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from __future__ import annotations |
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import copy |
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import numpy as np |
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from lib_controlnet import external_code, global_state |
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from lib_controlnet.external_code import ControlNetUnit |
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from modules import scripts |
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from modules.processing import StableDiffusionProcessing |
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from .common import cn_model_regex |
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controlnet_exists = True |
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controlnet_type = "forge" |
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def find_script(p: StableDiffusionProcessing, script_title: str) -> scripts.Script: |
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script = next((s for s in p.scripts.scripts if s.title() == script_title), None) |
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if not script: |
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msg = f"Script not found: {script_title!r}" |
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raise RuntimeError(msg) |
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return script |
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def add_forge_script_to_adetailer_run( |
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p: StableDiffusionProcessing, script_title: str, script_args: list |
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): |
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p.scripts = copy.copy(scripts.scripts_img2img) |
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p.scripts.alwayson_scripts = [] |
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p.script_args_value = [] |
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script = copy.copy(find_script(p, script_title)) |
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script.args_from = len(p.script_args_value) |
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script.args_to = len(p.script_args_value) + len(script_args) |
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p.scripts.alwayson_scripts.append(script) |
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p.script_args_value.extend(script_args) |
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class ControlNetExt: |
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def __init__(self): |
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self.cn_available = False |
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self.external_cn = external_code |
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def init_controlnet(self): |
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self.cn_available = True |
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def update_scripts_args( |
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self, |
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p, |
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model: str, |
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module: str | None, |
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weight: float, |
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guidance_start: float, |
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guidance_end: float, |
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): |
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if (not self.cn_available) or model == "None": |
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return |
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image = np.asarray(p.init_images[0]) |
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mask = np.full_like(image, fill_value=255) |
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cnet_image = {"image": image, "mask": mask} |
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pres = external_code.pixel_perfect_resolution( |
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image, |
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target_H=p.height, |
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target_W=p.width, |
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resize_mode=external_code.resize_mode_from_value(p.resize_mode), |
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) |
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add_forge_script_to_adetailer_run( |
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p, |
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"ControlNet", |
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[ |
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ControlNetUnit( |
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enabled=True, |
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image=cnet_image, |
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model=model, |
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module=module, |
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weight=weight, |
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guidance_start=guidance_start, |
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guidance_end=guidance_end, |
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processor_res=pres, |
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) |
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], |
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) |
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def get_cn_models() -> list[str]: |
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models = global_state.get_all_controlnet_names() |
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return [m for m in models if cn_model_regex.search(m)] |
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