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from basicsr.archs.rrdbnet_arch import RRDBNet | ||
from basicsr.utils.download_util import load_file_from_url | ||
from gfpgan import GFPGANer | ||
from os import path | ||
from PIL import Image | ||
from realesrgan import RealESRGANer | ||
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denoise_strength = 0.5 | ||
gfpgan_url = 'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth' | ||
resrgan_url = [ | ||
'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth'] | ||
fp32 = True | ||
model_name = 'RealESRGAN_x4plus' | ||
netscale = 4 | ||
outscale = 4 | ||
pre_pad = 0 | ||
tile = 0 | ||
tile_pad = 10 | ||
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def upscale_resrgan(source_image: Image) -> Image: | ||
model_path = path.join('weights', model_name + '.pth') | ||
if not path.isfile(model_path): | ||
ROOT_DIR = os.path.dirname(path.abspath(__file__)) | ||
for url in resrgan_url: | ||
model_path = load_file_from_url( | ||
url=url, model_dir=path.join(ROOT_DIR, 'weights'), progress=True, file_name=None) | ||
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model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, | ||
num_block=23, num_grow_ch=32, scale=4) | ||
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dni_weight = None | ||
if model_name == 'realesr-general-x4v3' and denoise_strength != 1: | ||
wdn_model_path = model_path.replace( | ||
'realesr-general-x4v3', 'realesr-general-wdn-x4v3') | ||
model_path = [model_path, wdn_model_path] | ||
dni_weight = [denoise_strength, 1 - denoise_strength] | ||
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upsampler = RealESRGANer( | ||
scale=netscale, | ||
model_path=model_path, | ||
dni_weight=dni_weight, | ||
model=model, | ||
tile=tile, | ||
tile_pad=tile_pad, | ||
pre_pad=pre_pad, | ||
half=fp32) | ||
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output, _ = upsampler.enhance(source_image, outscale=outscale) | ||
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return upscale_gfpgan(output, upsampler) | ||
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def upscale_gfpgan(source_image: Image, upsampler) -> Image: | ||
face_enhancer = GFPGANer( | ||
model_path=gfpgan_url, | ||
upscale=outscale, | ||
arch='clean', | ||
channel_multiplier=2, | ||
bg_upsampler=upsampler) | ||
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_, _, output = face_enhancer.enhance(source_image, has_aligned=False, only_center_face=False, paste_back=True) | ||
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return output |