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https://github.com/comfyanonymous/ComfyUI.git
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[feat]switch to gpen
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333
custom_functions/ai_portrait_gpen_api.py
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333
custom_functions/ai_portrait_gpen_api.py
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import os
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import random
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import sys
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from typing import Sequence, Mapping, Any, Union
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import torch
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def get_value_at_index(obj: Union[Sequence, Mapping], index: int) -> Any:
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"""Returns the value at the given index of a sequence or mapping.
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If the object is a sequence (like list or string), returns the value at the given index.
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If the object is a mapping (like a dictionary), returns the value at the index-th key.
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Some return a dictionary, in these cases, we look for the "results" key
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Args:
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obj (Union[Sequence, Mapping]): The object to retrieve the value from.
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index (int): The index of the value to retrieve.
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Returns:
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Any: The value at the given index.
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Raises:
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IndexError: If the index is out of bounds for the object and the object is not a mapping.
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"""
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try:
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return obj[index]
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except KeyError:
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return obj["result"][index]
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def find_path(name: str, path: str = None) -> str:
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"""
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Recursively looks at parent folders starting from the given path until it finds the given name.
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Returns the path as a Path object if found, or None otherwise.
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"""
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# If no path is given, use the current working directory
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if path is None:
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# path = os.getcwd()
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path = os.path.dirname(__file__)
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# Check if the current directory contains the name
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if name in os.listdir(path):
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path_name = os.path.join(path, name)
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print(f"{name} found: {path_name}")
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return path_name
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# Get the parent directory
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parent_directory = os.path.dirname(path)
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# If the parent directory is the same as the current directory, we've reached the root and stop the search
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if parent_directory == path:
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return None
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# Recursively call the function with the parent directory
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return find_path(name, parent_directory)
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def add_comfyui_directory_to_sys_path() -> None:
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"""
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Add 'ComfyUI' to the sys.path
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"""
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comfyui_path = find_path("ComfyUI")
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if comfyui_path is not None and os.path.isdir(comfyui_path):
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sys.path.append(comfyui_path)
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print(f"'{comfyui_path}' added to sys.path")
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def add_extra_model_paths() -> None:
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"""
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Parse the optional extra_model_paths.yaml file and add the parsed paths to the sys.path.
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"""
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try:
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from main import load_extra_path_config
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except ImportError:
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print(
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"Could not import load_extra_path_config from main.py. Looking in utils.extra_config instead."
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)
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from utils.extra_config import load_extra_path_config
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extra_model_paths = find_path("extra_model_paths.yaml")
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if extra_model_paths is not None:
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load_extra_path_config(extra_model_paths)
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else:
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print("Could not find the extra_model_paths config file.")
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add_comfyui_directory_to_sys_path()
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# add_extra_model_paths()
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def import_custom_nodes() -> None:
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"""Find all custom nodes in the custom_nodes folder and add those node objects to NODE_CLASS_MAPPINGS
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This function sets up a new asyncio event loop, initializes the PromptServer,
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creates a PromptQueue, and initializes the custom nodes.
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"""
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import asyncio
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import execution
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from nodes import init_extra_nodes
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import server
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# Creating a new event loop and setting it as the default loop
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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# Creating an instance of PromptServer with the loop
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server_instance = server.PromptServer(loop)
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execution.PromptQueue(server_instance)
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# Initializing custom nodes
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init_extra_nodes()
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from nodes import LoadImage, NODE_CLASS_MAPPINGS
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def init_portrait_models():
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import_custom_nodes()
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with torch.inference_mode():
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preprocbuildpipe = NODE_CLASS_MAPPINGS["PreprocBuildPipe"]()
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preprocbuildpipe_22 = preprocbuildpipe.load_models(
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prompt_cgpath="prompt",
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templates_cgpath="templates",
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wd14_cgpath="wd14_tagger",
