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from __future__ import annotations
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import gradio as gr
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import torch
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torch.jit.script = lambda f: f
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import spaces
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from app_canny import create_demo as create_demo_canny
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from app_depth import create_demo as create_demo_depth
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from model import Model
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from settings import ALLOW_CHANGING_BASE_MODEL, DEFAULT_MODEL_ID, SHOW_DUPLICATE_BUTTON
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from transformers.utils.hub import move_cache
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move_cache()
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DESCRIPTION = "ControlNet"
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if not torch.cuda.is_available():
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DESCRIPTION += "\n<p>Running on CPU.</p>"
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model = Model(base_model_id=DEFAULT_MODEL_ID, task_name="Canny")
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with gr.Blocks(css="style.css") as demo:
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gr.Markdown(DESCRIPTION)
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gr.DuplicateButton(
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value="Duplicate Space for private use",
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elem_id="duplicate-button",
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visible=SHOW_DUPLICATE_BUTTON,
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)
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with gr.Tabs():
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with gr.TabItem("Depth"):
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create_demo_depth(model.process_depth)
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with gr.TabItem("Canny"):
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create_demo_canny(model.process_canny)
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with gr.Accordion(label="Base model", open=False):
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with gr.Row():
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with gr.Column(scale=5):
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current_base_model = gr.Text(label="Current base model")
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with gr.Column(scale=1):
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check_base_model_button = gr.Button("Check current base model")
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with gr.Row():
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with gr.Column(scale=5):
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new_base_model_id = gr.Text(
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label="New base model",
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max_lines=1,
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placeholder="runwayml/stable-diffusion-v1-5",
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info="The base model must be compatible with Stable Diffusion v1.5.",
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interactive=ALLOW_CHANGING_BASE_MODEL,
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)
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with gr.Column(scale=1):
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change_base_model_button = gr.Button(
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"Change base model", interactive=ALLOW_CHANGING_BASE_MODEL
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)
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if not ALLOW_CHANGING_BASE_MODEL:
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gr.Markdown(
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"""The base model is not allowed to be changed in this Space so as not to slow down the demo, but it can be changed if you duplicate the Space."""
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)
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check_base_model_button.click(
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fn=lambda: model.base_model_id,
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outputs=current_base_model,
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queue=False,
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api_name="check_base_model",
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)
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gr.on(
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triggers=[new_base_model_id.submit, change_base_model_button.click],
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fn=model.set_base_model,
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inputs=new_base_model_id,
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outputs=current_base_model,
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api_name=False,
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)
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if __name__ == "__main__":
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demo.queue(max_size=20).launch()
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