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
def extractPlate(img_original, list_of_matching_chars):
possible_plate = PossiblePlate.PossiblePlate() # this will be the return value
list_of_matching_chars.sort(key=lambda c: c.intCenterX)
# calculate the center point of the plate
fltPlateCenterX = (list_of_matching_chars[0].intCenterX + list_of_matching_chars[
len(list_of_matching_chars) - 1].intCenterX) / 2.0
fltPlateCenterY = (list_of_matching_chars[0].intCenterY + list_of_matching_chars[
len(list_of_matching_chars) - 1].intCenterY) / 2.0
ptPlateCenter = fltPlateCenterX, fltPlateCenterY
# calculate plate width and height
intPlateWidth = int((list_of_matching_chars[len(list_of_matching_chars) - 1].intBoundingRectX + list_of_matching_chars[
len(list_of_matching_chars) - 1].intBoundingRectWidth - list_of_matching_chars[
0].intBoundingRectX) * PLATE_WIDTH_PADDING_FACTOR)
intTotalOfCharHeights = 0
for matchingChar in list_of_matching_chars:
intTotalOfCharHeights = intTotalOfCharHeights + matchingChar.intBoundingRectHeight
# end for
fltAverageCharHeight = intTotalOfCharHeights / len(list_of_matching_chars)
intPlateHeight = int(fltAverageCharHeight * PLATE_HEIGHT_PADDING_FACTOR)
# calculate correction angle of plate region
fltOpposite = list_of_matching_chars[len(list_of_matching_chars) - 1].intCenterY - list_of_matching_chars[0].intCenterY
fltHypotenuse = DetectChars.distanceBetweenChars(list_of_matching_chars[0],
list_of_matching_chars[len(list_of_matching_chars) - 1])
fltCorrectionAngleInRad = math.asin(fltOpposite / fltHypotenuse)
fltCorrectionAngleInDeg = fltCorrectionAngleInRad * (180.0 / math.pi)
# pack plate region center point, width and height, and correction angle into rotated rect member variable of plate
possible_plate.rrLocationOfPlateInScene = (tuple(ptPlateCenter),
(intPlateWidth, intPlateHeight),
fltCorrectionAngleInDeg)
# final steps are to perform the actual rotation
# get the rotation matrix for our calculated correction angle
rotationMatrix = cv2.getRotationMatrix2D(tuple(ptPlateCenter), fltCorrectionAngleInDeg, 1.0)
height, width, numChannels = img_original.shape # unpack original image width and height
imgRotated = cv2.warpAffine(img_original, rotationMatrix, (width, height)) # rotate the entire image
imgCropped = cv2.getRectSubPix(imgRotated, (intPlateWidth, intPlateHeight), tuple(ptPlateCenter))
possible_plate.imgPlate = imgCropped
return possible_plate
def extractPlate(listOfMatchingChars):
possiblePlate = PossiblePlate.PossiblePlate(
) # this will be the return value
listOfMatchingChars.sort(
key=lambda matchingChar: matchingChar.intCenterX
) # sort chars from left to right based on x position
# calculate the center point of the plate
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
# calculate plate width and height
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
# end for
fltAverageCharHeight = intTotalOfCharHeights / len(listOfMatchingChars)
intPlateHeight = int(fltAverageCharHeight * PLATE_HEIGHT_PADDING_FACTOR)
# calculate correction angle of plate region
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)
# pack plate region center point, width and height, and correction angle into rotated rect member variable of plate
possiblePlate.rrLocationOfPlateInScene = (tuple(ptPlateCenter),
(intPlateWidth, intPlateHeight),
fltCorrectionAngleInDeg)
return possiblePlate
def extractPlate(input_image, listOfMatchingChars):
possiblePlate = PossiblePlate.PossiblePlate()
listOfMatchingChars.sort(
key=lambda matchingChar: matchingChar.intCenterX
) # sort chars from left to right based on x position
plate_center_X = (
listOfMatchingChars[0].intCenterX +
listOfMatchingChars[len(listOfMatchingChars) - 1].intCenterX) / 2.0
plate_center_Y = (
listOfMatchingChars[0].intCenterY +
listOfMatchingChars[len(listOfMatchingChars) - 1].intCenterY) / 2.0
plate_center = plate_center_X, plate_center_Y
plate_width = int(
(listOfMatchingChars[len(listOfMatchingChars) - 1].intBoundingRectX +
