Added more filters.

src/filters.py

@@ -4,7 +4,7 @@
 """
 
 import numpy as np
-import matplotlib.pyplot as plt
+#import matplotlib.pyplot as plt
 import cv2 as cv
 
 
@@ -15,26 +15,14 @@ class filter:
         self.output_file = output_file
         self.img = img
 
-# Used when no other filters are present, plots original image, 
-# may not be necessary
-class filter_none(filter):
-    def __init__(self, input_file, output_file, img):
-        super().__init__(input_file, output_file, img)
-
-    def apply(self):
-        plt.imshow(self.img)
-        print("No filter selected")
-
 
 class average(filter):
     def __init__(self, input_file, output_file, img):
         super().__init__(input_file, output_file, img)
 
     def apply(self):
-        kernel = np.ones((5, 5), np.float32) / 25
+        kernel = np.ones((3, 3), np.float32) / 9
         self.img = cv.filter2D(self.img, -1, kernel)
-        plt.imshow(self.img)
-        print("Applying average filter")
 
 
 class blur(filter):
@@ -42,9 +30,7 @@ class blur(filter):
         super().__init__(input_file, output_file, img)
 
     def apply(self):
-        self.img = cv.blur(self.img, (5, 5))
+        self.img = cv.blur(self.img, (3, 3))
-        plt.imshow(self.img)
-        print("Applying normal blur")
 
 
 class gaussian(filter):
@@ -52,9 +38,7 @@ class gaussian(filter):
         super().__init__(input_file, output_file, img)
 
     def apply(self):
-        self.img = cv.GaussianBlur(self.img, (5, 5), 0)
+        self.img = cv.GaussianBlur(self.img, (3, 3), 0)
-        plt.imshow(self.img)
-        print("Applying Gaussian blur")
 
 
 class median(filter):
@@ -62,9 +46,35 @@ class median(filter):
         super().__init__(input_file, output_file, img)
 
     def apply(self):
-        self.img = cv.medianBlur(self.img, 5)
+        self.img = cv.medianBlur(self.img, 1)
-        plt.imshow(self.img)
+
-        print("Applying median blur")
+
+class bilateral(filter):
+    def __init__(self, input_file, output_file, img):
+        super().__init__(input_file, output_file, img)
+
+    def apply(self):
+        self.img = cv.bilateralFilter(self.img, 1, 75, 75)
+
+
+class denoise(filter):
+    def __init__(self, input_file, output_file, img):
+        super().__init__(input_file, output_file, img)
+
+    def apply(self):
+        pass
+        #does not work
+        #img = cv.cvtColor(self.img, cv.COLOR_GRAY2BGR)
+        #self.img = cv.fastNlMeansDenoisingColored(img, h=3)
+
+
+class sharpen(filter):
+    def __init__(self, input_file, output_file, img):
+        super().__init__(input_file, output_file, img)
+
+    def apply(self):
+        kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
+        self.img = cv.filter2D(self.img, ddepth=-1, kernel=kernel)
 
 
 class erode(filter):
@@ -72,10 +82,8 @@ class erode(filter):
         super().__init__(input_file, output_file, img)
 
     def apply(self):
-        kernel = np.ones((5, 5), np.uint8)
+        kernel = np.ones((3, 3), np.uint8)
         self.img = cv.erode(self.img, kernel, 1)
-        plt.imshow(self.img)
-        print("Applying erosion")
 
 
 class dilate(filter):
@@ -83,10 +91,8 @@ class dilate(filter):
         super().__init__(input_file, output_file, img)
 
     def apply(self):
-        kernel = np.ones((5, 5), np.uint8)
+        kernel = np.ones((3, 3), np.uint8)
         self.img = cv.dilate(self.img, kernel, 1)
-        plt.imshow(self.img)
-        print("Applying dilatation")
 
 
 # Erosion, then dilatation
@@ -97,8 +103,6 @@ class opening(filter):
     def apply(self):
         kernel = cv.getStructuringElement(cv.MORPH_RECT, (3, 3))
         self.img = cv.morphologyEx(self.img, cv.MORPH_CLOSE, kernel)
-        plt.imshow(self.img)
-        print("Applying opening")
 
 
 # Dilatation, then erosion
@@ -109,5 +113,3 @@ class closing(filter):
     def apply(self):
         kernel = cv.getStructuringElement(cv.MORPH_RECT, (3, 3))
         self.img = cv.morphologyEx(self.img, cv.MORPH_OPEN, kernel)
-        plt.imshow(self.img)
-        print("Applying closing")