def normalize_characters_character_height(license_plate,
image_original,
character_height,
m,
c,
recrop=True):
'''
Normalize height of characters.
'''
origin = Point(0, 0)
end = Point(license_plate.image.width - 1, license_plate.image.height - 1)
changed_image = False
for index in range(len(license_plate.subrects)):
new_y = int(license_plate.subrects[index].x * m + c)
if abs(new_y - license_plate.subrects[index].y) > 5:
license_plate.subrects[index].y = new_y
if license_plate.subrects[index].y < origin.y:
origin.y = license_plate.subrects[index].y
changed_image = True
license_plate.subrects[index].h = character_height
if license_plate.subrects[index].h + license_plate.subrects[
index].y - 1 > end.y:
end.y = license_plate.subrects[index].y + license_plate.subrects[
index].h - 1 + 50
changed_image = True
if changed_image and recrop:
# Recrop image and compute rectangles again.
license_plate = recrop_license_plate_image(license_plate, origin, end,
image_original)
character_validator = models.character_validator.CharacterValidator()
backup_image = Image(image=license_plate.image.data)
image = pre_process_license_plate_image(license_plate.image,
adaptative=False)
license_plate.subrects = image.compute_rectangles_for_characters()
character_validator.remove_wrong_characters(license_plate)
# If not enough characters detected, binarize image using adaptative method.
if len(license_plate.subrects) < 2:
image = pre_process_license_plate_image(backup_image, True)
license_plate.subrects = image.compute_rectangles_for_characters()
character_validator.remove_wrong_characters(license_plate)
validator = models.character_validator.CharacterValidator()
m, c = validator.get_least_squares(license_plate)
license_plate, m, c = normalize_characters_character_height(
license_plate, image_original, character_height, m, c, False)
return license_plate, m, c
def _recrop_image(self, license_plate, image_original, width, height, m, c,
x_interval):
'''
Recrop image if necessary.
'''
changed_image = False
origin = Point(0, 0)
end = Point(license_plate.image.width - 1,
license_plate.image.height - 1)
for character in license_plate.subrects:
if character.y < origin.y:
origin.y = character.y
changed_image = True
if character.x < origin.x:
origin.x = character.x
changed_image = True
if character.h + character.y - 1 > end.y:
end.y = character.y + character.h
changed_image = True
if character.w + character.x - 1 > end.x:
end.x = character.x + character.w
changed_image = True
if changed_image:
# Recrop image and compute rectangles again.
scale = license_plate.w * 1.0 / license_plate.image.width
license_plate = recrop_license_plate_image(license_plate, origin,
end, image_original)
old_image = Image(image=license_plate.image.data)
image_1 = pre_process_license_plate_image(license_plate.image,
True)
image_2 = pre_process_license_plate_image(old_image, False)
license_plate.image = image_1
color_mean_1 = self._calculate_mean_caracter_values(license_plate)
license_plate.image = image_2
color_mean_2 = self._calculate_mean_caracter_values(license_plate)
if color_mean_1 < 10 and color_mean_2 > 10:
color_mean_2 = 119
elif color_mean_1 > 10 and color_mean_2 < 10:
color_mean_1 = 119
if color_mean_1 < 255 and color_mean_2 > 255:
color_mean_1 = 119
elif color_mean_1 > 255 and color_mean_2 < 255:
color_mean_2 = 119
t1 = 70
t2 = 180
color_delta_1 = min(abs(color_mean_1 - t1), abs(color_mean_1 - t2))
color_delta_2 = min(abs(color_mean_2 - t1), abs(color_mean_2 - t2))
if color_delta_1 < color_delta_2:
license_plate.image = image_1
else:
license_plate.image = image_2
old_list = list(license_plate.subrects)
if len(old_list) > 0:
height = old_list[0].h
width = old_list[0].w
if len(old_list) > 2:
license_plate.subrects = license_plate.subrects[0:3]
m, c = self.get_least_squares(license_plate)
else:
m, c = self.get_least_squares(license_plate)
else:
height, width = self._get_h_w(license_plate)
m, c = self.get_least_squares(license_plate)
x_interval = int(x_interval * scale + 0.5)
license_plate.subrects = old_list
#license_plate.image.plot_rectangles(license_plate.subrects)
return license_plate, width, height, m, c, x_interval
def crop_image(image, quadrilateral, width_dest, height_dest):
'''
Crop image using parameters of quadrilateral.
'''
# Find crop parameters.
logger = Logger()
logger.log(Logger.INFO, "Finding crop parameters.")
origin = Point(image.width, image.height)
end = Point(0, 0)
for point in quadrilateral.points:
if point.x > end.x:
end.x = point.x
if point.y > end.y:
end.y = point.y
if point.x < origin.x:
origin.x = point.x
if point.y < origin.y:
origin.y = point.y
# Adjust dimensions to height be 20% of width.
scale = height_dest * 1.0 / width_dest
height = end.y - origin.y
width = end.x - origin.x
# Check if we will change height or width.
if width * scale < height:
# We need to increase width.
increment = height * 2.5 - width
end.x += increment / 2
if end.x >= image.width:
increment -= image.width - 1 - end.x
end.x = image.width - 1
else:
increment /= 2
origin.x -= increment
if origin.x < 0:
increment = -origin.x
origin.x = 0
end.x += increment
if end.x >= image.width:
end.x = image.width - 1
logger.log(Logger.INFO,
"Increasing width in " + str(end.x - origin.x - width))
else:
# We need to increase height.
increment = width * scale - height
end.y += increment / 2
if end.y >= image.height:
increment -= image.height - 1 - end.y
end.y = image.height - 1
else:
increment /= 2
origin.y -= increment
if origin.y < 0:
increment = -origin.y
origin.y = 0
end.y += increment
if end.y >= image.height:
end.y = image.height - 1
logger.log(Logger.INFO,
"Increasing height in " + str(end.y - origin.y - height))
# Crop image using points from configuration data.
cropped = image.crop(Point(origin.x, origin.y), Point(end.x, end.y))
# Resize image.
resized = cropped.resize(width_dest, height_dest)
return resized