listOfMatchingChars[len(listOfMatchingChars) - 1].intBoundingRectWidth
- listOfMatchingChars[0].intBoundingRectX) * 1.3)
total_char_heights = 0
for matchingChar in listOfMatchingChars:
total_char_heights = total_char_heights + matchingChar.intBoundingRectHeight
average_char_height = total_char_heights / len(listOfMatchingChars)
plate_height = int(average_char_height * 1.5)
opposite = listOfMatchingChars[
len(listOfMatchingChars) -
1].intCenterY - listOfMatchingChars[0].intCenterY
hypotenuse = DetectChars.distanceBetweenChars(
listOfMatchingChars[0],
listOfMatchingChars[len(listOfMatchingChars) - 1])
correction_angle_radian = math.asin(opposite / hypotenuse)
correction_angle_degree = correction_angle_radian * (180.0 / math.pi)
possiblePlate.rrLocationOfPlateInScene = (tuple(plate_center),
(plate_width, plate_height),
correction_angle_degree)
rotationMatrix = cv2.getRotationMatrix2D(tuple(plate_center),
correction_angle_degree, 1.0)
height, width, Channels = input_image.shape
rotated_image = cv2.warpAffine(input_image, rotationMatrix,
(width, height))
cropped_image = cv2.getRectSubPix(rotated_image,
(plate_width, plate_height),
tuple(plate_center))
possiblePlate.imgPlate = cropped_image
return possiblePlate
def extractPlate(imgOriginal, listOfMatchingChars):
possiblePlate = PossiblePlate.PossiblePlate()
# sort chars from left to right based on x position
listOfMatchingChars.sort(key = lambda matchingChar: matchingChar.intCenterX)
# calculate the center point of the plate
fltPlateCenterX = (listOfMatchingChars[0].intCenterX + listOfMatchingChars[len(listOfMatchingChars) - 1].intCenterX) / 2.0
fltPlateCenterY = (listOfMatchingChars[0].intCenterY + listOfMatchingChars[len(listOfMatchingChars) - 1].intCenterY) / 2.0
# This is the probable central point of this plate.
ptPlateCenter = fltPlateCenterX, fltPlateCenterY
# calculate plate width and height
intPlateWidth = int((listOfMatchingChars[len(listOfMatchingChars) - 1].intBoundingRectX + listOfMatchingChars[len(listOfMatchingChars) - 1].intBoundingRectWidth - listOfMatchingChars[0].intBoundingRectX) * PLATE_WIDTH_PADDING_FACTOR)
# Here we calculate the probable width of this plate.
intTotalOfCharHeights = 0
for matchingChar in listOfMatchingChars:
intTotalOfCharHeights = intTotalOfCharHeights + matchingChar.intBoundingRectHeight
# Here we calculate the probale height of this particular plate.
fltAverageCharHeight = intTotalOfCharHeights / len(listOfMatchingChars)
# We include the padding factor.
intPlateHeight = int(fltAverageCharHeight * PLATE_HEIGHT_PADDING_FACTOR)
# calculate correction angle of plate region
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)
# pack plate region center point, width and height, and correction angle into rotated rect member variable of plate
possiblePlate.rrLocationOfPlateInScene = ( tuple(ptPlateCenter), (intPlateWidth, intPlateHeight), fltCorrectionAngleInDeg )
# final steps are to perform the actual rotation
# get the rotation matrix for our calculated correction angle
# The first point is the point of rotation or center,theta and scaling factor
rotationMatrix = cv2.getRotationMatrix2D(tuple(ptPlateCenter), fltCorrectionAngleInDeg, 1.0)
# unpack original image width and height
height, width, numChannels = imgOriginal.shape
# rotate the entire image
imgRotated = cv2.warpAffine(imgOriginal, rotationMatrix, (width, height))
# We extract the probable plate from the Original image
imgCropped = cv2.getRectSubPix(imgRotated, (intPlateWidth, intPlateHeight), tuple(ptPlateCenter))
# copy the cropped plate image into the applicable member variable of the possible plate
possiblePlate.imgPlate = imgCropped
return possiblePlate
def extractPlate(imgOriginal, listOfMatchingChars):
possiblePlate = PossiblePlate.PossiblePlate() # this will be the return value
listOfMatchingChars.sort(key = lambda matchingChar: matchingChar.intCenterX) # sort chars from left to right based on x position
