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DetectPlates.py

+# DetectPlates.py
+
+import cv2
+import numpy as np
+import math
+import Main
+import random
+
+import Preprocess
+import DetectChars
+import PossiblePlate
+import PossibleChar
+
+PLATE_WIDTH_PADDING_FACTOR = 1.3
+PLATE_HEIGHT_PADDING_FACTOR = 1.5
+
+def detectPlatesInScene(imgOriginalScene):
+    listOfPossiblePlates = []                   
+
+    height, width, numChannels = imgOriginalScene.shape
+
+    imgGrayscaleScene = np.zeros((height, width, 1), np.uint8)
+    imgThreshScene = np.zeros((height, width, 1), np.uint8)
+    imgContours = np.zeros((height, width, 3), np.uint8)
+
+    cv2.destroyAllWindows()
+
+    if Main.showSteps == True: 
+        cv2.imshow("0", imgOriginalScene)
+    
+    imgGrayscaleScene, imgThreshScene = Preprocess.preprocess(imgOriginalScene)         
+
+    if Main.showSteps == True: 
+        cv2.imshow("1a", imgGrayscaleScene)
+        cv2.imshow("1b", imgThreshScene)
+    
+    listOfPossibleCharsInScene = findPossibleCharsInScene(imgThreshScene)
+
+    if Main.showSteps == True: 
+        print("step 2 - len(listOfPossibleCharsInScene) = " + str(
+            len(listOfPossibleCharsInScene)))  
+
+        imgContours = np.zeros((height, width, 3), np.uint8)
+
+        contours = []
+
+        for possibleChar in listOfPossibleCharsInScene:
+            contours.append(possibleChar.contour)
+        
+        cv2.drawContours(imgContours, contours, -1, Main.SCALAR_WHITE)
+        cv2.imshow("2b", imgContours)
+    
+    listOfListsOfMatchingCharsInScene = DetectChars.findListOfListsOfMatchingChars(listOfPossibleCharsInScene)
+
+    if Main.showSteps == True: 
+        print("step 3 - listOfListsOfMatchingCharsInScene.Count = " + str(
+            len(listOfListsOfMatchingCharsInScene)))  
+
+        imgContours = np.zeros((height, width, 3), np.uint8)
+
+        for listOfMatchingChars in listOfListsOfMatchingCharsInScene:
+            intRandomBlue = random.randint(0, 255)
+            intRandomGreen = random.randint(0, 255)
+            intRandomRed = random.randint(0, 255)
+
+            contours = []
+
+            for matchingChar in listOfMatchingChars:
+                contours.append(matchingChar.contour)
+            
+            cv2.drawContours(imgContours, contours, -1, (intRandomBlue, intRandomGreen, intRandomRed))
+        
+        cv2.imshow("3", imgContours)
+    
+    for listOfMatchingChars in listOfListsOfMatchingCharsInScene:                   
+        possiblePlate = extractPlate(imgOriginalScene, listOfMatchingChars)         
+
+        if possiblePlate.imgPlate is not None:                          
+            listOfPossiblePlates.append(possiblePlate)                  
+        
+
+    print("\n" + str(len(listOfPossiblePlates)) + " possible plates found")  
+
+    if Main.showSteps == True:
+        print("\n")
+        cv2.imshow("4a", imgContours)
+
+        for i in range(0, len(listOfPossiblePlates)):
+            p2fRectPoints = cv2.boxPoints(listOfPossiblePlates[i].rrLocationOfPlateInScene)
+
+            cv2.line(imgContours, tuple(p2fRectPoints[0]), tuple(p2fRectPoints[1]), Main.SCALAR_RED, 2)
+            cv2.line(imgContours, tuple(p2fRectPoints[1]), tuple(p2fRectPoints[2]), Main.SCALAR_RED, 2)
+            cv2.line(imgContours, tuple(p2fRectPoints[2]), tuple(p2fRectPoints[3]), Main.SCALAR_RED, 2)
+            cv2.line(imgContours, tuple(p2fRectPoints[3]), tuple(p2fRectPoints[0]), Main.SCALAR_RED, 2)
+
+            cv2.imshow("4a", imgContours)
+
+            print("possible plate " + str(i) + ", click on any image and press a key to continue . . .")
