72 lines
2.2 KiB
Python
72 lines
2.2 KiB
Python
from __future__ import annotations
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import logging
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import os
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import torch
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from modules import (
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devices,
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errors,
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face_restoration,
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face_restoration_utils,
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modelloader,
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shared,
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)
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logger = logging.getLogger(__name__)
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model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth"
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model_download_name = "GFPGANv1.4.pth"
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gfpgan_face_restorer: face_restoration.FaceRestoration | None = None
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class FaceRestorerGFPGAN(face_restoration_utils.CommonFaceRestoration):
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def name(self):
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return "GFPGAN"
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def get_device(self):
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return devices.device_gfpgan
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def load_net(self) -> torch.Module:
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for model_path in modelloader.load_models(
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model_path=self.model_path,
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model_url=model_url,
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command_path=self.model_path,
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download_name=model_download_name,
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ext_filter=['.pth'],
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):
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if 'GFPGAN' in os.path.basename(model_path):
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model = modelloader.load_spandrel_model(
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model_path,
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device=self.get_device(),
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expected_architecture='GFPGAN',
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).model
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model.different_w = True # see https://github.com/chaiNNer-org/spandrel/pull/81
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return model
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raise ValueError("No GFPGAN model found")
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def restore(self, np_image):
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def restore_face(cropped_face_t):
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assert self.net is not None
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return self.net(cropped_face_t, return_rgb=False)[0]
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return self.restore_with_helper(np_image, restore_face)
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def gfpgan_fix_faces(np_image):
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if gfpgan_face_restorer:
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return gfpgan_face_restorer.restore(np_image)
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logger.warning("GFPGAN face restorer not set up")
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return np_image
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def setup_model(dirname: str) -> None:
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global gfpgan_face_restorer
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try:
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face_restoration_utils.patch_facexlib(dirname)
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gfpgan_face_restorer = FaceRestorerGFPGAN(model_path=dirname)
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shared.face_restorers.append(gfpgan_face_restorer)
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except Exception:
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errors.report("Error setting up GFPGAN", exc_info=True)
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