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image_aligner.py
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image_aligner.py
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# source: https://github.com/woctezuma/stylegan2/tree/tiled-projector
import numpy as np
import scipy.ndimage
import os
import PIL.Image
import auxiliary as aux
import sys
import argparse
from LandmarksDetector import LandmarksDetector
DLIB_LMD_PATH = "shape_predictor_68_face_landmarks.dat"
def parse_arguments():
'''Parses in CLI arguments'''
parser = argparse.ArgumentParser(
prog='image_aligner.py',
description='A CLI tool for aligning images of faces using FFHQ\'s script.',
epilog='Disclaimer: this code comes from this reposioty: https://github.com/woctezuma/stylegan2/tree/tiled-projector')
requiredArgs = parser.add_argument_group('Required arguments')
requiredArgs.add_argument('-r', '--raw', type=aux.check_dir_path, help='Provide the folder path containing the raw images.', required=True)
requiredArgs.add_argument('-a', '--aligned', type=aux.check_dir_path, help='Provide the folder path for the results (aligned images).', required=True)
return parser.parse_args()
def create_aligned_image(src_file, out_file, face_landmarks, output_size=1024, transform_size=4096, enable_padding=True):
# Parse landmarks.
# pylint: disable=unused-variable
lm = np.array(face_landmarks)
lm_chin = lm[0 : 17] # left-right
lm_eyebrow_left = lm[17 : 22] # left-right
lm_eyebrow_right = lm[22 : 27] # left-right
lm_nose = lm[27 : 31] # top-down
lm_nostrils = lm[31 : 36] # top-down
lm_eye_left = lm[36 : 42] # left-clockwise
lm_eye_right = lm[42 : 48] # left-clockwise
lm_mouth_outer = lm[48 : 60] # left-clockwise
lm_mouth_inner = lm[60 : 68] # left-clockwise
# Calculate auxiliary vectors.
eye_left = np.mean(lm_eye_left, axis=0)
eye_right = np.mean(lm_eye_right, axis=0)
eye_avg = (eye_left + eye_right) * 0.5
eye_to_eye = eye_right - eye_left
mouth_left = lm_mouth_outer[0]
mouth_right = lm_mouth_outer[6]
mouth_avg = (mouth_left + mouth_right) * 0.5
eye_to_mouth = mouth_avg - eye_avg
# Choose oriented crop rectangle.
x = eye_to_eye - np.flipud(eye_to_mouth) * [-1, 1]
x /= np.hypot(*x)
x *= max(np.hypot(*eye_to_eye) * 2.0, np.hypot(*eye_to_mouth) * 1.8)
y = np.flipud(x) * [-1, 1]
c = eye_avg + eye_to_mouth * 0.1
quad = np.stack([c - x - y, c - x + y, c + x + y, c + x - y])
qsize = np.hypot(*x) * 2
# Load unaligned image.
if not os.path.isfile(src_file):
print('\nCannot find source image. Please run "--wilds" before "--align".')
return
img = PIL.Image.open(src_file)
# Shrink.
shrink = int(np.floor(qsize / output_size * 0.5))
if shrink > 1:
rsize = (int(np.rint(float(img.size[0]) / shrink)), int(np.rint(float(img.size[1]) / shrink)))
img = img.resize(rsize, PIL.Image.ANTIALIAS)
quad /= shrink
qsize /= shrink
# Crop.
border = max(int(np.rint(qsize * 0.1)), 3)
crop = (int(np.floor(min(quad[:,0]))), int(np.floor(min(quad[:,1]))), int(np.ceil(max(quad[:,0]))), int(np.ceil(max(quad[:,1]))))
crop = (max(crop[0] - border, 0), max(crop[1] - border, 0), min(crop[2] + border, img.size[0]), min(crop[3] + border, img.size[1]))
if crop[2] - crop[0] < img.size[0] or crop[3] - crop[1] < img.size[1]:
img = img.crop(crop)
quad -= crop[0:2]
# Pad.
pad = (int(np.floor(min(quad[:,0]))), int(np.floor(min(quad[:,1]))), int(np.ceil(max(quad[:,0]))), int(np.ceil(max(quad[:,1]))))
pad = (max(-pad[0] + border, 0), max(-pad[1] + border, 0), max(pad[2] - img.size[0] + border, 0), max(pad[3] - img.size[1] + border, 0))
if enable_padding and max(pad) > border - 4:
pad = np.maximum(pad, int(np.rint(qsize * 0.3)))
img = np.pad(np.float32(img), ((pad[1], pad[3]), (pad[0], pad[2]), (0, 0)), 'reflect')
h, w, _ = img.shape
y, x, _ = np.ogrid[:h, :w, :1]
mask = np.maximum(1.0 - np.minimum(np.float32(x) / pad[0], np.float32(w-1-x) / pad[2]), 1.0 - np.minimum(np.float32(y) / pad[1], np.float32(h-1-y) / pad[3]))
blur = qsize * 0.02
img += (scipy.ndimage.gaussian_filter(img, [blur, blur, 0]) - img) * np.clip(mask * 3.0 + 1.0, 0.0, 1.0)
img += (np.median(img, axis=(0,1)) - img) * np.clip(mask, 0.0, 1.0)
img = PIL.Image.fromarray(np.uint8(np.clip(np.rint(img), 0, 255)), 'RGB')
quad += pad[:2]
# Transform.
img = img.transform((transform_size, transform_size), PIL.Image.QUAD, (quad + 0.5).flatten(), PIL.Image.BILINEAR)
if output_size < transform_size:
img = img.resize((output_size, output_size), PIL.Image.ANTIALIAS) # ANTIALIAS is deprecated and will be removed in Pillow 10
# you have to downgrade your pillow installation
# pip install Pillow==9.5.0
# source: https://stackoverflow.com/questions/76616042/attributeerror-module-pil-image-has-no-attribute-antialias
# Save aligned image.
img.save(out_file,'png')
def main():
# Parse arguments
args = parse_arguments()
# download dlib model
aux.download_dlib_lmd(DLIB_LMD_PATH)
landmarksDetector = LandmarksDetector(DLIB_LMD_PATH)
for img_name in os.listdir(args.raw):
raw_img_path = os.path.join(args.raw, img_name)
if raw_img_path.endswith('.ppm'):
# https://github.com/dhar174/ppm-2-png/blob/master/ppm-2-png.py
temp_image = PIL.Image.open(raw_img_path)
new_path = raw_img_path[:-4]
new_path = new_path + ".png"
temp_image.save(new_path)
print(f'Saved .ppm image as .png')
print(f' {raw_img_path} \t -> \t {new_path}')
raw_img_path = new_path
for i, face_landmarks in enumerate(landmarksDetector.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(args.aligned, face_img_name)
os.makedirs(args.aligned, exist_ok=True)
create_aligned_image(raw_img_path, aligned_face_path, face_landmarks)
if __name__ == "__main__":
main()