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| from huggingface_hub import from_pretrained_keras | |
| from keras_cv import models | |
| from tensorflow import keras | |
| import tensorflow as tf | |
| import gradio as gr | |
| keras.mixed_precision.set_global_policy("mixed_float16") | |
| keras_model_list = [ | |
| "keras-dreambooth/keras_diffusion_lowpoly_world", | |
| ] | |
| stable_prompt_list = [ | |
| "a photo of lowpoly_world", | |
| ] | |
| stable_negative_prompt_list = [ | |
| "bad, ugly", | |
| "deformed" | |
| ] | |
| def keras_stable_diffusion( | |
| model_path:str, | |
| prompt:str, | |
| negative_prompt:str, | |
| guidance_scale:int, | |
| num_inference_step:int, | |
| height:int, | |
| width:int, | |
| ): | |
| sd_dreambooth_model = models.StableDiffusion( | |
| img_width=height, | |
| img_height=width | |
| ) | |
| db_diffusion_model = from_pretrained_keras(model_path) | |
| sd_dreambooth_model._diffusion_model = db_diffusion_model | |
| generated_images = sd_dreambooth_model.text_to_image( | |
| prompt=prompt, | |
| negative_prompt=negative_prompt, | |
| num_steps=num_inference_step, | |
| unconditional_guidance_scale=guidance_scale | |
| ) | |
| return generated_images | |
| def keras_stable_diffusion_app(): | |
| with gr.Blocks(): | |
| with gr.Row(): | |
| with gr.Column(): | |
| keras_text2image_model_path = gr.Dropdown( | |
| choices=keras_model_list, | |
| value=keras_model_list[0], | |
| label='Text-Image Model Id' | |
| ) | |
| keras_text2image_prompt = gr.Textbox( | |
| lines=1, | |
| value=stable_prompt_list[0], | |
| label='Prompt' | |
| ) | |
| keras_text2image_negative_prompt = gr.Textbox( | |
| lines=1, | |
| value=stable_negative_prompt_list[0], | |
| label='Negative Prompt' | |
| ) | |
| with gr.Accordion("Advanced Options", open=False): | |
| keras_text2image_guidance_scale = gr.Slider( | |
| minimum=0.1, | |
| maximum=15, | |
| step=0.1, | |
| value=7.5, | |
| label='Guidance Scale' | |
| ) | |
| keras_text2image_num_inference_step = gr.Slider( | |
| minimum=1, | |
| maximum=100, | |
| step=1, | |
| value=50, | |
| label='Num Inference Step' | |
| ) | |
| keras_text2image_height = gr.Slider( | |
| minimum=128, | |
| maximum=1280, | |
| step=32, | |
| value=512, | |
| label='Image Height' | |
| ) | |
| keras_text2image_width = gr.Slider( | |
| minimum=128, | |
| maximum=1280, | |
| step=32, | |
| value=512, | |
| label='Image Height' | |
| ) | |
| keras_text2image_predict = gr.Button(value='Generator') | |
| with gr.Column(): | |
| output_image = gr.Gallery(label='Output') | |
| keras_text2image_predict.click( | |
| fn=keras_stable_diffusion, | |
| inputs=[ | |
| keras_text2image_model_path, | |
| keras_text2image_prompt, | |
| keras_text2image_negative_prompt, | |
| keras_text2image_guidance_scale, | |
| keras_text2image_num_inference_step, | |
| keras_text2image_height, | |
| keras_text2image_width | |
| ], | |
| outputs=output_image | |
| ) | |