Finish 2.2.1 exercise 1

CV-App/algorithms/invis_cloak.py

@@ -1,11 +1,10 @@
-import cv2
+import cv2, datetime, os
 import numpy as np
 from copy import deepcopy
 from matplotlib import pyplot as plt
 
 from . import Algorithm
 
-
 class InvisCloak (Algorithm):
 
     """ init function """
@@ -20,6 +19,15 @@ class InvisCloak (Algorithm):
         # Includes noice reduction and histogram spread
         self.middle_value_picture = None
 
+        # Clean up results folder
+        folder_path = os.path.join("results")
+
+        for filename in os.listdir(folder_path):
+            file_path = os.path.join(folder_path, filename)
+
+            if os.path.isfile(file_path):
+                os.unlink(file_path)
+
 
     """ Processes the input image"""
     def process(self, img):
@@ -38,12 +46,12 @@ class InvisCloak (Algorithm):
 
         """ 2.2 Farbanalyse """
         """ 2.2.1 RGB """
-        self._221_RGB(img)
+        #self._221_RGB(img)
         """ 2.2.2 HSV """
-        self._222_HSV(img)
+        #self._222_HSV(img)
 
 
-        """ 2.3 Segmentierung und Bildmdifikation """
+        """ 2.3 Segmentierung und Bildmodifikation """
         img = self._23_SegmentUndBildmodifizierung(img)
 
         return img
@@ -53,6 +61,14 @@ class InvisCloak (Algorithm):
         if event == cv2.EVENT_LBUTTONUP:
             print("A Mouse click happend! at position", x, y)
 
+            # Stores the current image to data folder
+            cv2.imwrite(f"results/{datetime.datetime.now().strftime('%Y-%m-%d_%H:%M:%S')}_captured_image.png",
+                        self.picture_buffer[4])
+
+            # Create RGB histogram
+            self._221_RGB(self.middle_value_picture)
+
+
     def _plotNoise(self, img, name:str):
         height, width = np.array(img.shape[:2])
         centY = (height / 2).astype(int)
@@ -112,12 +128,21 @@ class InvisCloak (Algorithm):
         return self.middle_value_picture
 
 
-    def _221_RGB(self, img):
+    def _221_RGB(self, img, colorspectrum = "bgr"):
         """
             Hier steht Ihr Code zu Aufgabe 2.2.1 (RGB)
             - Histogrammberechnung und Analyse
         """
-        pass
+        # Names of the color spectrums
+        channels = ["b", "g", "r"]
+
+        for index, channel_name in enumerate(channels):
+            hist = cv2.calcHist([img], [index], None, [256], [0, 256])
+            plt.plot(hist, color=channel_name)
+            plt.xlim([0, 256])
+
+        plt.savefig(f"results/{datetime.datetime.now().strftime('%Y-%m-%d_%H:%M:%S')}_histogram_{colorspectrum}.png")
+        plt.clf()
 
 
     def _222_HSV(self, img):