1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
|
# Copyright 2016 (c) Egor Tensin <Egor.Tensin@gmail.com>
# This file is part of the "Simple image filters" project.
# For details, see https://github.com/egor-tensin/filters.
# Distributed under the MIT License.
import argparse
import sys
import cv2
import numpy as np
def gen_kernel(radius, sigma):
kernel = np.array([[i ** 2 + j ** 2
for i in range(-radius, radius + 1)]
for j in range(-radius, radius + 1)])
kernel = -kernel / (2 * sigma ** 2)
kernel = np.exp(kernel)
kernel = kernel / np.sum(kernel)
return kernel
def convolve(img, kernel):
#print(kernel)
radius = kernel.shape[0] // 2
output = np.zeros(img.shape, dtype=img.dtype)
for i in range(radius, img.shape[0] - radius):
for j in range(radius, img.shape[1] - radius):
neighborhood = img[i - radius:i + radius + 1, j - radius:j + radius + 1]
output[i, j] = np.sum(neighborhood * kernel)
return output
DEFAULT_SIGMA = 1.
DEFAULT_RADIUS = 1
def gaussian(img_path, radius=DEFAULT_RADIUS, sigma=DEFAULT_SIGMA,
output_path=None):
img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)
kernel = gen_kernel(radius, sigma)
output = convolve(img, kernel)
if output_path is None:
cv2.imshow("Output", output)
cv2.waitKey()
else:
cv2.imwrite(output_path, output)
def _parse_non_negative_integer(s):
try:
x = int(s)
except ValueError:
raise argparse.ArgumentTypeError('must be a non-negative integer: ' + s)
if x < 0:
raise argparse.ArgumentTypeError('must be a non-negative integer: ' + s)
return x
def _parse_args(args=sys.argv):
parser = argparse.ArgumentParser()
parser.add_argument('img_path')
parser.add_argument('--output', '-o',
dest='output_path', default=None)
parser.add_argument('-s', '--sigma',
type=float, default=DEFAULT_SIGMA)
parser.add_argument('--radius', '-r',
type=_parse_non_negative_integer,
default=DEFAULT_RADIUS)
return parser.parse_args(args[1:])
def main(args=sys.argv):
gaussian(**vars(_parse_args(args)))
if __name__ == '__main__':
main()
|
