def eliminateSize(characters, display=None):
indexRemove = set([])
currentCount = 0
for cnt in characters:
count = 0
while count < len(characters):
if count == currentCount:
count += 1
continue
compareCnt = characters[count]
w1, h1 = cnt.w, cnt.h
w2, h2 = compareCnt.w, compareCnt.h
changeInWidth = abs(w2-w1)/float(w2)
changeInHeight = abs(h2-h1)/float(h2)
if changeInWidth > cu.MAX_CHANGE_IN_WIDTH:
if changeInHeight > cu.MAX_CHANGE_IN_HEIGHT:
if h1 > h2:
indexRemove.add(currentCount)
else:
indexRemove.add(count)
count += 1
currentCount += 1
indexRemove = sorted(indexRemove, reverse=True, key=int)
for i in indexRemove:
if display is not None:
ip2.drawRect(display, characters[i].boundingRect, RED)
del characters[i]
cv2.imshow('after_delete_size_red', display)
def detectCharacter(file):
img = cv2.imread(file)
if img is not None:
showimg = img.copy()
result_characters = main.findContours(img, main.OTSU)
for character in result_characters:
x, y, w, h = character.boundingRect
ip2.drawRect(showimg, character.boundingRect, (255, 0, 255), 10)
blurredImage = ip2.gaussianBlur(
ip2.resizeWithSize(
ip2.addBorder(ip2.addPadding(img[y:y + h, x:x + w]), 8),
(32, 32)), 3)
caffe_image = singleimage.cv2caffe(blurredImage)
character.index, character.score = singleimage.getProb(
main.net, caffe_image)
character.score = character.score[0][character.index]
sortresult.sortCarplateResult(result_characters)
result = ''
for character in result_characters:
char = singleimage.convertIndex(character.index)
result += char
ip2.addText(showimg, char, (character.x - 30, character.y - 30),
20)
if character.isLastChar:
result += '\n'
return result, showimg
def eliminateNonMaybe(ori_img, maybeCharacter, total, min_thresh, number, display=None): if number is 1: thresh_img = ip2.preprocessOtsuThreshold(ori_img) elif number is 2: thresh_img = ip2.preprocessWithThreshold(ori_img, min_thresh) else: thresh_img = ip2.preprocessOtsuThreshold(ip2.preprocessWithThreshold(ori_img)) cu.normalChecking(thresh_img, ori_img, total, 150, display) for t in total.getArray(): if display is not None: ip2.drawRect(display, t.boundingRect, MAGENTA) maybeCharacter.append(t)
def eliminateArea(characters, display=None):
indexRemove = set([])
avgArea = cu.findAvgArea(characters)
threshArea = avgArea/cu.THRESH_AREA_DENOMINATOR
count = 0
for cnt in characters:
if cnt.area < threshArea:
indexRemove.add(count)
count += 1
indexRemove = sorted(indexRemove, reverse=True, key=int)
for i in indexRemove:
if display is not None:
ip2.drawRect(display, characters[i].boundingRect, PURPLE)
del characters[i]
cv2.imshow('after_delete_area_purple', display)
def eliminateDiagonal(characters, display=None):
indexRemove = set([])
avgDiagonal = cu.findAvgDiagonal(characters)
threshDiagonal = avgDiagonal/cu.THRESH_DIAGONAL_DENOMINATOR
count = 0
for cnt in characters:
if cnt.diagonalSize < threshDiagonal:
indexRemove.add(count)
count += 1
indexRemove = sorted(indexRemove, reverse=True, key=int)
for i in indexRemove:
if display is not None:
ip2.drawRect(display, characters[i].boundingRect, YELLOW)
del characters[i]
cv2.imshow('after_delete_diagonal_yellow', display)
def eliminateNewArea(characters, display=None):
indexRemove = set([])
count = 0
median_area = cu.findMedianArea(characters)
for cnt in characters:
area = cnt.area
changeInArea = abs(median_area-area)/median_area
if changeInArea > cu.MAX_CHANGE_IN_NEW_AREA:
indexRemove.add(count)
count += 1
indexRemove = sorted(indexRemove, reverse=True, key=int)
for i in indexRemove:
if display is not None:
ip2.drawRect(display, characters[i].boundingRect, MAROON)
del characters[i]
if display is not None:
cv2.imshow('new_area_maroon', display)
