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import gradio as gr
import spaces
import torch
from clip_slider_pipeline import CLIPSliderXL
from diffusers import StableDiffusionXLPipeline, EulerDiscreteScheduler
flash_pipe = StableDiffusionXLPipeline.from_pretrained("sd-community/sdxl-flash").to("cuda", torch.float16)
flash_pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)
clip_slider = CLIPSliderXL(flash_pipe, device=torch.device("cuda"))
@spaces.GPU
def generate(slider_x, slider_y, prompt, x_concept_1, x_concept_2, y_concept_1, y_concept_2):
# check if avg diff for directions need to be re-calculated
if not sorted(slider_x) == sorted([x_concept_1, x_concept_2]):
clip_slider.avg_diff = clip_slider.find_latent_direction(slider_x[0], slider_x[0])
x_concept_1, x_concept_2 = slider_x[0], slider_x[1]
if not sorted(slider_y) == sorted([y_concept_1, y_concept_2]):
clip_slider.avg_diff_2nd = clip_slider.find_latent_direction(slider_y[0], slider_y[0])
y_concept_1, y_concept_2 = slider_y[0], slider_y[1]
comma_concepts_x = ', '.join(slider_x)
comma_concepts_y = ', '.join(slider_y)
image = clip_slider(prompt, scale=0, scale_2nd=0, num_inference_steps=8)
return gr.update(label=comma_concepts_x, interactive=True),gr.update(label=comma_concepts_y, interactive=True), x_concept_1, x_concept_2, y_concept_1, y_concept_2, image
def update_x(x,y,prompt):
image = clip_slider(prompt, scale=x, scale_2nd=y, num_inference_steps=8)
return image
def update_y(x,y,prompt):
image = clip_slider(prompt, scale=x, scale_2nd=y, num_inference_steps=8)
return image
css = '''
#group {
position: relative;
width: 420px;
height: 420px;
margin-bottom: 20px;
background-color: white
}
#x {
position: absolute;
bottom: 0;
left: 25px;
width: 400px;
}
#y {
position: absolute;
bottom: 20px;
left: 67px;
width: 400px;
transform: rotate(-90deg);
transform-origin: left bottom;
}
#image_out{position:absolute; width: 80%; right: 10px; top: 40px}
'''
with gr.Blocks(css=css) as demo:
x_concept_1 = gr.State("")
x_concept_2 = gr.State("")
y_concept_1 = gr.State("")
y_concept_2 = gr.State("")
with gr.Row():
with gr.Column():
slider_x = gr.Dropdown(label="Slider X concept range", allow_custom_value=True, multiselect=True, max_choices=2)
slider_y = gr.Dropdown(label="Slider X concept range", allow_custom_value=True, multiselect=True, max_choices=2)
prompt = gr.Textbox(label="Prompt")
submit = gr.Button("Submit")
with gr.Group(elem_id="group"):
x = gr.Slider(minimum=-10, value=0, maximum=10, elem_id="x", interactive=False)
y = gr.Slider(minimum=-10, value=0, maximum=10, elem_id="y", interactive=False)
output_image = gr.Image(elem_id="image_out")
submit.click(fn=generate,
inputs=[slider_x, slider_y, prompt, x_concept_1, x_concept_2, y_concept_1, y_concept_2],
outputs=[x, y, x_concept_1, x_concept_2, y_concept_1, y_concept_2, output_image])
x.change(fn=update_x, inputs=[x,y, prompt], outputs=[output_image])
y.change(fn=update_y, inputs=[x,y, prompt], outputs=[output_image])
if __name__ == "__main__":
demo.launch() |