Inokova Evita

filter.py

@@ -1,28 +1,33 @@
 from PIL import Image
 import numpy as np
-img = Image.open("img2.jpg")
+img = Image.open(input("Enter image you want to change: "))
+result_img = input("Enter image to write your result onto: ")
 arr = np.array(img)
-a = len(arr)
-a1 = len(arr[1])
-i = 0
-while i < a - 11:
-    j = 0
-    while j < a1 - 11:
-        s = 0
-        for n in range(i, i + 10):
-            for n1 in range(j, j + 10):
-                n1 = arr[n][n1][0]
-                n2 = arr[n][n1][1]
-                n3 = arr[n][n1][2]
-                M = n1 + n2 + n3
-                s += M
-        s = int(s // 100)
-        for n in range(i, i + 10):
-            for n1 in range(j, j + 10):
-                arr[n][n1][0] = int(s // 50) * 50
-                arr[n][n1][1] = int(s // 50) * 50
-                arr[n][n1][2] = int(s // 50) * 50
-        j = j + 10
-    i = i + 10
-res = Image.fromarray(arr)
-res.save('res.jpg')
+height = len(arr)
+width = len(arr[1])
+size = int(input("Enter size: "))
+gradation = int(input("Enter gradation: "))
+step = int(255 / gradation)
+
+class Grey:
+  def __init__(self, step, height, width, size, arr):
+    self.step = step
+    self.height = height
+    self.width = width
+    self.size = size
+    self.arr = arr
+  def getGrey(self):
+    i = 0
+    while i < self.height:
+      j = 0
+      while j < self.width:
+        color_sum = np.sum((self.arr[i: i + self.size, j: j + self.size]) / 3)
+        average = int(color_sum // (self.size*self.size))
+        self.arr[i: i + self.size, j: j + self.size] = int(average // self.step) * self.step
+        j = j + self.size
+      i = i + self.size
+    return self.arr
+
+newPicture = Grey(step, height, width, size, arr)
+res = Image.fromarray(newPicture.getGrey())
+res.save(result_img)