Filters now all convert image to uint_8 after application.

src/filters.py

@@ -41,6 +41,7 @@ class gaussian(img_filter):
 
         self.img = skiflt.gaussian(
             self.img, sigma=sigma, preserve_range=True)
+        self.img = np.uint8(self.img)
 
 
 class median(img_filter):
@@ -56,7 +57,9 @@ class median(img_filter):
         # Used kernel is disk of size ksize
         ksize = int(params["ksize"]) if params["ksize"] else 3
 
+        
         self.img = skiflt.median(self.img, footprint=skimorph.disk(ksize))
+        self.img = np.uint8(self.img)
 
 
 class bilateral(img_filter):
@@ -175,6 +178,8 @@ class block_match(img_filter):
 
         self.img = bm3d.bm3d(self.img, sigma_psd=sigma,
                              stage_arg=bm3d.BM3DStages.ALL_STAGES)
+        self.img = np.uint8(self.img)
+
 
 
 class unsharp_mask_scikit(img_filter):
@@ -199,6 +204,30 @@ class unsharp_mask_scikit(img_filter):
                                        amount=amount, channel_axis=None)
         self.img = np.uint8(self.img * 255.0)  # converting back to uint
 
+
+class unsharp_mask_pil(img_filter):
+    ''' Unsharp mask filter from PIL.
+    '''
+
+    def __init__(self, img):
+        super().__init__(img)
+
+    def apply(self, params):
+
+        # Blur radius
+        radius = int(params["radius"]) if params["radius"] else 2
+
+        # Unsharp strength in percent
+        percent = int(params["percent"]) if params["percent"] else 150
+
+        # Threshold controls the minimum brightness change that will be sharpened
+        threshold = int(params["threshold"]) if params["threshold"] else 3
+
+        self.img = np.uint8(self.img)
+        tmp = Image.fromarray(self.img)
+        tmp = tmp.filter(ImageFilter.UnsharpMask(radius, percent, threshold))
+        self.img = np.uint8(np.asarray(tmp))
+
 # ------------------- EDGE DETECTION FILTERS -------------------#
 
 
@@ -213,6 +242,8 @@ class farid(img_filter):
     def apply(self, _):
 
         self.img = skiflt.farid(self.img)
+        self.img = np.uint8(self.img)
+
 
 # ------------------ RIDGE EXTRACTION FILTERS ------------------#
 
@@ -270,6 +301,8 @@ class invert(img_filter):
 
     def apply(self, _):
         self.img = cv.bitwise_not(self.img)
+        self.img = np.uint8(self.img)
+
 
 
 class scale_values(img_filter):
@@ -290,6 +323,7 @@ class scale_values(img_filter):
         self.img = cv.bitwise_not(tmp.astype(np.uint8))
         coef = 255 / np.max(tmp)
         tmp = tmp * coef
+        self.img = np.uint8(tmp)
 
 
 class binarize(img_filter):
@@ -300,6 +334,8 @@ class binarize(img_filter):
         threshold = int(params["threshold"]) if params["threshold"] else 128
 
         self.img = cv.threshold(self.img, threshold, 255, cv.THRESH_BINARY)[1]
+        self.img = np.uint8(self.img)
+
 
 
 class binarize_otsu(img_filter):
@@ -310,6 +346,8 @@ class binarize_otsu(img_filter):
     
     def apply(self, _):
         self.img = cv.threshold(self.img, 0, 255, cv.THRESH_BINARY + cv.THRESH_OTSU)[1]
+        self.img = np.uint8(self.img)
+
 
 
 class add_margin(img_filter):
@@ -325,6 +363,8 @@ class add_margin(img_filter):
         self.img = cv.copyMakeBorder(
             self.img, margin, margin, margin, margin, cv.BORDER_CONSTANT, value=color)
         self.height, self.width = self.img.shape
+        self.img = np.uint8(self.img)
+
 
 # ---------------------- MORPHOLOGICAL OPS --------------------------#
 
@@ -345,6 +385,8 @@ class erode(img_filter):
 
         self.img = cv.morphologyEx(
             np.uint8(self.img), op=cv.MORPH_ERODE, kernel=kernel)
+        self.img = np.uint8(self.img)
+
 
 class dilate(img_filter):
     ''' General morphological operations from OpenCV.
@@ -363,32 +405,4 @@ class dilate(img_filter):
 
         self.img = cv.morphologyEx(
             np.uint8(self.img), op=cv.MORPH_DILATE, kernel=kernel)
-
-
-# ---------------------- OLD --------------------------#
-
-
-# TODO: REVISE, REMOVE unused filters
-
-class unsharp_mask_pil(img_filter):
-    ''' Unsharp mask filter from PIL.
-    '''
-
-    def __init__(self, img):
-        super().__init__(img)
-
-    def apply(self, params):
-
-        # Blur radius
-        radius = int(params["radius"]) if params["radius"] else 2
-
-        # Unsharp strength in percent
-        percent = int(params["percent"]) if params["percent"] else 150
-
-        # Threshold controls the minimum brightness change that will be sharpened
-        threshold = int(params["threshold"]) if params["threshold"] else 3
-
         self.img = np.uint8(self.img)
-        tmp = Image.fromarray(self.img)
-        tmp = tmp.filter(ImageFilter.UnsharpMask(radius, percent, threshold))
-        self.img = np.asarray(tmp)