# calculate the center point of the plate
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
# calculate plate width and height
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
# end for
fltAverageCharHeight = intTotalOfCharHeights / len(listOfMatchingChars)
intPlateHeight = int(fltAverageCharHeight * PLATE_HEIGHT_PADDING_FACTOR)
# calculate correction angle of plate region
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)
# pack plate region center point, width and height, and correction angle into rotated rect member variable of plate
possiblePlate.rrLocationOfPlateInScene = ( tuple(ptPlateCenter), (intPlateWidth, intPlateHeight), fltCorrectionAngleInDeg )
# final steps are to perform the actual rotation
# get the rotation matrix for our calculated correction angle
rotationMatrix = cv2.getRotationMatrix2D(tuple(ptPlateCenter), fltCorrectionAngleInDeg, 1.0)
height, width, numChannels = imgOriginal.shape # unpack original image width and height
imgRotated = cv2.warpAffine(imgOriginal, rotationMatrix, (width, height)) # rotate the entire image
imgCropped = cv2.getRectSubPix(imgRotated, (intPlateWidth, intPlateHeight), tuple(ptPlateCenter))
possiblePlate.imgPlate = imgCropped # copy the cropped plate image into the applicable member variable of the possible plate
return possiblePlate
def extractPlate(imgOriginal, listOfMatchingChars):
possiblePlate = PossiblePlate.PossiblePlate()
# sort chars from left to right based on x position
listOfMatchingChars.sort(key = lambda matchingChar: matchingChar.CenterX)
# calculate the center point of the plate
PlateCenterX = (listOfMatchingChars[0].CenterX + listOfMatchingChars[len(listOfMatchingChars) - 1].CenterX) / 2.0
PlateCenterY = (listOfMatchingChars[0].CenterY + listOfMatchingChars[len(listOfMatchingChars) - 1].CenterY) / 2.0
ptPlateCenter = PlateCenterX, PlateCenterY
# calculate plate width and height
PlateWidth = int((listOfMatchingChars[len(listOfMatchingChars) - 1].BoundingRectX + listOfMatchingChars[len(listOfMatchingChars) - 1].BoundingRectWidth - listOfMatchingChars[0].BoundingRectX) * PLATE_WIDTH_PADDING_FACTOR)
TotalOfCharHeights = 0
for matchingChar in listOfMatchingChars:
TotalOfCharHeights = TotalOfCharHeights + matchingChar.BoundingRectHeight
# end for
AverageCharHeight = TotalOfCharHeights / len(listOfMatchingChars)
PlateHeight = int(AverageCharHeight * PLATE_HEIGHT_PADDING_FACTOR)
# calculate correction angle of plate region
Opposite = listOfMatchingChars[len(listOfMatchingChars) - 1].CenterY - listOfMatchingChars[0].CenterY
Hypotenuse = DetectChars.distanceBetweenChars(listOfMatchingChars[0], listOfMatchingChars[len(listOfMatchingChars) - 1])
CorrectionAngleInRad = math.asin(Opposite / Hypotenuse)
CorrectionAngleInDeg = CorrectionAngleInRad * (180.0 / math.pi)
# pack plate region center point, width and height, and correction angle into rotated rect member variable of plate
possiblePlate.rrLocationOfPlateInScene = ( tuple(ptPlateCenter), (PlateWidth, PlateHeight), CorrectionAngleInDeg )
# final steps are to perform the actual rotation
# get the rotation matrix for our calculated correction angle
rotationMatrix = cv2.getRotationMatrix2D(tuple(ptPlateCenter), CorrectionAngleInDeg, 1.0)
height, width, numChannels = imgOriginal.shape
imgRotated = cv2.warpAffine(imgOriginal, rotationMatrix, (width, height))
imgCropped = cv2.getRectSubPix(imgRotated, (PlateWidth, PlateHeight), tuple(ptPlateCenter))
possiblePlate.imgPlate = imgCropped
return possiblePlate
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
def extractPlate(imgOriginal, listOfMatchingChars):
possiblePlate = PossiblePlate.PossiblePlate() # Dönüş değeri olacak
listOfMatchingChars.sort(key = lambda matchingChar: matchingChar.intCenterX) # Karakterleri x konumuna göre sola veya sağa sıralayın
# Plakanın merkez noktasını hesaplar
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
# Plaka genişliği ve yüksekliğini hesaplar
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)
