Added the option to pass filter parameters from command line and config, reworked most filters to match.

src/filters.py

@@ -10,16 +10,25 @@ import cv2 as cv
 
 # Parent class for all the filters
 class filter:
+    '''
+    Parent class for all the filters
+    '''
     def __init__(self, img):
         self.img = img
 
 
-class average(filter):
+class convolve(filter):
+    ''' Convolve using custom kernel, 
+    if no kernel is given, use default 3x3 kernel for averaging'''  
     def __init__(self, img):
         super().__init__(img)
 
-    def apply(self):
-        kernel = np.ones((3, 3), np.float32) / 9
+    def apply(self, params):
+        # Set default values
+        ksize = int(params["ksize"]) if params["ksize"] else 3
+        kernel = np.array(params["kernel"]) if params["kernel"] else np.ones((ksize, ksize), np.float32) / np.sqrt(ksize)
+
+        #print("with params: " + " ksize: " + str(ksize) + " kernel: \n" + str(kernel))
         self.img = cv.filter2D(self.img, -1, kernel)
 
 
@@ -27,88 +36,111 @@ class blur(filter):
     def __init__(self, img):
         super().__init__(img)
 
-    def apply(self):
-        self.img = cv.blur(self.img, (3, 3))
+    def apply(self, params):
+        # Set default values
+        if(params["anchor"]):
+            try:
+                anchor = tuple(map(int, params["anchor"].split(',')))
+            except AttributeError:
+                anchor = tuple(params["anchor"])
+        else:
+            anchor = (-1, -1)
+        ksize = int(params["ksize"]) if params["ksize"] else 3
+
         
+        #print("with params: " + " ksize: " + str(ksize) + " anchor: " + str(anchor))
+        self.img = cv.blur(self.img, ksize=(ksize, ksize), anchor=anchor)
 
 class gaussian(filter):
     def __init__(self, img):
         super().__init__(img)
 
-    def apply(self):
-        self.img = cv.GaussianBlur(self.img, (3, 3), 0)
+    def apply(self, params):
+        # Set default values
+        ksize = int(params["ksize"]) if params["ksize"] else 3
+        sigmaX = float(params["sigmaX"]) if params["sigmaX"] else 0
+        sigmaY = float(params["sigmaY"]) if params["sigmaY"] else 0
+
+        #print("with params: " + " ksize: " + str(ksize) + " sigmaX: " + str(sigmaX) + " sigmaY: " + str(sigmaY))
+        self.img = cv.GaussianBlur(self.img, (ksize, ksize), sigmaX, sigmaY)
 
 
 class median(filter):
     def __init__(self, img):
         super().__init__(img)
 
-    def apply(self):
-        self.img = cv.medianBlur(self.img, 1)
+    def apply(self, params):
+        # Set default values
+        ksize = int(params["ksize"]) if params["ksize"] else 3
+
+        #print("with params: " + " ksize: " + str(ksize))
+        self.img = cv.medianBlur(self.img, ksize)
 
 
 class bilateral(filter):
     def __init__(self, img):
         super().__init__(img)
 
-    def apply(self):
-        self.img = cv.bilateralFilter(self.img, 1, 75, 75)
+    def apply(self, params):
+        # Set default values
+        d = int(params["d"]) if params["d"] else 1
+        sigmaColor = int(params["sigmaColor"]) if params["sigmaColor"] else 75
+        sigmaSpace = int(params["sigmaSpace"]) if params["sigmaSpace"] else 75
+
+        #print("with params: " + " d: " + str(d) + " sigmaColor: " + str(sigmaColor) + " sigmaSpace: " + str(sigmaSpace))
+        self.img = cv.bilateralFilter(self.img, d, sigmaColor, sigmaSpace)
 
 
 class denoise(filter):
     def __init__(self, img):
         super().__init__(img)
 
-    def apply(self):
-        pass
-        #does not work
+    def apply(self, params):
+        # Set default values
+        h = int(params["h"]) if params["h"] else 20
+        tWS = int(params["templateWindowSize"]) if params["templateWindowSize"] else 7
+        sWS = int(params["searchWindowSize"]) if params["searchWindowSize"] else 21
+
+        #print("with params: " + " h: " + str(h) + " tWS: " + str(tWS) + " sWS: " + str(sWS))
         self.img = np.uint8(self.img)
-        self.img = cv.fastNlMeansDenoising(
-            self.img, h=10, searchWindowSize=21, templateWindowSize=7)
+        self.img = cv.fastNlMeansDenoising(self.img, h, tWS, sWS)
 
 
 class sharpen(filter):
     def __init__(self, img):
         super().__init__(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):
-    def __init__(self, img):
-        super().__init__(img)
+    def apply(self, params):
+        # Set default values
+        kernel = np.matrix(params["kernel"]) if params["kernel"] else np.array(
+            [[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
 
