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from typing import Any |
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import gradio as gr |
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from backend.models.lcmdiffusion_setting import DiffusionTask |
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from context import Context |
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from models.interface_types import InterfaceType |
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from frontend.utils import is_reshape_required |
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from constants import DEVICE |
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from state import get_settings |
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from concurrent.futures import ThreadPoolExecutor |
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app_settings = get_settings() |
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context = Context(InterfaceType.WEBUI) |
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previous_width = 0 |
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previous_height = 0 |
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previous_model_id = "" |
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previous_num_of_images = 0 |
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def generate_image_to_image( |
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prompt, |
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negative_prompt, |
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init_image, |
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strength, |
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) -> Any: |
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global previous_height, previous_width, previous_model_id, previous_num_of_images, app_settings |
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w, h = init_image.size |
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newW = app_settings.settings.lcm_diffusion_setting.image_width |
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newH = int(h * newW / w) |
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img = init_image.resize((newW, newH)) |
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print("新图",newH,newW) |
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app_settings.settings.lcm_diffusion_setting.prompt = prompt |
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app_settings.settings.lcm_diffusion_setting.negative_prompt = negative_prompt |
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app_settings.settings.lcm_diffusion_setting.init_image = img |
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app_settings.settings.lcm_diffusion_setting.strength = strength |
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app_settings.settings.lcm_diffusion_setting.diffusion_task = ( |
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DiffusionTask.image_to_image.value |
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) |
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model_id = app_settings.settings.lcm_diffusion_setting.openvino_lcm_model_id |
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reshape = False |
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app_settings.settings.lcm_diffusion_setting.image_height=newH |
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image_width = app_settings.settings.lcm_diffusion_setting.image_width |
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image_height = app_settings.settings.lcm_diffusion_setting.image_height |
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num_images = app_settings.settings.lcm_diffusion_setting.number_of_images |
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if app_settings.settings.lcm_diffusion_setting.use_openvino: |
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reshape = is_reshape_required( |
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previous_width, |
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image_width, |
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previous_height, |
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image_height, |
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previous_model_id, |
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model_id, |
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previous_num_of_images, |
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num_images, |
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) |
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with ThreadPoolExecutor(max_workers=1) as executor: |
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future = executor.submit( |
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context.generate_text_to_image, |
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app_settings.settings, |
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reshape, |
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DEVICE, |
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) |
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images = future.result() |
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previous_width = image_width |
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previous_height = image_height |
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previous_model_id = model_id |
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previous_num_of_images = num_images |
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return images |
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def get_image_to_image_ui() -> None: |
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with gr.Blocks(): |
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with gr.Row(): |
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with gr.Column(): |
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input_image = gr.Image(label="Init image", type="pil") |
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with gr.Row(): |
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prompt = gr.Textbox( |
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show_label=False, |
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lines=3, |
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placeholder="A fantasy landscape", |
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container=False, |
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) |
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generate_btn = gr.Button( |
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"Generate", |
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elem_id="generate_button", |
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scale=0, |
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) |
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negative_prompt = gr.Textbox( |
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label="Negative prompt (Works in LCM-LoRA mode, set guidance > 1.0):", |
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lines=1, |
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placeholder="", |
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) |
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strength = gr.Slider( |
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0.1, |
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1, |
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value=app_settings.settings.lcm_diffusion_setting.strength, |
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step=0.01, |
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label="Strength", |
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) |
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input_params = [ |
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prompt, |
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negative_prompt, |
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input_image, |
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strength, |
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] |
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with gr.Column(): |
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output = gr.Gallery( |
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label="Generated images", |
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show_label=True, |
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elem_id="gallery", |
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columns=2, |
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height=512, |
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) |
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generate_btn.click( |
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fn=generate_image_to_image, |
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inputs=input_params, |
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outputs=output, |
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) |
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