Recognize text from number plate

[Sheheryar]

Hello, I am beginner in python development and data sciences and i am doing project of recognize number plate i have been trained own tensorflow model with own datasets and successfully detect but how i get text OCR not recognize number plate text please help me.

[Larz60+]

code please

[Sheheryar]

code please

I am using OCR simply and that was read text but this code i took from github and change one or two line of code and then try and accuracy was not good read some character wrong.

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 main():

    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("p.jpg")               # open image
    # exit()

    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
    # exit()
    # end if

    listOfPossiblePlates = DetectPlates.detectPlatesInScene(imgOriginalScene) # detect plates
    # exit()

    listOfPossiblePlates = DetectChars.detectCharsInPlates(listOfPossiblePlates)        # detect chars in plates
    # print(listOfPossiblePlates)
    # exit()

    cv2.imshow("imgOriginalScene", imgOriginalScene)            # show scene image

    if len(listOfPossiblePlates) == 0:                          # if no plates were found
        print("\nno 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]
        # print(licPlate)
        # exit()

        # 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
        print(imgOriginalScene)

        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
# 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()

[Larz60+]

I'm not vouching for this package (I have not used it), but it looks like it's professionally done, and well documented and updated last on July 2nd. Worth trying out.

https://github.com/Calamari-OCR/calamari

There are others that you can investigate here: https://pypi.org/search/?q=ocr

[Sheheryar]

I'm not vouching for this package (I have not used it), but it looks like it's professionally done, and well documented and updated last on July 2nd. Worth trying out.

https://github.com/Calamari-OCR/calamari

There are others that you can investigate here: https://pypi.org/search/?q=ocr

---

Thanks, I will use it and then feedback about that links.