def test_scaling(self):
im = get_img_arr('imgs/castle_small.jpg')
h, w = new_shape_for_ratio(im, 315, 851, scale_x=False)
assert (abs(h / w - 315 / 851) < 0.001)
h, w = new_shape_for_ratio(im, 215, 851)
assert (abs(h / w - 215 / 851) < 0.001)
def test_import_rect(self):
rectangle_img = get_img_arr("imgs/HJoceanSmall.png")
self.assertEqual(rectangle_img.shape, (285, 507, 3))
def test_import_square(self):
square_img = get_img_arr("imgs/mountain_icon.jpg")
self.assertEqual(square_img.shape, (64, 64, 3))
def main():
parser = argparse.ArgumentParser(
description="Intelligently crop an image along one axis")
parser.add_argument('input_file')
parser.add_argument('-a',
'--axis',
required=True,
help="What axis to shrink the image on.",
choices=['x', 'y'])
parser.add_argument('-p',
'--pixels',
type=int,
required=True,
help="How many pixels to shrink the image by.")
parser.add_argument('-o',
'--output',
help="What to name the new cropped image.")
parser.add_argument('-i',
'--interval',
type=int,
help="Save every i intermediate images.")
parser.add_argument(
'-b',
'--border',
type=bool,
help=
"Whether or not to pad the cropped images to the size of the original")
parser.add_argument(
'-s',
'--show_seam',
type=bool,
help="Whether to highlight the removed seam on the intermediate images."
)
args = vars(parser.parse_args())
print(args)
img = get_img_arr(args['input_file'])
if args['axis'] == 'y':
img = np.transpose(img, axes=(1, 0, 2))
if args['output'] is None:
name = args['input_file'].split('.')
args['output'] = name[0] + '_crop.' + name[1]
savepoints = every_n(args['interval'],
img.shape[1]) if args['interval'] else None
cropped_img = resize_image(img,
args['pixels'],
dual_gradient_energy,
save_name=args['output'],
savepoints=savepoints,
rotated=args['axis'] == 'y',
pad=args['border'],
highlight=args['show_seam'])
if args['axis'] == 'y':
cropped_img = np.transpose(cropped_img, axes=(1, 0, 2))
if args['border']:
h, w = img.shape[:2]
if args['axis'] == 'y':
h, w = w, h
cropped_img = pad_img(cropped_img, h, w)
cropped_img.save(args['output'])
else:
Image.fromarray(cropped_img).save(args['output'])
print(
"\nImage {0} cropped by {1} pixels along the {2}-axis and saved as {3}\n"
.format(args['input_file'], args['pixels'], args['axis'],
args['output']))