From dc549357af9af5240ec1684efc990d2b3c337b9b Mon Sep 17 00:00:00 2001
From: Egor Tensin <Egor.Tensin@gmail.com>
Date: Mon, 29 Aug 2016 02:52:02 +0300
Subject: initial commit

---
 shift.py | 112 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 112 insertions(+)
 create mode 100644 shift.py

(limited to 'shift.py')

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()
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