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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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import re |
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import openai |
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from cairosvg import svg2png |
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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 app_ip2p import create_demo as create_demo_ip2p |
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from app_lineart import create_demo as create_demo_lineart |
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from app_mlsd import create_demo as create_demo_mlsd |
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from app_normal import create_demo as create_demo_normal |
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from app_openpose import create_demo as create_demo_openpose |
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from app_scribble import create_demo as create_demo_scribble |
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from app_scribble_interactive import create_demo as create_demo_scribble_interactive |
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from app_segmentation import create_demo as create_demo_segmentation |
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from app_shuffle import create_demo as create_demo_shuffle |
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from app_softedge import create_demo as create_demo_softedge |
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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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DESCRIPTION = "# ControlNet v1.1" |
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if not torch.cuda.is_available(): |
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DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>" |
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model = Model(base_model_id=DEFAULT_MODEL_ID, task_name="Canny") |
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def gpt_control(apikey, prompt): |
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openai.api_key = apikey |
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messages = [{"role": "system", "content": "You are an SVG expert with years of experience and multiple contributions to the SVG project. Based on the prompt and the description, please generate the corresponding SVG code."}, |
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{"role": "user", "content": f"""Provide only the shell command without any explanations. |
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The current objective is below. Reply with the SVG code only: |
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OBJECTIVE: {prompt} |
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YOUR SVG CODE: |
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"""}] |
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completion = openai.ChatCompletion.create( |
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model = "gpt-4", |
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messages = messages |
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) |
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chat_response = completion.choices[0].message.content |
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code = re.findall('<.*>', chat_response) |
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code_new = '\n'.join(code) |
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svg_code = f""" |
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{code_new} |
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""" |
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svg2png(bytestring=svg_code,write_to='output.png') |
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return 'output.png' |
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with gr.Blocks(css="style.css") as demo: |
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gr.HTML("<center>" |
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"<h1>🌁🪄🌃 - ControlNet with GPT-4</h1>" |
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"</center>") |
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gr.Markdown("## <center>🌟 Born to Create: Controllable Text-to-Image Generation with GPT-4</center>") |
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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.Tab("GPT-4 Control"): |
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with gr.Row(): |
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with gr.Column(): |
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inp1 = gr.Textbox(label="OpenAI API Key", type="password") |
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inp2 = gr.Textbox(label="Position Prompt (as simple as possible)") |
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btn1 = gr.Button("GPT-4 Control", variant="primary") |
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with gr.Column(): |
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out1 = gr.Image(label="Output Image", type="pil", interactive=True) |
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btn1.click(gpt_control, [inp1, inp2], [out1]) |
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with gr.Tabs(): |
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with gr.TabItem("Canny"): |
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create_demo_canny(model.process_canny) |
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with gr.TabItem("MLSD"): |
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create_demo_mlsd(model.process_mlsd) |
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with gr.TabItem("Scribble"): |
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create_demo_scribble(model.process_scribble) |
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with gr.TabItem("Scribble Interactive"): |
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create_demo_scribble_interactive(model.process_scribble_interactive) |
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with gr.TabItem("SoftEdge"): |
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create_demo_softedge(model.process_softedge) |
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with gr.TabItem("OpenPose"): |
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create_demo_openpose(model.process_openpose) |
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with gr.TabItem("Segmentation"): |
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create_demo_segmentation(model.process_segmentation) |
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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("Normal map"): |
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create_demo_normal(model.process_normal) |
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with gr.TabItem("Lineart"): |
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create_demo_lineart(model.process_lineart) |
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with gr.TabItem("Content Shuffle"): |
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create_demo_shuffle(model.process_shuffle) |
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with gr.TabItem("Instruct Pix2Pix"): |
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create_demo_ip2p(model.process_ip2p) |
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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("Change base model", interactive=ALLOW_CHANGING_BASE_MODEL) |
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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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