2023-03-30 10:07:38 +02:00
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import cv2
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from loguru import logger
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from lama_cleaner.helper import download_model
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from lama_cleaner.plugins.base_plugin import BasePlugin
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class RestoreFormerPlugin(BasePlugin):
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name = "RestoreFormer"
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def __init__(self, device, upscaler=None):
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super().__init__()
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from .gfpganer import MyGFPGANer
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url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/RestoreFormer.pth"
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model_md5 = "eaeeff6c4a1caa1673977cb374e6f699"
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model_path = download_model(url, model_md5)
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logger.info(f"RestoreFormer model path: {model_path}")
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import facexlib
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if hasattr(facexlib.detection.retinaface, "device"):
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facexlib.detection.retinaface.device = device
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self.face_enhancer = MyGFPGANer(
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model_path=model_path,
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2023-04-03 07:19:26 +02:00
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upscale=1,
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2023-03-30 10:07:38 +02:00
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arch="RestoreFormer",
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channel_multiplier=2,
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device=device,
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bg_upsampler=upscaler.model if upscaler is not None else None,
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)
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def __call__(self, rgb_np_img, files, form):
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weight = 0.5
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bgr_np_img = cv2.cvtColor(rgb_np_img, cv2.COLOR_RGB2BGR)
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logger.info(f"RestoreFormer input shape: {bgr_np_img.shape}")
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_, _, bgr_output = self.face_enhancer.enhance(
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bgr_np_img,
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has_aligned=False,
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only_center_face=False,
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paste_back=True,
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weight=weight,
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)
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logger.info(f"RestoreFormer output shape: {bgr_output.shape}")
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return bgr_output
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def check_dep(self):
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try:
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import gfpgan
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except ImportError:
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return (
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"gfpgan is not installed, please install it first. pip install gfpgan"
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)
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