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import os | |
from basicsr.utils import imwrite | |
from gfpgan import GFPGANer | |
from tqdm import tqdm | |
def enhancer(images, method='gfpgan'): | |
# ------------------------ set up GFPGAN restorer ------------------------ | |
if method == 'gfpgan': | |
arch = 'clean' | |
channel_multiplier = 2 | |
model_name = 'GFPGANv1.4' | |
url = 'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth' | |
elif method == 'RestoreFormer': | |
arch = 'RestoreFormer' | |
channel_multiplier = 2 | |
model_name = 'RestoreFormer' | |
url = 'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/RestoreFormer.pth' | |
elif method == 'codeformer': | |
arch = 'CodeFormer' | |
channel_multiplier = 2 | |
model_name = 'CodeFormer' | |
url = 'https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth' | |
else: | |
raise ValueError(f'Wrong model version {method}.') | |
# determine model paths | |
model_path = os.path.join('experiments/pretrained_models', model_name + '.pth') | |
if not os.path.isfile(model_path): | |
model_path = os.path.join('checkpoints', model_name + '.pth') | |
if not os.path.isfile(model_path): | |
# download pre-trained models from url | |
model_path = url | |
restorer = GFPGANer( | |
model_path=model_path, | |
upscale=2, | |
arch=arch, | |
channel_multiplier=channel_multiplier, | |
bg_upsampler=None) | |
# ------------------------ restore ------------------------ | |
restored_img = [] | |
for idx in tqdm(range(len(images)), 'Face Enhancer:'): | |
# restore faces and background if necessary | |
cropped_faces, restored_faces, _ = restorer.enhance( | |
images[idx], | |
has_aligned=True, | |
only_center_face=False, | |
paste_back=True, | |
weight=0.5) | |
restored_img += restored_faces | |
return restored_img |