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import os |
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import sys |
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import bz2 |
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import argparse |
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from keras.utils import get_file |
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from ffhq_dataset.face_alignment import image_align |
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from ffhq_dataset.landmarks_detector import LandmarksDetector |
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import multiprocessing |
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def unpack_bz2(src_path): |
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data = bz2.BZ2File(src_path).read() |
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dst_path = src_path[:-4] |
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with open(dst_path, 'wb') as fp: |
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fp.write(data) |
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return dst_path |
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if __name__ == "__main__": |
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""" |
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Extracts and aligns all faces from images using DLib and a function from original FFHQ dataset preparation step |
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python align_images.py /raw_images /aligned_images |
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""" |
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parser = argparse.ArgumentParser(description='Align faces from input images', formatter_class=argparse.ArgumentDefaultsHelpFormatter) |
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parser.add_argument('raw_dir', help='Directory with raw images for face alignment') |
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parser.add_argument('aligned_dir', help='Directory for storing aligned images') |
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parser.add_argument('--output_size', default=1024, help='The dimension of images for input to the model', type=int) |
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parser.add_argument('--x_scale', default=1, help='Scaling factor for x dimension', type=float) |
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parser.add_argument('--y_scale', default=1, help='Scaling factor for y dimension', type=float) |
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parser.add_argument('--em_scale', default=0.1, help='Scaling factor for eye-mouth distance', type=float) |
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parser.add_argument('--use_alpha', default=False, help='Add an alpha channel for masking', type=bool) |
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args, other_args = parser.parse_known_args() |
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landmarks_model_path = unpack_bz2("shape_predictor_68_face_landmarks.dat.bz2") |
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RAW_IMAGES_DIR = args.raw_dir |
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ALIGNED_IMAGES_DIR = args.aligned_dir |
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landmarks_detector = LandmarksDetector(landmarks_model_path) |
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for img_name in os.listdir(RAW_IMAGES_DIR): |
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print('Aligning %s ...' % img_name) |
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try: |
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raw_img_path = os.path.join(RAW_IMAGES_DIR, img_name) |
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fn = face_img_name = '%s_%02d.png' % (os.path.splitext(img_name)[0], 1) |
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if os.path.isfile(fn): |
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continue |
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print('Getting landmarks...') |
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for i, face_landmarks in enumerate(landmarks_detector.get_landmarks(raw_img_path), start=1): |
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try: |
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print('Starting face alignment...') |
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face_img_name = '%s_%02d.png' % (os.path.splitext(img_name)[0], i) |
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aligned_face_path = os.path.join(ALIGNED_IMAGES_DIR, face_img_name) |
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image_align(raw_img_path, aligned_face_path, face_landmarks, output_size=args.output_size, x_scale=args.x_scale, y_scale=args.y_scale, em_scale=args.em_scale, alpha=args.use_alpha) |
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print('Wrote result %s' % aligned_face_path) |
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except: |
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print("Exception in face alignment!") |
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except: |
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print("Exception in landmark detection!") |
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