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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")
stable_prompt_list = [
"a photo of sshh shoe",
]
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
)
tf.keras.backend.clear_session()
return generated_images
def keras_stable_diffusion_app():
with gr.Blocks():
with gr.Row():
with gr.Column():
keras_text2image_model_path = "ashishtanwer/shoe"
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
)
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