resize = tuple(map(
int, args.resize.split('x'))) if args.resize is not None else None
crop = tuple(map(int, args.crop.split('x'))) if args.crop is not None else None
trim = tuple(map(float,
args.trim.split(':'))) if args.trim is not None else None
flip = {
'v': 0,
'h': 1,
'hv': -1,
'vh': -1
}[args.flip] if args.flip is not None else None
normalize = args.normalize
crop_center = CropCenter[args.crop_center]
print("Creating directory hierarchy")
create_directories(paths)
print("Fetching models")
fetch_models(paths)
if args.no_label:
print("Decimating video")
labeller = None
else:
print("Decimating video and labelling with {}".format(args.label_with))
labeller = Labeller.build_from_arguments(args, paths)
decimate_and_label_video(paths,
labeller,
trim=trim,
subsample=args.subsample,
subsample_offset=args.subsample_offset,
p.add_argument('--frame-offset',
help='The frame offset for the two datasets',
required=True,
type=int)
p.add_argument('--target-label-offset', required=True, type=int)
p = Labeller.add_arguments(p)
return p.parse_args()
print("Synthesizing face puppet")
args = parse_arguments()
paths_base = build_paths(args, directory_prefix='base')
paths_out = build_paths(args, directory_prefix='test')
create_directories(paths_out)
labeller = Labeller.build_from_arguments(args, paths_base)
labeller_t = Labeller.build_from_arguments(
args, paths_base, label_offset=args.target_label_offset)
del labeller.face_labeller.landmarks["right_eyebrow"]
del labeller.face_labeller.landmarks["left_eyebrow"]
del labeller.face_labeller.landmarks["right_eye"]
del labeller.face_labeller.landmarks["left_eye"]
del labeller_t.face_labeller.landmarks["mouth"]
del labeller_t.face_labeller.landmarks["inner_mouth"]
del labeller_t.face_labeller.landmarks["nose"]
del labeller_t.face_labeller.landmarks["jaw"]
base_image_fns = sorted(os.listdir(paths_base.img_dir))