-    def apply(self):
-        kernel = np.ones((3, 3), np.uint8)
-        self.img = cv.erode(self.img, kernel, 1)
-
-
-class dilate(filter):
-    def __init__(self, img):
-        super().__init__(img)
-
-    def apply(self):
-        kernel = np.ones((3, 3), np.uint8)
-        self.img = cv.dilate(self.img, kernel, 1)
-
-
-# Erosion, then dilatation
-class opening(filter):
-    def __init__(self, img):
-        super().__init__(img)
+        #print("with params: " + " kernel: \n" + str(kernel))
+        self.img = cv.filter2D(self.img, ddepth=-1, kernel=kernel)
 
-    def apply(self):
-        kernel = cv.getStructuringElement(cv.MORPH_RECT, (3, 3))
-        self.img = cv.morphologyEx(self.img, cv.MORPH_CLOSE, kernel)
 
+class morph(filter):
+    ''' General morphological operations.
 
-# Dilatation, then erosion
-class closing(filter):
+    Can be used with MORPH_OPEN, MORPH_CLOSE, MORPH_DILATE, MORPH_ERODE as op.
+    '''
     def __init__(self, img):
         super().__init__(img)
 
-    def apply(self):
-        kernel = cv.getStructuringElement(cv.MORPH_RECT, (3, 3))
-        self.img = cv.morphologyEx(self.img, cv.MORPH_OPEN, kernel)
+    def apply(self, params):
+        # Set default values
+        kernel = np.matrix(params["kernel"]) if params["kernel"] else np.ones((3, 3), np.uint8)
+        iterations = int(params["iterations"]) if params["iterations"] else 1
+        op = getattr(cv, params["op"]) if params["op"] else cv.MORPH_OPEN
+        if(params["anchor"]):
+            try:
+                anchor = tuple(map(int, params["anchor"].split(',')))
+            except AttributeError:
+                anchor = tuple(params["anchor"])
+        else:
+            anchor = (-1, -1)
+
+
+        #print("with params: " + " kernel: \n" + str(kernel) + " anchor: " + str(anchor) + " iterations: " + str(iterations) + " op: " + str(op))
+        self.img = cv.morphologyEx(
+            self.img, op=op, kernel=kernel, anchor=anchor, iterations=iterations)

src/main.py

@@ -23,29 +23,42 @@ class apply_filters:
     def __init__(self):
         # Parse arguments from command line
         self.parse_arguments()
-        self.input_file = self.args.input_file
-        self.output_file = self.args.output_file
-        self.dpi = self.args.dpi
-        self.filters = self.args.filters
-        self.mirror = self.args.mirror if self.args.mirror else 0
+        self.params = {}
+        self.filters = []
         
         # Parse configuration from json file
         if self.args.config:
             self.config_file = self.args.config[0]
             self.preset_name = self.args.config[1]
             self.config = json.load(open(self.config_file))
+            print("Config loaded")
             self.parse_conf()
 
         # If no config file given, expect filters in command line
         else:
-            self.filters = self.args.filters
+            print("No config file given, using command line arguments")
+            i = 0
+            for filter in self.args.filters:
+                if filter.find('=') == -1:
+                    self.filters.append(filter)
+                    i += 1
+                    self.params[i] = {}
+                else:
+                    key, value = filter.split('=')
+                    self.params[i][key] = value
+                self.parse_params(self.params[i])
+
+        self.input_file = self.args.input_file
+        self.output_file = self.args.output_file
+        self.dpi = self.args.dpi
+        self.mirror = self.args.mirror if self.args.mirror else 0
 
         #read as numpy.array
-        self.img = plt.imread(self.input_file)
+        self.img = cv.imread(self.input_file, cv.IMREAD_GRAYSCALE)
     
         self.width = self.img.shape[1]
         self.height = self.img.shape[0]
-        print(self.width, self.height)
+        #print(self.width, self.height)
         
         fig = plt.figure(figsize = (self.width, self.height), 
             frameon = False, dpi = self.dpi / 100) # dpi is in cm
@@ -57,14 +70,38 @@ class apply_filters:
         if self.mirror:
             self.mirror_image()
 
