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Preprocess.py

+import cv2
+import numpy as np
+import math
+
+GAUSSIAN_SMOOTH_FILTER_SIZE = (5, 5)
+ADAPTIVE_THRESH_BLOCK_SIZE = 19
+ADAPTIVE_THRESH_WEIGHT = 9
+
+def preprocess(imgOriginal):
+    imgGrayscale = extractValue(imgOriginal)
+
+    imgMaxContrastGrayscale = maximizeContrast(imgGrayscale)
+
+    height, width = imgGrayscale.shape
+
+    imgBlurred = np.zeros((height, width, 1), np.uint8)
+
+    imgBlurred = cv2.GaussianBlur(imgMaxContrastGrayscale, GAUSSIAN_SMOOTH_FILTER_SIZE, 0)
+
+    imgThresh = cv2.adaptiveThreshold(imgBlurred, 255.0, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, ADAPTIVE_THRESH_BLOCK_SIZE, ADAPTIVE_THRESH_WEIGHT)
+
+    return imgGrayscale, imgThresh
+
+def extractValue(imgOriginal):
+    height, width, numChannels = imgOriginal.shape
+
+    imgHSV = np.zeros((height, width, 3), np.uint8)
+
+    imgHSV = cv2.cvtColor(imgOriginal, cv2.COLOR_BGR2HSV)
+
+    imgHue, imgSaturation, imgValue = cv2.split(imgHSV)
+
+    return imgValue
+
+def maximizeContrast(imgGrayscale):
+
+    height, width = imgGrayscale.shape
+
+    imgTopHat = np.zeros((height, width, 1), np.uint8)
+    imgBlackHat = np.zeros((height, width, 1), np.uint8)
+
+    structuringElement = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
+
+    imgTopHat = cv2.morphologyEx(imgGrayscale, cv2.MORPH_TOPHAT, structuringElement)
+    imgBlackHat = cv2.morphologyEx(imgGrayscale, cv2.MORPH_BLACKHAT, structuringElement)
+
+    imgGrayscalePlusTopHat = cv2.add(imgGrayscale, imgTopHat)
+    imgGrayscalePlusTopHatMinusBlackHat = cv2.subtract(imgGrayscalePlusTopHat, imgBlackHat)
+
+    return imgGrayscalePlusTopHatMinusBlackHat
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