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-rw-r--r--.gitignore1
-rw-r--r--LICENSE.txt21
-rw-r--r--gaussian.py71
-rw-r--r--img/Lenna.pngbin0 -> 473831 bytes
-rw-r--r--mean.py61
-rw-r--r--shift.py112
6 files changed, 266 insertions, 0 deletions
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..b44ef38
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1 @@
+/*.png
diff --git a/LICENSE.txt b/LICENSE.txt
new file mode 100644
index 0000000..80c5e0a
--- /dev/null
+++ b/LICENSE.txt
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2016 Egor Tensin <Egor.Tensin@gmail.com>
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/gaussian.py b/gaussian.py
new file mode 100644
index 0000000..743b70d
--- /dev/null
+++ b/gaussian.py
@@ -0,0 +1,71 @@
+# 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 do(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):
+ do(**vars(_parse_args(args)))
+
+if __name__ == '__main__':
+ main()
diff --git a/img/Lenna.png b/img/Lenna.png
new file mode 100644
index 0000000..59ef68a
--- /dev/null
+++ b/img/Lenna.png
Binary files differ
diff --git a/mean.py b/mean.py
new file mode 100644
index 0000000..6b09eda
--- /dev/null
+++ b/mean.py
@@ -0,0 +1,61 @@
+# 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):
+ size = radius * 2 + 1
+ return np.ones((size, size)) / size ** 2
+
+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(kernel * neighborhood)
+ return output
+
+DEFAULT_RADIUS = 1
+
+def do(img_path, radius=DEFAULT_RADIUS, output_path=None):
+ img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)
+ kernel = gen_kernel(radius)
+ 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('--radius', '-r',
+ type=_parse_non_negative_integer,
+ default=DEFAULT_RADIUS)
+ return parser.parse_args(args[1:])
+
+def main(args=sys.argv):
+ do(**vars(_parse_args(args)))
+
+if __name__ == '__main__':
+ main()
diff --git a/shift.py b/shift.py
new file mode 100644
index 0000000..76ca09a
--- /dev/null
+++ b/shift.py
@@ -0,0 +1,112 @@
+# 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
+from enum import Enum
+import sys
+
+import cv2
+import numpy as np
+
+class Direction(Enum):
+ N = 'N'
+ NE = 'NE'
+ E = 'E'
+ SE = 'SE'
+ S = 'S'
+ SW = 'SW'
+ W = 'W'
+ NW = 'NW'
+
+ def gen_kernel(self, distance):
+ radius = distance
+ size = 2 * radius + 1
+ kernel = np.zeros((size, size))
+ x, y = radius, radius
+
+ if self is Direction.N:
+ x = -1
+ elif self is Direction.NE:
+ x, y = -1, 0
+ elif self is Direction.E:
+ y = 0
+ elif self is Direction.SE:
+ x, y = 0, 0
+ elif self is Direction.S:
+ x = 0
+ elif self is Direction.SW:
+ x, y = 0, -1
+ elif self is Direction.W:
+ y = -1
+ elif self is Direction.NW:
+ x, y = -1, -1
+ else:
+ raise NotImplementedError('unsupported direction: ' + str(self))
+
+ kernel[x, y] = 1
+ return kernel
+
+ def __str__(self):
+ return self.name
+
+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_DIRECTION = Direction.SE
+DEFAULT_DISTANCE = 1
+
+def do(img_path, direction=DEFAULT_DIRECTION, distance=DEFAULT_DISTANCE,
+ output_path=None):
+
+ img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)
+ kernel = direction.gen_kernel(distance)
+ output = convolve(img, kernel)
+ if output_path is None:
+ cv2.imshow("Output", output)
+ cv2.waitKey()
+ else:
+ cv2.imwrite(output_path, output)
+
+def _parse_direction(s):
+ try:
+ return Direction(s)
+ except ValueError:
+ raise argparse.ArgumentTypeError('invalid direction: ' + s)
+
+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('--direction', '-d',
+ type=_parse_direction,
+ choices=Direction,
+ default=DEFAULT_DIRECTION)
+ parser.add_argument('--distance', '-n',
+ type=_parse_non_negative_integer,
+ default=DEFAULT_DISTANCE)
+ return parser.parse_args(args[1:])
+
+def main(args=sys.argv):
+ do(**vars(_parse_args(args)))
+
+if __name__ == '__main__':
+ main()