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lut_path="lut",
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)
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facewarppipebuilder = NODE_CLASS_MAPPINGS["FaceWarpPipeBuilder"]()
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facewarppipebuilder_31 = facewarppipebuilder.load_models(
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detect_model_path="facedetect/scrfd_10g_bnkps_shape640x640.onnx",
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deca_dir="deca",
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gpu_choose="cuda:0",
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)
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pulidmodelsloader = NODE_CLASS_MAPPINGS["PulidModelsLoader"]()
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pulidmodelsloader_34 = pulidmodelsloader.load_models(
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base_model_path="checkpoints/LEOSAM_SDXL_v5.0.safetensors",
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canny_model_dir="controlnet/Canny",
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pulid_model_dir="pulid",
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eva_clip_path="eva_clip/EVA02_CLIP_L_336_psz14_s6B.pt",
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insightface_dir="insightface",
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facexlib_dir="facexlib",
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)
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faceswappipebuilder = NODE_CLASS_MAPPINGS["FaceSwapPipeBuilder"]()
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faceswappipebuilder_51 = faceswappipebuilder.load_models(
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swap_own_model="faceswap/swapper_own.pth",
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arcface_model="faceswap/arcface_checkpoint.tar",
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facealign_config_dir="face_align",
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phase1_model="facealign/p1.pt",
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phase2_model="facealign/p2.pt",
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device="cuda:0",
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)
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srblendbuildpipe = NODE_CLASS_MAPPINGS["SrBlendBuildPipe"]()
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srblendbuildpipe_58 = srblendbuildpipe.load_models(
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lut_path="lut", gpu_choose="cuda:0", sr_type="ESRGAN", half=True
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)
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gpenpbuildipeline = NODE_CLASS_MAPPINGS["GPENPBuildipeline"]()
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gpenpbuildipeline_59 = gpenpbuildipeline.load_model(
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model="GPEN-BFR-1024.pth",
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in_size=1024,
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channel_multiplier=2,
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narrow=1,
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alpha=1,
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device="cuda:0",
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)
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preprocgetconds = NODE_CLASS_MAPPINGS["PreprocGetConds"]()
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preprocsplitconds = NODE_CLASS_MAPPINGS["PreprocSplitConds"]()
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facewarpdetectfacesmethod = NODE_CLASS_MAPPINGS["FaceWarpDetectFacesMethod"]()
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facewarpgetfaces3dinfomethod = NODE_CLASS_MAPPINGS[
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"FaceWarpGetFaces3DinfoMethod"
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]()
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facewarpwarp3dfaceimgmaskmethod = NODE_CLASS_MAPPINGS[
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"FaceWarpWarp3DfaceImgMaskMethod"
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]()
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pulidinferclass = NODE_CLASS_MAPPINGS["PulidInferClass"]()
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faceswapdetectpts = NODE_CLASS_MAPPINGS["FaceSwapDetectPts"]()
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faceswapmethod = NODE_CLASS_MAPPINGS["FaceSwapMethod"]()
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gpenprocess = NODE_CLASS_MAPPINGS["GPENProcess"]()
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srblendprocess = NODE_CLASS_MAPPINGS["SrBlendProcess"]()
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return {
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'preprocbuildpipe_22' : preprocbuildpipe_22,
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'facewarppipebuilder_31' : facewarppipebuilder_31,
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'pulidmodelsloader_34' : pulidmodelsloader_34,
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'faceswappipebuilder_51' : faceswappipebuilder_51,
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'srblendbuildpipe_58' : srblendbuildpipe_58,
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'gpenpbuildipeline_59' : gpenpbuildipeline_59,
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'preprocgetconds' : preprocgetconds,
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'preprocsplitconds' : preprocsplitconds,
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'facewarpdetectfacesmethod' : facewarpdetectfacesmethod,
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'facewarpgetfaces3dinfomethod' : facewarpgetfaces3dinfomethod,
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'facewarpwarp3dfaceimgmaskmethod' : facewarpwarp3dfaceimgmaskmethod,
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'pulidinferclass' : pulidinferclass,
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'faceswapdetectpts' : faceswapdetectpts,
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'faceswapmethod' : faceswapmethod,
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'gpenprocess' : gpenprocess,
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'srblendprocess' : srblendprocess,
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}
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portrait_inited_pipes = init_portrait_models()
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def ai_portrait_gpen(image_path, abs_path=True, is_ndarray=False):
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import_custom_nodes()
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with torch.inference_mode():
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# for q in range(10):
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loadimage = LoadImage()
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loadimage_24 = loadimage.load_image(image=image_path, abs_path=abs_path, is_ndarray=is_ndarray)
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preprocgetconds_23 = portrait_inited_pipes['preprocgetconds'].prepare_conditions(
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style="FORMAL",
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gender="MALE",
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is_child=False,
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model=get_value_at_index(portrait_inited_pipes['preprocbuildpipe_22'], 0),
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src_img=get_value_at_index(loadimage_24, 0),
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)
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preprocsplitconds_27 = portrait_inited_pipes['preprocsplitconds'].split_conditions(
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pipe_conditions=get_value_at_index(preprocgetconds_23, 0)
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)
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facewarpdetectfacesmethod_33 = portrait_inited_pipes['facewarpdetectfacesmethod'].detect_faces(
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model=get_value_at_index(portrait_inited_pipes['facewarppipebuilder_31'], 0),
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image=get_value_at_index(preprocsplitconds_27, 0),
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)
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facewarpgetfaces3dinfomethod_32 = (
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portrait_inited_pipes['facewarpgetfaces3dinfomethod'].get_faces_3dinfo(
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model=get_value_at_index(portrait_inited_pipes['facewarppipebuilder_31'], 0),
