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	| from huggingface_hub import from_pretrained_keras | |
| import keras_cv | |
| import gradio as gr | |
| from tensorflow import keras | |
| keras.mixed_precision.set_global_policy("mixed_float16") | |
| # load keras model | |
| resolution = 512 | |
| dreambooth_model = keras_cv.models.StableDiffusion( | |
| img_width=resolution, img_height=resolution, jit_compile=True, | |
| ) | |
| loaded_diffusion_model = from_pretrained_keras("keras-dreambooth/dreambooth-galaxy-mergers") | |
| dreambooth_model._diffusion_model = loaded_diffusion_model | |
| def generate_images(prompt: str, negative_prompt:str, num_imgs_to_gen: int, num_steps: int, ugs: int): | |
| generated_img = dreambooth_model.text_to_image( | |
| prompt, | |
| negative_prompt=negative_prompt, | |
| batch_size=num_imgs_to_gen, | |
| num_steps=num_steps, | |
| unconditional_guidance_scale=ugs, | |
| ) | |
| return generated_img | |
| with gr.Blocks() as demo: | |
| gr.Markdown(""" | |
| # Keras-Dreambooth Galaxy Mergers πͺπ€ | |
| This is a Keras Dreambooth model fine-tuned to images of galaxy mergers taken with the [Hubble Space Telescope](https://en.wikipedia.org/wiki/Hubble_Space_Telescope) (credit [ESA/Hubble](https://esahubble.org/images/)). | |
| The model, part of the [Keras Dreambooth Sprint](https://github.com/huggingface/community-events/tree/main/keras-dreambooth-sprint) trained by lposti, can be found in [keras-dreambooth/dreambooth-galaxy-mergers](https://huggingface.co/keras-dreambooth/dreambooth-galaxy-mergers). | |
| The model should be used with a prompt containing `sks galaxies merging`. A typical prompt for this model is `image of sks galaxies merging in space`. | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| prompt = gr.Textbox(lines=1, value="image of sks galaxies merging in space", label="Base Prompt") | |
| negative_prompt = gr.Textbox(lines=1, value="deformed", label="Negative Prompt") | |
| samples = gr.Slider(minimum=1, maximum=5, value=1, step=1, label="Number of Image") | |
| num_steps = gr.Slider(label="Inference Steps",value=40) | |
| ugs = gr.Slider(value=15, minimum=5, maximum=25, step=1, label="Unconditional Guidance Scale") | |
| run = gr.Button(value="Run") | |
| with gr.Column(): | |
| gallery = gr.Gallery(label="Outputs").style(grid=(1,2)) | |
| run.click(generate_images, inputs=[prompt,negative_prompt, samples, num_steps, ugs], outputs=gallery) | |
| gr.Examples([["image of sks galaxies merging in space, 8k, high quality","deformed, blurry, grain, artifacts, low quality", 1, 40, 12], | |
| ["painting of sks galaxies merging in van gogh style, 8k, high quality, trending on artstation","deformed, blurry, grain, artifacts, low quality", 1, 40, 12], | |
| ], | |
| [prompt,negative_prompt, samples,num_steps, ugs], gallery, generate_images) | |
| gr.Markdown(""" | |
| ## Output samples | |
| > image of sks galaxies merging in space | |
|  | |
| > painting of sks galaxies merging in van gogh style | |
|  | |
| ## Cosmic Hugs π€: an artistic rendition of galaxy collisions | |
|  | |
| """) | |
| demo.launch(debug=True) |