-        # Apply all filters
-        self.apply_filter(fig, ax)
+        # Apply all filters and save image
+        self.apply_filter()
+        self.save_image(fig, ax)
+
+
+    def check_param(self, params, key):
+        try:
+            params[key] = params[key]
+        except KeyError:
+            params[key] = None
+
+
+    def parse_params(self, params):
+        possible_params = {"h", "searchWindowSize","templateWindowSize", 
+                            "ksize", "kernel", "sigmaX" , "sigmaY",
+                           "sigmaColor", "sigmaSpace", "d", "anchor", "iterations", "op"}
+        for key in possible_params:
+            self.check_param(params, key)
 
 
     def parse_conf(self):
         # Parse configuration file if given.
         try:
-            self.filters = self.config[self.preset_name]
+            filter_array = self.config[self.preset_name]
+            for i, filter in enumerate(range(len(filter_array)), start=1):
+                self.filters.append(filter_array[filter]["name"])
+                self.params[i] = {}
+                for attribute, value in filter_array[filter].items():
+                    if attribute != "name":
+                        self.params[i][attribute] = value
+                self.parse_params(self.params[i])
+
         except(KeyError):
             print("Preset not found", file = sys.stderr)
 
@@ -72,25 +109,27 @@ class apply_filters:
     def parse_arguments(self):
 
         # Parse arguments
-        parser = ap.ArgumentParser(prog = 'main.py', description = 
-            'Program for processing a 2D image into 3D fingerprint.')
+        parser = ap.ArgumentParser(prog = 'main.py', 
+            description = 'Program for processing a 2D image into 3D fingerprint.', 
+                                   usage='%(prog)s [-h] [-m | --mirror | --no-mirror] input_file output_file dpi ([-c config_file preset | --config config_file preset] | [filters ...])')
 
         # positional arguments
-        parser.add_argument("input_file", type = str, help = "Location with input file")
-        parser.add_argument("output_file", type = str, help = "Output file location")
-        parser.add_argument("dpi", type = int, help = "Scanner dpi")
+        parser.add_argument("input_file", type = str, help = "location with input file")
+        parser.add_argument("output_file", type = str, help = "output file location")
+        parser.add_argument("dpi", type = int, help = "scanner dpi")
 
         # boolean switch
-        parser.add_argument('-m', "--mirror", help = "Mirror input image",
+        parser.add_argument('-m', "--mirror", help = "mirror input image",
                             type = bool, action = ap.BooleanOptionalAction)
 
         # file with configuration containing presets, new preset name
         # pair argument - give both or none
-        parser.add_argument('--config', nargs=2, metavar=('config_file', 'preset'),
-                            help='Config file with presets, name of the preset')
+        parser.add_argument('-c','--config', nargs = 2, metavar = ('config_file', 'preset'),
+                            help = 'pair: name of the config file with presets, name of the preset')
 
         # array of unknown length, all filter names saved inside
-        parser.add_argument('filters', type = str, nargs = '*', help = "List of filter names")
+        parser.add_argument('filters', type = str, nargs = '*',
+                            help="list of filter names and their parameters in form [filter_name1 param1=value1 param2=value2 filter_name2 param1=value1...]")
 
         self.args = parser.parse_args()
 
@@ -104,10 +143,7 @@ class apply_filters:
 
     def resize_image(self):
 
-        # open image as python image object
         print("Resize image", file = sys.stderr)
-
-        self.convert_dpi()
         self.img = self.img.resize((np.array(self.width, self.height)).astype(int))
 
 
@@ -119,16 +155,16 @@ class apply_filters:
         self.img = cv.flip(self.img, 1)  # 1 for vertical mirror
 
 
-    def apply_filter(self, fig, ax):
+    def apply_filter(self):
 
         if len(self.filters) == 0:
             # No filter given, just save the image
             pass
         else:
-            for filter_name in self.filters:
+            # Apply all filters
+            for i, filter_name in enumerate(self.filters):
                 filter = self.filter_factory(filter_name)
-                filter.apply(self)
-        self.save_image(fig, ax)
+                filter.apply(self, self.params[i+1])
         
 
     def print_size(self, size):
@@ -139,7 +175,7 @@ class apply_filters:
     def save_image(self, fig, ax):
         # Save processed image.
         print("Saving image", file = sys.stderr)
-        ax.imshow(self.img)
+        ax.imshow(self.img, cmap="gray")
         fig.savefig(fname=self.output_file)