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image=get_value_at_index(preprocsplitconds_27, 0),
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faces=get_value_at_index(facewarpdetectfacesmethod_33, 0),
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)
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)
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facewarpwarp3dfaceimgmaskmethod_36 = (
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portrait_inited_pipes['facewarpwarp3dfaceimgmaskmethod'].warp_3d_face(
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model=get_value_at_index(portrait_inited_pipes['facewarppipebuilder_31'], 0),
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user_dict=get_value_at_index(facewarpgetfaces3dinfomethod_32, 0),
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template_image=get_value_at_index(preprocsplitconds_27, 3),
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template_mask_img=get_value_at_index(preprocsplitconds_27, 11),
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)
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)
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pulidinferclass_35 = portrait_inited_pipes['pulidinferclass'].pulid_infer(
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prompt=get_value_at_index(preprocsplitconds_27, 1),
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negative_prompt=get_value_at_index(preprocsplitconds_27, 2),
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strength=0.7,
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model=get_value_at_index(portrait_inited_pipes['pulidmodelsloader_34'], 0),
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template_image=get_value_at_index(
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facewarpwarp3dfaceimgmaskmethod_36, 0
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),
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canny_control=get_value_at_index(preprocsplitconds_27, 4),
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user_image=get_value_at_index(preprocsplitconds_27, 0),
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mask=get_value_at_index(facewarpwarp3dfaceimgmaskmethod_36, 1),
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)
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facewarpwarp3dfaceimgmaskmethod_41 = (
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portrait_inited_pipes['facewarpwarp3dfaceimgmaskmethod'].warp_3d_face(
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model=get_value_at_index(portrait_inited_pipes['facewarppipebuilder_31'], 0),
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user_dict=get_value_at_index(facewarpgetfaces3dinfomethod_32, 0),
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template_image=get_value_at_index(pulidinferclass_35, 0),
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template_mask_img=get_value_at_index(
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facewarpwarp3dfaceimgmaskmethod_36, 1
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),
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)
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)
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facewarpdetectfacesmethod_55 = portrait_inited_pipes['facewarpdetectfacesmethod'].detect_faces(
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model=get_value_at_index(portrait_inited_pipes['facewarppipebuilder_31'], 0),
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image=get_value_at_index(facewarpwarp3dfaceimgmaskmethod_41, 0),
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)
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faceswapdetectpts_52 = portrait_inited_pipes['faceswapdetectpts'].detect_face_pts(
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ptstype="256",
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model=get_value_at_index(portrait_inited_pipes['faceswappipebuilder_51'], 0),
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src_image=get_value_at_index(facewarpwarp3dfaceimgmaskmethod_41, 0),
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src_faces=get_value_at_index(facewarpdetectfacesmethod_55, 0),
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)
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faceswapdetectpts_56 = portrait_inited_pipes['faceswapdetectpts'].detect_face_pts(
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ptstype="5",
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model=get_value_at_index(portrait_inited_pipes['faceswappipebuilder_51'], 0),
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src_image=get_value_at_index(preprocsplitconds_27, 0),
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src_faces=get_value_at_index(facewarpdetectfacesmethod_33, 0),
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)
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faceswapdetectpts_54 = portrait_inited_pipes['faceswapdetectpts'].detect_face_pts(
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ptstype="5",
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model=get_value_at_index(portrait_inited_pipes['faceswappipebuilder_51'], 0),
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src_image=get_value_at_index(facewarpwarp3dfaceimgmaskmethod_41, 0),
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src_faces=get_value_at_index(facewarpdetectfacesmethod_55, 0),
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)
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faceswapmethod_53 = portrait_inited_pipes['faceswapmethod'].swap_face(
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model=get_value_at_index(portrait_inited_pipes['faceswappipebuilder_51'], 0),
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src_image=get_value_at_index(preprocsplitconds_27, 0),
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two_stage_image=get_value_at_index(
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facewarpwarp3dfaceimgmaskmethod_41, 0
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),
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source_5pts=get_value_at_index(faceswapdetectpts_56, 0),
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target_5pts=get_value_at_index(faceswapdetectpts_54, 0),
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target_256pts=get_value_at_index(faceswapdetectpts_52, 0),
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)
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gpenprocess_60 = portrait_inited_pipes['gpenprocess'].enhance_face(
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aligned=False,
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model=get_value_at_index(portrait_inited_pipes['gpenpbuildipeline_59'], 0),
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image=get_value_at_index(faceswapmethod_53, 0),
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)
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_, final_img = portrait_inited_pipes['srblendprocess'].enhance_process(
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style="FORMAL",
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is_front="False",
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model=get_value_at_index(portrait_inited_pipes['srblendbuildpipe_58'], 0),
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conditions=get_value_at_index(preprocgetconds_23, 0),
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src_img=get_value_at_index(gpenprocess_60, 0),
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)
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outimg = get_value_at_index(final_img, 0) * 255.
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return outimg.cpu().numpy().astype(np.uint8)
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import numpy as np
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from PIL import Image
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import cv2
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if __name__ == "__main__":
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img_path = '/home/user/works/projs/WebServer/distributed-server-node/submodules/VisualForge/ComfyUI/input/portraitInput.jpg'
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image = np.array(Image.open(img_path))[..., :3]
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for i in range(10):
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final_img = ai_portrait_gpen(image, is_ndarray=True)
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cv2.imwrite('fuckaigc.png', final_img)
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