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A system to automatically generate parking receipts by identifying the type of vehicle and storing the vehicle details using the registration number extracted out of the number place using computer vision.
sagarika4/Automatic_Fare_Calculator_System
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# Main.py import cv2 import numpy as np import os import DetectChars import DetectPlates import PossiblePlate # module level variables ########################################################################## SCALAR_BLACK = (0.0, 0.0, 0.0) SCALAR_WHITE = (255.0, 255.0, 255.0) SCALAR_YELLOW = (0.0, 255.0, 255.0) SCALAR_GREEN = (0.0, 255.0, 0.0) SCALAR_RED = (0.0, 0.0, 255.0) showSteps = False ################################################################################################### def recognize_license_plate(img_path): blnKNNTrainingSuccessful = DetectChars.loadKNNDataAndTrainKNN() # attempt KNN training if blnKNNTrainingSuccessful == False: # if KNN training was not successful print ("\nerror: KNN traning was not successful\n") # show error message return # and exit program # end if imgOriginalScene = cv2.imread(img_path) # open image if imgOriginalScene is None: # if image was not read successfully print ("\nerror: image not read from file \n\n" ) # print error message to std out os.system("pause") # pause so user can see error message return # and exit program # end if listOfPossiblePlates = DetectPlates.detectPlatesInScene(imgOriginalScene) # detect plates listOfPossiblePlates = DetectChars.detectCharsInPlates(listOfPossiblePlates) # detect chars in plates #cv2.imshow("imgOriginalScene", imgOriginalScene) # show scene image if len(listOfPossiblePlates) == 0: # if no plates were found print ("\n no license plates were detected\n") # inform user no plates were found) else: # else # if we get in here list of possible plates has at leat one plate # sort the list of possible plates in DESCENDING order (most number of chars to least number of chars) listOfPossiblePlates.sort(key = lambda possiblePlate: len(possiblePlate.strChars), reverse = True) # suppose the plate with the most recognized chars (the first plate in sorted by string length descending order) is the actual plate licPlate = listOfPossiblePlates[0] #cv2.imshow("imgPlate", licPlate.imgPlate) # show crop of plate and threshold of plate #cv2.imshow("imgThresh", licPlate.imgThresh) #if len(licPlate.strChars) == 0: # if no chars were found in the plate #print( "\nno characters were detected\n\n" ) # show message #return # and exit program # end if #drawRedRectangleAroundPlate(imgOriginalScene, licPlate) # draw red rectangle around plate #print ("\nlicense plate read from image = " + licPlate.strChars + "\n" ) # write license plate text to std out #print ("----------------------------------------") #writeLicensePlateCharsOnImage(imgOriginalScene, licPlate) # write license plate text on the image #cv2.imshow("imgOriginalScene", imgOriginalScene) # re-show scene image #cv2.imwrite("imgOriginalScene.png", imgOriginalScene) # write image out to file # end if else #cv2.waitKey(0) # hold windows open until user presses a key return licPlate # end main ################################################################################################### def drawRedRectangleAroundPlate(imgOriginalScene, licPlate): p2fRectPoints = cv2.boxPoints(licPlate.rrLocationOfPlateInScene) # get 4 vertices of rotated rect cv2.line(imgOriginalScene, tuple(p2fRectPoints[0]), tuple(p2fRectPoints[1]), SCALAR_RED, 2) # draw 4 red lines cv2.line(imgOriginalScene, tuple(p2fRectPoints[1]), tuple(p2fRectPoints[2]), SCALAR_RED, 2) cv2.line(imgOriginalScene, tuple(p2fRectPoints[2]), tuple(p2fRectPoints[3]), SCALAR_RED, 2) cv2.line(imgOriginalScene, tuple(p2fRectPoints[3]), tuple(p2fRectPoints[0]), SCALAR_RED, 2) # end function ################################################################################################### def writeLicensePlateCharsOnImage(imgOriginalScene, licPlate): ptCenterOfTextAreaX = 0 # this will be the center of the area the text will be written to ptCenterOfTextAreaY = 0 ptLowerLeftTextOriginX = 0 # this will be the bottom left of the area that the text will be written to ptLowerLeftTextOriginY = 0 sceneHeight, sceneWidth, sceneNumChannels = imgOriginalScene.shape plateHeight, plateWidth, plateNumChannels = licPlate.imgPlate.shape intFontFace = cv2.FONT_HERSHEY_SIMPLEX # choose a plain jane font fltFontScale = float(plateHeight) / 30.0 # base font scale on height of plate area intFontThickness = int(round(fltFontScale * 1.5)) # base font thickness on font scale textSize, baseline = cv2.getTextSize(licPlate.strChars, intFontFace, fltFontScale, intFontThickness) # call getTextSize # unpack roatated rect into center point, width and height, and angle ( (intPlateCenterX, intPlateCenterY), (intPlateWidth, intPlateHeight), fltCorrectionAngleInDeg ) = licPlate.rrLocationOfPlateInScene intPlateCenterX = int(intPlateCenterX) # make sure center is an integer intPlateCenterY = int(intPlateCenterY) ptCenterOfTextAreaX = int(intPlateCenterX) # the horizontal location of the text area is the same as the plate if intPlateCenterY < (sceneHeight * 0.75): # if the license plate is in the upper 3/4 of the image ptCenterOfTextAreaY = int(round(intPlateCenterY)) + int(round(plateHeight * 1.6)) # write the chars in below the plate else: # else if the license plate is in the lower 1/4 of the image ptCenterOfTextAreaY = int(round(intPlateCenterY)) - int(round(plateHeight * 1.6)) # write the chars in above the plate # end if textSizeWidth, textSizeHeight = textSize # unpack text size width and height ptLowerLeftTextOriginX = int(ptCenterOfTextAreaX - (textSizeWidth / 2)) # calculate the lower left origin of the text area ptLowerLeftTextOriginY = int(ptCenterOfTextAreaY + (textSizeHeight / 2)) # based on the text area center, width, and height # write the text on the image cv2.putText(imgOriginalScene, licPlate.strChars, (ptLowerLeftTextOriginX, ptLowerLeftTextOriginY), intFontFace, fltFontScale, SCALAR_YELLOW, intFontThickness) # end function ################################################################################################### if __name__ == "__main__": main()
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A system to automatically generate parking receipts by identifying the type of vehicle and storing the vehicle details using the registration number extracted out of the number place using computer vision.
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