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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 |