Initial commit with project files

4_Farbrepräsentationen/ü1/l_a.py

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+import numpy as np
+import cv2
+
+
+# Einlesen des Bildes
+filepath = "../../data/balls.png"
+img = cv2.imread(filepath)
+
+''' a) Manuelles Konvertieren '''
+img_norm = img.astype(np.float32) / 255.0
+height, width, channels = img.shape
+hsv_img = np.zeros_like(img_norm)
+
+for x in range(width):
+    for y in range(int(height)):
+        minimum = np.min(img_norm[y, x])
+        b, g, r = img_norm[y, x, 0], img_norm[y, x, 1], img_norm[y, x, 2]
+        # V Wert
+        v = np.max(img_norm[y, x].copy())
+
+        # S Wert
+        if v == 0:
+            s = 0
+        else:
+            s = (v - minimum) / v
+
+        # H Wert
+        max_channel_index = np.argmax(img_norm[y, x])
+        if (v - np.min(img_norm[y, x])) == 0:
+            h = np.zeros(1)
+        elif max_channel_index == 2:  # Rot
+            h = 60 * (g - b) / (v - minimum)
+        elif max_channel_index == 1:  # Grün
+            h = 120 + 60 * (b - r) / (v - minimum)
+        else:  # Blau
+            h = 240 + 60 * (r - g) / (v - minimum)
+        if h < 0:
+            h += 360
+        h /= (2 * 255)
+
+        hsv_img[y, x, 0] = h
+        hsv_img[y, x, 1] = s
+        hsv_img[y, x, 2] = v
+
+hsv_img = np.round(hsv_img * 255)
+hsv_img = hsv_img.astype(np.uint8)
+
+''' b) Konvertieren mit OpenCV '''
+hsv_img2 = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
+
+
+''' Das Ergebnis überprüfen '''
+img2 = cv2.cvtColor(hsv_img, cv2.COLOR_HSV2BGR)
+img3 = cv2.cvtColor(hsv_img2, cv2.COLOR_HSV2BGR)
+
+difference = np.sum(np.abs(img2 - img3))
+print("Totale Differenz zwischen den Ergebnissen:", difference)
+max_difference = np.max(np.abs(img2 - img3))
+print("Maximale Abweichung pro Pixel/Kanal:", max_difference)
+example_differences = img2[0:3, 0:3] - img3[0:3, 0:3]
+print("Beispiel Differenzen:\n", example_differences)
+
+cv2.imshow("ORIGINAL", img)
+cv2.imshow("MANUELL", img2)
+cv2.imshow("OPENCV", img3)
+cv2.waitKey(0)