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| ''' | |
| @paper: GAN Prior Embedded Network for Blind Face Restoration in the Wild (CVPR2021) | |
| @author: yangxy (yangtao9009@gmail.com) | |
| ''' | |
| import os | |
| import cv2 | |
| import glob | |
| import time | |
| import numpy as np | |
| from PIL import Image | |
| import __init_paths | |
| from face_model.face_gan import FaceGAN | |
| class Segmentation2Face(object): | |
| def __init__(self, base_dir='./', size=1024, model=None, channel_multiplier=2, narrow=1, is_norm=True): | |
| self.facegan = FaceGAN(base_dir, size, model, channel_multiplier, narrow, is_norm) | |
| # make sure the face image is well aligned. Please refer to face_enhancement.py | |
| def process(self, segf): | |
| # from segmentations to faces | |
| out = self.facegan.process(segf) | |
| return out | |
| if __name__=='__main__': | |
| model = {'name':'GPEN-Seg2face-512', 'size':512} | |
| indir = 'examples/segs' | |
| outdir = 'examples/outs-seg2face' | |
| os.makedirs(outdir, exist_ok=True) | |
| seg2face = Segmentation2Face(size=model['size'], model=model['name'], channel_multiplier=2, is_norm=False) | |
| files = sorted(glob.glob(os.path.join(indir, '*.*g'))) | |
| for n, file in enumerate(files[:]): | |
| filename = os.path.basename(file) | |
| segf = cv2.imread(file, cv2.IMREAD_COLOR) | |
| realf = seg2face.process(segf) | |
| segf = cv2.resize(segf, realf.shape[:2]) | |
| cv2.imwrite(os.path.join(outdir, '.'.join(filename.split('.')[:-1])+'.jpg'), np.hstack((segf, realf))) | |
| if n%10==0: print(n, file) | |