# Plaka bölgesinin düzeltme açısını hesaplar
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)
# Paket bölgesinin merkez noktası, genişliği, yüksekliği ve plakanın döndürülmüş dikme elemanı değişkenine düzeltme açısı
possiblePlate.rrLocationOfPlateInScene = ( tuple(ptPlateCenter), (intPlateWidth, intPlateHeight), fltCorrectionAngleInDeg )
# Son adımlar asıl dönüşü gerçekleştirmektir
# Hesaplanan düzeltme açımız için rotasyon matrisini alın
rotationMatrix = cv2.getRotationMatrix2D(tuple(ptPlateCenter), fltCorrectionAngleInDeg, 1.0)
height, width, numChannels = imgOriginal.shape # Orjinal görüntü genişliğini ve yüksekliğini açma
imgRotated = cv2.warpAffine(imgOriginal, rotationMatrix, (width, height)) # Tüm resmi döndür
imgCropped = cv2.getRectSubPix(imgRotated, (intPlateWidth, intPlateHeight), tuple(ptPlateCenter))
possiblePlate.imgPlate = imgCropped # Kırpılmış plaka görüntüsünü olası plakanın uygulanabilir üye değişkenine kopyala
return possiblePlate
def extractPlate(imgOriginal, listOfMatchingChars):
possiblePlate = PossiblePlate.PossiblePlate(
) # this will be the return value
listOfMatchingChars.sort(
key=lambda matchingChar: matchingChar.intCenterX
) # 람다는 한줄로 정의하는 함수다. sort chars from left to right based on x position
##### [plate 중심좌표계산] calculate the center point of the plate
fltPlateCenterX = (listOfMatchingChars[0].intCenterX + listOfMatchingChars[
len(listOfMatchingChars) - 1].intCenterX) / 2.0 #처음거랑 마지막거 센터평균
fltPlateCenterY = (
listOfMatchingChars[0].intCenterY +
listOfMatchingChars[len(listOfMatchingChars) - 1].intCenterY) / 2.0
ptPlateCenter = fltPlateCenterX, fltPlateCenterY
###### [plate높이와 폭계산] calculate plate width and height
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
# end for
fltAverageCharHeight = intTotalOfCharHeights / len(listOfMatchingChars)
intPlateHeight = int(fltAverageCharHeight * PLATE_HEIGHT_PADDING_FACTOR)
##### end [plate높이와 폭계산]
######[각도 계산. y차와 거리 이용] calculate correction angle of plate region
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)
#####[위치기록.Box2D형식인듯] pack plate region center point, width and height, and correction angle into rotated rect member variable of plate
possiblePlate.rrLocationOfPlateInScene = (tuple(ptPlateCenter),
(intPlateWidth, intPlateHeight),
fltCorrectionAngleInDeg)
# final steps are to perform the actual rotation
#####[회전 및 crop] # get the rotation matrix for our calculated correction angle
rotationMatrix = cv2.getRotationMatrix2D(tuple(ptPlateCenter),
fltCorrectionAngleInDeg, 1.0)
height, width, numChannels = imgOriginal.shape # unpack original image width and height
imgRotated = cv2.warpAffine(imgOriginal, rotationMatrix,
(width, height)) # rotate the entire image
imgCropped = cv2.getRectSubPix(imgRotated, (intPlateWidth, intPlateHeight),
tuple(ptPlateCenter))
possiblePlate.imgPlate = imgCropped # copy the cropped plate image into the applicable member variable of the possible plate
return possiblePlate
def extractPlate(imgOriginal, listOfMatchingChars):
possiblePlate = PossiblePlate.PossiblePlate(
) # this will be the return value ##回傳PossiblePlate.py内的物件PossiblePlate()
listOfMatchingChars.sort(
key=lambda matchingChar: matchingChar.intCenterX
) # sort chars from left to right based on x position #以listOfMatchingChars（裏面的物件）的屬性intCenterX去做sort
# calculate the center point of the plate
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 #
# calculate plate width and height #最後一個點-第一個點=等於寬度*1.3
intPlateWidth = int(
(listOfMatchingChars[len(listOfMatchingChars) - 1].intBoundingRectX +
listOfMatchingChars[len(listOfMatchingChars) - 1].intBoundingRectWidth
- listOfMatchingChars[0].intBoundingRectX) *
PLATE_WIDTH_PADDING_FACTOR)
intTotalOfCharHeights = 0
#listOfMatchingChar裏面的height 全部相加
for matchingChar in listOfMatchingChars:
intTotalOfCharHeights = intTotalOfCharHeights + matchingChar.intBoundingRectHeight
# end for
fltAverageCharHeight = intTotalOfCharHeights / len(
listOfMatchingChars) #平均height
