Spaces:
Runtime error
Runtime error
| from huggingface_hub import from_pretrained_keras | |
| from keras_cv import models | |
| import gradio as gr | |
| import tensorflow as tf | |
| # load keras model | |
| resolution = 512 | |
| dreambooth_model = models.StableDiffusion( | |
| img_width=resolution, img_height=resolution, jit_compile=True, | |
| ) | |
| loaded_diffusion_model = from_pretrained_keras("keras-dreambooth/dreambooth_diffusion_minercraft") | |
| dreambooth_model._diffusion_model = loaded_diffusion_model | |
| # generate images | |
| def inference(prompt, negative_prompt, num_imgs_to_gen, num_steps, guidance_scale): | |
| generated_images = dreambooth_model.text_to_image( | |
| prompt, | |
| negative_prompt=negative_prompt, | |
| batch_size=num_imgs_to_gen, | |
| num_steps=num_steps, | |
| unconditional_guidance_scale=guidance_scale, | |
| ) | |
| return generated_images | |
| # pass function, input type for prompt, the output for multiple images | |
| gr.Interface( | |
| inference, [ | |
| gr.Textbox(label="Positive Prompt", value="a fishing village under a cherry blossom forest at sunset in mrf style"), | |
| gr.Textbox(label="Negative Prompt", value="bad anatomy, soft blurry"), | |
| gr.Slider(label='Number of gen image', minimum=1, maximum=4, value=2, step=1), | |
| gr.Slider(label="Inference Steps",value=50), | |
| gr.Number(label='Guidance scale', value=7.5), | |
| ], [ | |
| gr.Gallery(show_label=False), | |
| ], | |
| title="Keras Dreambooth - Minecraft Style Demo 🤖", | |
| description = "This model has been fine tuned to learn the concept of Minecraft. To use this demo, you should have {mrf style} in the input", | |
| ).queue().launch(debug=True) |