme", 1]],
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[prompt,samples,model_choice], gallery, generate_images, cache_examples=True)
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gr.Markdown("Some fun examples I created while playing with the model:")
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gr.Makdown("![Example 1](sample_outputs/1.png)")
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demo.launch(debug=True)
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