intPlateHeight = int(fltAverageCharHeight *
PLATE_HEIGHT_PADDING_FACTOR) #平均height*1.5
# calculate correction angle of plate region
fltOpposite = listOfMatchingChars[len(
listOfMatchingChars
) - 1].intCenterY - listOfMatchingChars[
0].intCenterY #listOfMatchingChars的CenterY最後一個-listOfMatchingChars的CenterY第一個 ##找到寬度==高度
fltHypotenuse = DetectChars.distanceBetweenChars(
listOfMatchingChars[0],
listOfMatchingChars[len(listOfMatchingChars) -
1]) #第一個值和最後一個去做彼氏定理 找到char之間的距離
fltCorrectionAngleInRad = math.asin(
fltOpposite / fltHypotenuse) #math.asin=只接受-1到1之間的數字 超出範圍就會回傳NAN##
fltCorrectionAngleInDeg = fltCorrectionAngleInRad * (180.0 / math.pi
) ##找角度
# pack plate region center point, width and height, and correction angle into rotated rect member variable of plate
possiblePlate.rrLocationOfPlateInScene = (tuple(ptPlateCenter),
(intPlateWidth, intPlateHeight),
fltCorrectionAngleInDeg)
# final steps are to perform the actual rotation
# get the rotation matrix for our calculated correction angle
rotationMatrix = cv2.getRotationMatrix2D(
tuple(ptPlateCenter), fltCorrectionAngleInDeg,
1.0) ##(旋轉中心,旋轉角度，縮放比例 ) ##更正字體的角度
height, width, numChannels = imgOriginal.shape # unpack original image width and height
imgRotated = cv2.warpAffine(
imgOriginal, rotationMatrix,
(width, height)) # rotate the entire image ##圖像平移（圖像，變換矩陣，變換后的大小）
imgCropped = cv2.getRectSubPix(
imgRotated, (intPlateWidth, intPlateHeight),
tuple(ptPlateCenter)) ##（imgRotated圖像，（截取圖像高和寬），中心）###回傳圖片
possiblePlate.imgPlate = imgCropped # copy the cropped plate image into the applicable member variable of the possible plate ###給值
return possiblePlate
def extractPlate(imgOriginal, listOfMatchingChars):
possiblePlate = PossiblePlate.PossiblePlate()
listOfMatchingChars.sort(key=lambda matchingChar: matchingChar.intCenterX
) # sắp xếp kí tự từ trái sang phải từ X
# Tính điểm trung tâm của tấm
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
# tính chiều rộng cua tấm
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
# end for
fltAverageCharHeight = intTotalOfCharHeights / len(listOfMatchingChars)
intPlateHeight = int(fltAverageCharHeight * PLATE_HEIGHT_PADDING_FACTOR)
# tính góc của tấm
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)
# pack plate region center point, width and height, and correction angle into rotated rect member variable of plate
possiblePlate.rrLocationOfPlateInScene = (tuple(ptPlateCenter),
(intPlateWidth, intPlateHeight),
fltCorrectionAngleInDeg)
# get the rotation matrix for our calculated correction angle
rotationMatrix = cv2.getRotationMatrix2D(tuple(ptPlateCenter),
fltCorrectionAngleInDeg, 1.0)
height, width, numChannels = imgOriginal.shape # giải nén chiều rộng và chiều cao ảnh gốc
imgRotated = cv2.warpAffine(imgOriginal, rotationMatrix,
(width, height)) # xoay hình ảnh
imgCropped = cv2.getRectSubPix(imgRotated, (intPlateWidth, intPlateHeight),
tuple(ptPlateCenter))
possiblePlate.imgPlate = imgCropped
return possiblePlate
def extractPlate(imgOriginal, listOfMatchingChars):
possiblePlate = PossiblePlate.PossiblePlate(
) #possiblePlate is object of class PossiblePlate
""" object provides us huge flexibility like we can use multile attributes by just one object"""
# this will be the return value
""" NOTE->matchingChar.intCenterX """
listOfMatchingChars.sort(
key=lambda matchingChar: matchingChar.intCenterX
) # sort chars from left to right based on x position
# calculate the center point of the plate
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
# calculate plate width and height
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
# end for
fltAverageCharHeight = intTotalOfCharHeights / len(listOfMatchingChars)
intPlateHeight = int(fltAverageCharHeight * PLATE_HEIGHT_PADDING_FACTOR)
# calculate correction angle of plate region
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)
# pack plate region center point, width and height, and correction angle into rotated rect member variable of plate
possiblePlate.rrLocationOfPlateInScene = (tuple(ptPlateCenter),