def normalChecking(thresh_img, ori_img, total, min_thresh, display=None): ''' 1. find contours and create cu.Character array 2. eliminate impossible size character :param thresh_img: :param ori_img: :param total: :param min_thresh: :param display: :return: ''' contours, hierarchy = ip2.findContours(thresh_img) for cnt in contours: char = Character(cnt) if display is not None: ip2.drawRect(display, char.boundingRect, ip2.WHITE) if char.isMaybeSize(): if char.aspectRatio <= MAX_ASPECTRATIO: # char.increaseSize() total.__add__(char)
def eliminateDistance(characters, display=None):
indexRemove = set([])
count = 0
median_distance = cu.findMedianDistance(characters) # sort by x already
for i in xrange(len(characters)-1):
cnt1 = characters[i]
cnt2 = characters[i+1]
distance = cnt1.distanceFromCenter(cnt2)
changeInDistance = abs(distance-median_distance)/median_distance
if changeInDistance > cu.MAX_CHANGE_IN_DISTANCE:
indexRemove.add(count)
count += 1
indexRemove = sorted(indexRemove, reverse=True, key=int)
for i in indexRemove:
if display is not None:
ip2.drawRect(display, characters[i].boundingRect, INDIGO)
del characters[i]
if display is not None:
cv2.imshow('distance_indigo', display)
def eliminateNewSize(characters, display=None):
'''
eliminate size which small than max change height
:param characters:
:param display:
:return:
'''
indexRemove = set([])
count = 0
median_h = cu.findMedianHeight(characters)
for cnt in characters:
h = cnt.h
changeInHeight = float(abs(median_h-h))/median_h
if changeInHeight > cu.MAX_CHANGE_IN_NEW_HEIGHT:
indexRemove.add(count)
count += 1
indexRemove = sorted(indexRemove, reverse=True, key=int)
for i in indexRemove:
if display is not None:
ip2.drawRect(display, characters[i].boundingRect, GREEN)
del characters[i]
if display is not None:
cv2.imshow('new_size_green', display)
def drawAllChar(self, display, color=ip2.GREEN): for char in self.charArray: ip2.drawRect(display, char.boundingRect, color)
def guiRun(file, number):
'''
used by gui
:param file: image path
:param number: threshold method, 1-'otsu' 2-'threshold' 3-'normal-otsu'
:return:
'''
img = cv2.imread(file)
if img is not None:
img = resize(img, 320)
cv2.imwrite('gui/resize.png', img)
# display = img.copy()
characters = findContours(img, number)
greyscale = ip2.greyscale(img)
white = cc.newInRangeOfWhite(img)
threshold = ip2.preprocessWithThreshold(img)
threshold_otsu = ip2.preprocessOtsuThreshold(img)
otsu_normal = ip2.preprocessOtsuThreshold(threshold)
if number == 1:
contoursImage = threshold_otsu.copy()
currentImage = threshold_otsu.copy()
elif number == 2:
contoursImage = threshold.copy()
currentImage = threshold.copy()
else:
contoursImage = otsu_normal.copy()
currentImage = otsu_normal.copy()
contoursImage = ip2.colour(contoursImage)
indices = []
scores = []
for cnt in characters: #type: cu.Character
x, y, w, h = cnt.boundingRect
ip2.drawRect(contoursImage, (x, y, w, h), ip2.RED)
cv_image = ip2.resizeWithSize(ip2.addBorder(ip2.addPadding(currentImage[y:y+h, x:x+w]), 8), (32, 32))
caffe_image = singleimage.cv2caffe(cv_image)
prob, score = singleimage.getProb(net, caffe_image)
cnt.index = int(prob)
cnt.score = score[0][prob]
indices.append(int(prob))
scores.append(score[0][prob])
# indices, scores = sortResultv2(characters, indices, scores)
characters = sortresult.sortCarplateResult(characters)
carplate_str = ''
for cnt in characters:
carplate_str += singleimage.convertIndex(cnt.index)
if len(carplate_str) <= 4 and number == 1:
return guiRun(file, 3)
elif len(carplate_str) <= 4 and number == 3:
return guiRun(file, 2)
cv2.imwrite('gui/greyscale.png', greyscale)
cv2.imwrite('gui/white.png', white)
cv2.imwrite('gui/threshold.png', threshold)
cv2.imwrite('gui/threshold_otsu.png', threshold_otsu)
cv2.imwrite('gui/otsu_normal.png', otsu_normal)
cv2.imwrite('gui/contours.png', contoursImage)
cv2.imwrite('gui/current.png', currentImage)
return carplate_str, characters, scores
else:
return '', None
