"--input",
help="input image",
type=str,
default='play/1.jpg')
parser.add_argument("-o", "--out", help="output image file", default='x.jpg')
parser.add_argument("--crop_size",
help="specify size of aligned faces",
default=112,
type=int)
args = parser.parse_args()
crop_size = args.crop_size
scale = crop_size / 112.
reference = get_reference_facial_points(default_square=True) * scale
img = Image.open(args.input).convert('RGB')
start = time.time()
bounding_boxes, landmarks = detect_faces(img)
print(bounding_boxes)
print(len(bounding_boxes))
end = time.time()
print(end - start)
show_results(img, bounding_boxes, landmarks).save(args.out)
for i in range(len(landmarks)):
facial5points = [[landmarks[i][j], landmarks[i][j + 5]] for j in range(5)]
warped_face = warp_and_crop_face(np.array(img),
facial5points,
reference,
crop_size=(crop_size, crop_size))
Image.fromarray(warped_face).save(f'y{i}.jpg')
os.chdir(source_root)
os.system("find . -name '*.DS_Store' -type f -delete")
os.chdir(cwd)
if not os.path.isdir(dest_root):
os.mkdir(dest_root)
for subfolder in tqdm(os.listdir(source_root)):
if not os.path.isdir(os.path.join(dest_root, subfolder)):
os.mkdir(os.path.join(dest_root, subfolder))
for image_name in os.listdir(os.path.join(source_root, subfolder)):
print("Processing\t{}".format(
os.path.join(source_root, subfolder, image_name)))
img = Image.open(os.path.join(source_root, subfolder, image_name))
try: # Handle exception
_, landmarks = detect_faces(img)
except Exception:
print("{} is discarded due to exception!".format(
os.path.join(source_root, subfolder, image_name)))
continue
if len(
landmarks
) == 0: # If the landmarks cannot be detected, the img will be discarded
print("{} is discarded due to non-detected landmarks!".format(
os.path.join(source_root, subfolder, image_name)))
continue
facial5points = [[landmarks[0][j], landmarks[0][j + 5]]
for j in range(5)]
warped_face = warp_and_crop_face(np.array(img),
facial5points,
reference,
#!/usr/bin/env python
from PIL import Image
import numpy as np
from evolveface import detect_faces, show_results
from evolveface import get_reference_facial_points, warp_and_crop_face
import time
crop_size = 112
scale = crop_size / 112.
reference = get_reference_facial_points(default_square=True) * scale
for img in [
"play/img_00005.jpg", "play/img_00276.jpg", "play/img_00277.jpg", "play/img_00278.jpg", "play/img_00279.jpg",
"play/img_00280.jpg", "play/img_00281.jpg", "play/img_00282.jpg", "play/img_00283.jpg", "play/img_00284.jpg",
"play/img_00285.jpg", "play/img_00286.jpg", "play/img_00287.jpg", "play/img_00288.jpg", "play/img_00323.jpg",
"play/img_01718.jpg", "play/img_02692.jpg", "play/img_03152.jpg", "play/img_05397.jpg"
]:
bounding_boxes, landmarks = detect_faces(Image.open(img).convert('RGB'))