(intPlateWidth, intPlateHeight),
fltCorrectionAngleInDeg)
# final steps are to perform the actual rotation
# get the rotation matrix for our calculated correction angle
rotationMatrix = cv2.getRotationMatrix2D(tuple(ptPlateCenter),
fltCorrectionAngleInDeg, 1.0)
height, width, numChannels = imgOriginal.shape # unpack original image width and height
imgRotated = cv2.warpAffine(imgOriginal, rotationMatrix,
(width, height)) # rotate the entire image
imgCropped = cv2.getRectSubPix(imgRotated, (intPlateWidth, intPlateHeight),
tuple(ptPlateCenter)) #cropping
#possiblePlate is object
possiblePlate.imgPlate = imgCropped # copy the cropped plate image into the applicable member variable of the possible plate
return possiblePlate
def extractPlate(imgOriginal, listOfMatchingChars):
# Valor retornado
possiblePlate = PossiblePlate.PossiblePlate()
# Ordena os caracteres da esquerda pra direita baseado na posição X
listOfMatchingChars.sort(key=lambda matchingChar: matchingChar.intCenterX)
# Calcula o centro da placa
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
# Calcula a altura e largura da placa
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
# end for
fltAverageCharHeight = intTotalOfCharHeights / len(listOfMatchingChars)
intPlateHeight = int(fltAverageCharHeight * PLATE_HEIGHT_PADDING_FACTOR)
# Calcula o angulo correto da reguao da placa
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)
# Reune o ponto central da regiao da placa, largura, altura e o angulo de rotacao em um retangulo rotacionado membro da variavel da placa
possiblePlate.rrLocationOfPlateInScene = (tuple(ptPlateCenter),
(intPlateWidth, intPlateHeight),
fltCorrectionAngleInDeg)
# Executa a rotacao atual
# Recupera a matriz de rotacao para o angulo encontrado
rotationMatrix = cv2.getRotationMatrix2D(tuple(ptPlateCenter),
fltCorrectionAngleInDeg, 1.0)
# Recupera os valores originais da imagem
height, width, numChannels = imgOriginal.shape
# Rotaciona a imagem inteira
imgRotated = cv2.warpAffine(imgOriginal, rotationMatrix, (width, height))
imgCropped = cv2.getRectSubPix(imgRotated, (intPlateWidth, intPlateHeight),
tuple(ptPlateCenter))
# Guarda a imagem cortada da placa
possiblePlate.imgPlate = imgCropped
return possiblePlate
# end function
def extractPlate(imgOriginal, listOfMatchingChars):
possiblePlate = PossiblePlate.PossiblePlate(
) # este será el valor de retorno
listOfMatchingChars.sort(
key=lambda matchingChar: matchingChar.intCenterX
) # ordenar caracteres de izquierda a derecha según la posición x
# calcular el punto central de la placa
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
#calcular el ancho y la altura de la placa
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
# end for
fltAverageCharHeight = intTotalOfCharHeights / len(listOfMatchingChars)
intPlateHeight = int(fltAverageCharHeight * PLATE_HEIGHT_PADDING_FACTOR)
# calcular el ángulo de corrección de la región de la placa
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)
# empaquete el punto central, el ancho y la altura de la región de la placa, y el ángulo de corrección en la variable del miembro correcto rotado de la placa
possiblePlate.rrLocationOfPlateInScene = (tuple(ptPlateCenter),
(intPlateWidth, intPlateHeight),
fltCorrectionAngleInDeg)
# los pasos finales son realizar la rotación real
# obtener la matriz de rotación para nuestro ángulo de corrección calculado
rotationMatrix = cv2.getRotationMatrix2D(tuple(ptPlateCenter),
fltCorrectionAngleInDeg, 1.0)
height, width, numChannels = imgOriginal.shape # descomprimir ancho y alto de la imagen original
imgRotated = cv2.warpAffine(imgOriginal, rotationMatrix,
(width, height)) # rotar toda la imagen
imgCropped = cv2.getRectSubPix(imgRotated, (intPlateWidth, intPlateHeight),
tuple(ptPlateCenter))
possiblePlate.imgPlate = imgCropped # copie la imagen de la placa recortada en la variable miembro aplicable de la placa posible
return possiblePlate
