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