+
+            cv2.imshow("4b", listOfPossiblePlates[i].imgPlate)
+            cv2.waitKey(0)
+
+        print("\nplate detection complete, click on any image and press a key to begin char recognition . . .\n")
+        cv2.waitKey(0)
+    
+    
+    return listOfPossiblePlates
+
+def findPossibleCharsInScene(imgThresh):
+    listOfPossibleChars = []                
+    
+    intCountOfPossibleChars = 0
+
+    imgThreshCopy = imgThresh.copy()
+
+    contours, npaHierarchy = cv2.findContours(imgThreshCopy, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)   
+
+    height, width = imgThresh.shape
+    imgContours = np.zeros((height, width, 3), np.uint8)
+
+    for i in range(0, len(contours)):                       
+
+        if Main.showSteps == True: 
+            cv2.drawContours(imgContours, contours, i, Main.SCALAR_WHITE)
+        
+        possibleChar = PossibleChar.PossibleChar(contours[i])
+
+        if DetectChars.checkIfPossibleChar(possibleChar):                   
+            intCountOfPossibleChars = intCountOfPossibleChars + 1           
+            listOfPossibleChars.append(possibleChar)                        
+
+    if Main.showSteps == True: 
+        print("\nstep 2 - len(contours) = " + str(len(contours)))  
+        print("step 2 - intCountOfPossibleChars = " + str(intCountOfPossibleChars))  
+        cv2.imshow("2a", imgContours)
+        
+    return listOfPossibleChars
+
+def extractPlate(imgOriginal, listOfMatchingChars):
+    possiblePlate = PossiblePlate.PossiblePlate()           
+    
+    listOfMatchingChars.sort(key = lambda matchingChar: matchingChar.intCenterX)        
+    
+    fltPlateCenterX = (listOfMatchingChars[0].intCenterX + listOfMatchingChars[len(listOfMatchingChars) - 1].intCenterX) / 2.0
+    fltPlateCenterY = (listOfMatchingChars[0].intCenterY + listOfMatchingChars[len(listOfMatchingChars) - 1].intCenterY) / 2.0
+
+    ptPlateCenter = fltPlateCenterX, fltPlateCenterY
+
+
+    intPlateWidth = int((listOfMatchingChars[len(listOfMatchingChars) - 1].intBoundingRectX + listOfMatchingChars[len(listOfMatchingChars) - 1].intBoundingRectWidth - listOfMatchingChars[0].intBoundingRectX) * PLATE_WIDTH_PADDING_FACTOR)
+
+    intTotalOfCharHeights = 0
+
+    for matchingChar in listOfMatchingChars:
+        intTotalOfCharHeights = intTotalOfCharHeights + matchingChar.intBoundingRectHeight
+    
+    
+    fltAverageCharHeight = intTotalOfCharHeights / len(listOfMatchingChars)
+
+    intPlateHeight = int(fltAverageCharHeight * PLATE_HEIGHT_PADDING_FACTOR)
+
+    fltOpposite = listOfMatchingChars[len(listOfMatchingChars) - 1].intCenterY - listOfMatchingChars[0].intCenterY
+    fltHypotenuse = DetectChars.distanceBetweenChars(listOfMatchingChars[0], listOfMatchingChars[len(listOfMatchingChars) - 1])
+    fltCorrectionAngleInRad = math.asin(fltOpposite / fltHypotenuse)
+    fltCorrectionAngleInDeg = fltCorrectionAngleInRad * (180.0 / math.pi)
+
+    possiblePlate.rrLocationOfPlateInScene = ( tuple(ptPlateCenter), (intPlateWidth, intPlateHeight), fltCorrectionAngleInDeg )
+
+    rotationMatrix = cv2.getRotationMatrix2D(tuple(ptPlateCenter), fltCorrectionAngleInDeg, 1.0)
+
+    height, width, numChannels = imgOriginal.shape      
+
+    imgRotated = cv2.warpAffine(imgOriginal, rotationMatrix, (width, height))       
+
+    imgCropped = cv2.getRectSubPix(imgRotated, (intPlateWidth, intPlateHeight), tuple(ptPlateCenter))
+
+    possiblePlate.imgPlate = imgCropped         
+
+    return possiblePlate
+
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