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align_images.py
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align_images.py
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import os
import sys
import bz2
from keras.utils import get_file
from ffhq_dataset.face_alignment import image_align
from ffhq_dataset.landmarks_detector import LandmarksDetector
LANDMARKS_MODEL_URL = 'http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2'
def unpack_bz2(src_path):
data = bz2.BZ2File(src_path).read()
dst_path = src_path[:-4]
with open(dst_path, 'wb') as fp:
fp.write(data)
return dst_path
if __name__ == "__main__":
"""
Extracts and aligns all faces from images using DLib and a function from original FFHQ dataset preparation step
python align_images.py /raw_images /aligned_images
"""
landmarks_model_path = unpack_bz2(get_file('shape_predictor_68_face_landmarks.dat.bz2',
LANDMARKS_MODEL_URL, cache_subdir='temp'))
RAW_IMAGES_DIR = sys.argv[1]
ALIGNED_IMAGES_DIR = sys.argv[2]
landmarks_detector = LandmarksDetector(landmarks_model_path)
for img_name in os.listdir(RAW_IMAGES_DIR):
raw_img_path = os.path.join(RAW_IMAGES_DIR, img_name)
for i, face_landmarks in enumerate(landmarks_detector.get_landmarks(raw_img_path), start=1):
face_img_name = '%s_%02d.png' % (os.path.splitext(img_name)[0], i)
aligned_face_path = os.path.join(ALIGNED_IMAGES_DIR, face_img_name)
image_align(raw_img_path, aligned_face_path, face_landmarks)