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from stable_diffusion_tf.stable_diffusion import StableDiffusion as StableDiffusionPy | |
import gradio as gr | |
from tensorflow import keras | |
keras.mixed_precision.set_global_policy("float32") | |
# load keras model | |
resolution=512 | |
sd_dreambooth_model_1=StableDiffusionPy(resolution, resolution, download_weights=False, jit_compile=True) | |
sd_dreambooth_model_1.load_weights_from_pytorch_ckpt("riffusion-model-v1.ckpt") | |
sd_dreambooth_model_1.diffusion_model.load_weights("/dreambooth_riffusion_model_currulao_v1") | |
def generate_images(prompt: str, num_steps: int, unconditional_guidance_scale: int, temperature: int): | |
generated_img = sd_dreambooth_model_1.generate( | |
prompt, | |
num_steps=num_steps, | |
unconditional_guidance_scale=unconditional_guidance_scale, | |
temperature=temperature, | |
batch_size=1, | |
) | |
return generated_img[0] | |
# pass function, input type for prompt, the output for multiple images | |
gr.Interface( | |
title="Keras Dreambooth Riffusion-Currulao", | |
description="""This SD model has been fine-tuned from Riffusion to generate Currulao spectrograms. Currulao is a traditional Afro-Colombian music and dance genre, characterized by its rhythmic beats, call-and-response singing, and lively percussion instruments, that holds significant cultural and social importance in Colombia, particularly in the Pacific coast region, as a celebration of African heritage and community identity. | |
To generate the concept, use the phrase 'a $currulao song' in your prompt. | |
""", | |
fn=generate_images, | |
inputs=[ | |
gr.Textbox(label="Prompt", value="a $currulao song, lo-fi"), | |
gr.Slider(label="Inference steps", value=50), | |
gr.Slider(label="Guidance scale", value=7.5, maximum=15, minimum=0, step=0.5), | |
gr.Slider(label='Temperature', value=1, maximum=1.5, minimum=0, step=0.1), | |
], | |
outputs=[ | |
gr.Gallery(show_label=False).style(grid=(1,2)), | |
], | |
examples=[["a $currulao song", "low quality, deformed, dark", 2, 50, 7.5]], | |
).queue().launch(debug=True) |