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import glob
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import os
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from typing import List
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from insightface.app.common import Face
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from safetensors.torch import save_file, safe_open
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import torch
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import modules.scripts as scripts
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from modules import scripts
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from scripts.faceswaplab_utils.faceswaplab_logging import logger
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import dill as pickle # will be removed in future versions
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def save_face(face: Face, filename: str) -> None:
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tensors = {
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"embedding": torch.tensor(face["embedding"]),
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"gender": torch.tensor(face["gender"]),
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"age": torch.tensor(face["age"]),
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}
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save_file(tensors, filename)
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def load_face(filename: str) -> Face:
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if filename.endswith(".pkl"):
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logger.warning(
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"Pkl files for faces are deprecated to enhance safety, they will be unsupported in future versions."
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)
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logger.warning("The file will be converted to .safetensors")
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logger.warning(
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"You can also use this script https://gist.github.com/glucauze/4a3c458541f2278ad801f6625e5b9d3d"
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)
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with open(filename, "rb") as file:
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logger.info("Load pkl")
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face = Face(pickle.load(file))
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logger.warning(
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"Convert to safetensors, you can remove the pkl version once you have ensured that the safetensor is working"
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)
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save_face(face, filename.replace(".pkl", ".safetensors"))
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return face
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elif filename.endswith(".safetensors"):
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face = {}
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with safe_open(filename, framework="pt", device="cpu") as f:
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for k in f.keys():
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logger.debug("load key %s", k)
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face[k] = f.get_tensor(k).numpy()
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return Face(face)
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raise NotImplementedError("Unknown file type, face extraction not implemented")
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def get_face_checkpoints() -> List[str]:
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"""
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Retrieve a list of face checkpoint paths.
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This function searches for face files with the extension ".safetensors" in the specified directory and returns a list
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containing the paths of those files.
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Returns:
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list: A list of face paths, including the string "None" as the first element.
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"""
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faces_path = os.path.join(
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scripts.basedir(), "models", "faceswaplab", "faces", "*.safetensors"
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)
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faces = glob.glob(faces_path)
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faces_path = os.path.join(
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scripts.basedir(), "models", "faceswaplab", "faces", "*.pkl"
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)
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faces += glob.glob(faces_path)
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return ["None"] + sorted(faces)
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