def detectCharsInPlates(listOfPossiblePlates):
intPlateCounter = 0
imgContours = None
contours = []
if len(listOfPossiblePlates) == 0:
return listOfPossiblePlates
for possiblePlate in listOfPossiblePlates:
possiblePlate.imgGrayscale, possiblePlate.imgThresh = refining.preprocess(
possiblePlate.imgPlate)
if product.showSteps == True:
cv2.imshow("5a", possiblePlate.imgPlate)
cv2.imshow("5b", possiblePlate.imgGrayscale)
cv2.imshow("5c", possiblePlate.imgThresh)
possiblePlate.imgThresh = cv2.resize(possiblePlate.imgThresh, (0, 0),
fx=1.6,
fy=1.6)
thresholdValue, possiblePlate.imgThresh = cv2.threshold(
possiblePlate.imgThresh, 0.0, 255.0,
cv2.THRESH_BINARY | cv2.THRESH_OTSU)
if product.showSteps == True:
cv2.imshow("5d", possiblePlate.imgThresh)
listOfPossibleCharsInPlate = findPossibleCharsInPlate(
possiblePlate.imgGrayscale, possiblePlate.imgThresh)
if product.showSteps == True:
height, width, numChannels = possiblePlate.imgPlate.shape
imgContours = np.zeros((height, width, 3), np.uint8)
del contours[:]
for possibleChar in listOfPossibleCharsInPlate:
contours.append(possibleChar.contour)
cv2.drawContours(imgContours, contours, -1, product.SCALAR_WHITE)
cv2.imshow("6", imgContours)
listOfListsOfMatchingCharsInPlate = findListOfListsOfMatchingChars(
listOfPossibleCharsInPlate)
if product.showSteps == True:
imgContours = np.zeros((height, width, 3), np.uint8)
del contours[:]
for listOfMatchingChars in listOfListsOfMatchingCharsInPlate:
intRandomBlue = random.randint(0, 255)
intRandomGreen = random.randint(0, 255)
intRandomRed = random.randint(0, 255)
for matchingChar in listOfMatchingChars:
contours.append(matchingChar.contour)
cv2.drawContours(imgContours, contours, -1,
(intRandomBlue, intRandomGreen, intRandomRed))
cv2.imshow("7", imgContours)
if (len(listOfListsOfMatchingCharsInPlate) == 0):
if product.showSteps == True:
print(
"chars found in plate number " + str(intPlateCounter) +
" = (none), click on any image and press a key to continue . . ."
)
intPlateCounter = intPlateCounter + 1
cv2.destroyWindow("8")
cv2.destroyWindow("9")
cv2.destroyWindow("10")
cv2.waitKey(0)
possiblePlate.strChars = ""
continue
for i in range(0, len(listOfListsOfMatchingCharsInPlate)):
listOfListsOfMatchingCharsInPlate[i].sort(
key=lambda matchingChar: matchingChar.intCenterX)
listOfListsOfMatchingCharsInPlate[i] = removeInnerOverlappingChars(
listOfListsOfMatchingCharsInPlate[i])
if product.showSteps == True:
imgContours = np.zeros((height, width, 3), np.uint8)
for listOfMatchingChars in listOfListsOfMatchingCharsInPlate:
intRandomBlue = random.randint(0, 255)
intRandomGreen = random.randint(0, 255)
intRandomRed = random.randint(0, 255)
del contours[:]
for matchingChar in listOfMatchingChars:
contours.append(matchingChar.contour)
cv2.drawContours(imgContours, contours, -1,
(intRandomBlue, intRandomGreen, intRandomRed))
cv2.imshow("8", imgContours)
intLenOfLongestListOfChars = 0
intIndexOfLongestListOfChars = 0
for i in range(0, len(listOfListsOfMatchingCharsInPlate)):
if len(listOfListsOfMatchingCharsInPlate[i]
) > intLenOfLongestListOfChars:
intLenOfLongestListOfChars = len(
listOfListsOfMatchingCharsInPlate[i])
intIndexOfLongestListOfChars = i
longestListOfMatchingCharsInPlate = listOfListsOfMatchingCharsInPlate[
intIndexOfLongestListOfChars]
if product.showSteps == True:
imgContours = np.zeros((height, width, 3), np.uint8)
del contours[:]
for matchingChar in longestListOfMatchingCharsInPlate:
contours.append(matchingChar.contour)
cv2.drawContours(imgContours, contours, -1, product.SCALAR_WHITE)
cv2.imshow("9", imgContours)
possiblePlate.strChars = recognizeCharsInPlate(
possiblePlate.imgThresh, longestListOfMatchingCharsInPlate)
if product.showSteps == True:
print("chars found in plate number " + str(intPlateCounter) +
" = " + possiblePlate.strChars +
", click on any image and press a key to continue . . .")
intPlateCounter = intPlateCounter + 1
cv2.waitKey(0)
if product.showSteps == True:
print(
"\nchar detection complete, click on any image and press a key to continue . . .\n"
)
cv2.waitKey(0)
return listOfPossiblePlates
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 product.showSteps == True:
cv2.imshow("0", imgOriginalScene)
imgGrayscaleScene, imgThreshScene = refining.preprocess(imgOriginalScene)
if product.showSteps == True:
cv2.imshow("1a", imgGrayscaleScene)
cv2.imshow("1b", imgThreshScene)
listOfPossibleCharsInScene = findPossibleCharsInScene(imgThreshScene)
if product.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, product.SCALAR_WHITE)
cv2.imshow("2b", imgContours)
listOfListsOfMatchingCharsInScene = char_detection.findListOfListsOfMatchingChars(
listOfPossibleCharsInScene)
if product.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") # 13 with MCLRNF1 image
if product.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]), product.SCALAR_RED, 2)
cv2.line(imgContours, tuple(p2fRectPoints[1]),
tuple(p2fRectPoints[2]), product.SCALAR_RED, 2)
cv2.line(imgContours, tuple(p2fRectPoints[2]),
tuple(p2fRectPoints[3]), product.SCALAR_RED, 2)
cv2.line(imgContours, tuple(p2fRectPoints[3]),
tuple(p2fRectPoints[0]), product.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