Added filter parameters to readme.

src/filters.py

@@ -8,9 +8,10 @@ import cv2 as cv
 from skimage import filters as skiflt
 from skimage import restoration as skirest
 from skimage import morphology as skimorph
-# from scipy import signal as sig
+from scipy import ndimage
 from PIL import Image, ImageFilter
 import bm3d
+import matplotlib.pyplot as plt
 
 
 class filter:
@@ -133,7 +134,7 @@ class nlmeans(filter):
         # Size of patches used for denoising
         patch_size = int(params["patch_size"]) if params["patch_size"] else 5
 
-        # Distance in pixels where to search patches
+        # Distance in pixels where to search for patches
         patch_distance = int(params["patch_distance"]
                              ) if params["patch_distance"] else 3
 
@@ -210,7 +211,7 @@ class unsharp_mask_scikit(filter):
               str(radius) + " amount: " + str(amount))
         self.img = skiflt.unsharp_mask(self.img, radius=radius,
                                        amount=amount, channel_axis=None)
-        self.img = np.uint8(self.img * 255.0)  # converting back to uintknapsack
+        self.img = np.uint8(self.img * 255.0)  # converting back to uint
 
 # ------------------- EDGE DETECTION FILTERS -------------------#
 
@@ -319,6 +320,16 @@ class binarize(filter):
         self.img = cv.threshold(self.img, threshold, maxval, type)[1]
 
 
+class binarize_otsu(filter):
+    ''' Otsu binarization filter from opencv.
+    '''
+    def init(self, img):
+        super().__init__(img)
+    
+    def apply(self, _):
+        self.img = cv.threshold(self.img, 0, 255, cv.THRESH_BINARY + cv.THRESH_OTSU)[1]
+
+
 class add_margin(filter):
     def init(self, img):
         super().__init__(img)

src/main.py

@@ -122,7 +122,7 @@ class app:
         # TODO: possibly too bloated, sending all possible params to each filter
         # TODO: remove unnecessary params
         possible_params = {"h", "searchWindowSize", "templateWindowSize",
-                           "ksize", "kernel",
+                           "ksize", "kernel", "angle",
                            "sigmaColor", "sigmaSpace", "diameter", "anchor", "iterations",
                            "op", "strength", "amount", "radius", "weight", "channelAxis",
                            "theta", "sigma", "lambd", "gamma", "psi", "shape", "percent",
@@ -610,8 +610,7 @@ class app:
         '''Map fingerprint to finger model.
         '''
 
-        # TODO: this might be done in a better way
-        # instead of summing up the values, use their product - 0 ?
+        # TODO: this might be done in a better way, comment
         z = np.array([])
         for x in range(self.width):
             z = np.append(z, np.sqrt(1 - (2*x/self.width - 1)**2)