def detect_vertical_lines(self, Mat_Binary):
''' Detect vertical lines present in the binary image '''
kernel_length = Mat_Binary.shape[1]//80
vertical_kernel = cv2.getStructuringElement(
cv2.MORPH_RECT, (1, kernel_length))
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
Mat_Vertical = cv2.erode(
Mat_Binary, vertical_kernel, iterations=3)
KLogger.set_log('LINE_VERTICAL200', 'Detecting Vertical Lines')
return Mat_Vertical
def detect_horizontal_lines(self, Mat_Binary):
'''
Detect Horizontal lines present in the binary image
'''
kernel_length = Mat_Binary.shape[1]//80
horizontal_kernel = cv2.getStructuringElement(
cv2.MORPH_RECT, (kernel_length, 1))
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
Mat_Horizontal = cv2.erode(
Mat_Binary, horizontal_kernel, iterations=3)
KLogger.set_log('LINE_HORIZONTAL200', 'Detecting Horizontal Lines')
return Mat_Horizontal
def detect_line_separation(self, Mat_Binary):
'''
detect line separation by space
'''
KLogger.set_log('DETECT_LINES200', 'Detecting Lines By Text Spacing')
pts = cv2.findNonZero(Mat_Binary)
rect = cv2.minAreaRect(pts)
(cx, cy), (w, h), angle = rect
# if w > h:
# w, h = h, w
# angle += 90
# M = cv2.getRotationMatrix2D((cx, cy), angle, 1.0)
# rotated = cv2.warpAffine(
# Mat_Binary, M, (Mat_Binary.shape[1], Mat_Binary.shape[0]))
hist = cv2.reduce(Mat_Binary, 1, cv2.REDUCE_AVG).reshape(-1)
th = 0
H, W = Mat_Binary.shape[:2]
uppers = [y for y in range(H-1) if hist[y] <= th and hist[y+1] > th]
lowers = [y for y in range(H-1) if hist[y] > th and hist[y+1] <= th]
# result = cv2.cvtColor(Mat_Binary, cv2.COLOR_GRAY2BGR)
result = np.zeros((H, W), dtype=np.uint8)
# for y in uppers:
# cv2.line(result, (0, y), (W, y), (0, 255, 0), 1)
for y in lowers:
cv2.line(result, (0, y), (W, y), (255, 0, 0), 1)
# result = cv2.pyrUp(result)
KLogger.set_log('RETURN_LINES200', 'Return Lines By Text Spacing')
return result
def count_lines(self, Mat, vertical=True):
''' Return total number of lines '''
if vertical:
KLogger.set_log('COUNT_VERTICAL_LINES200',
'Counting vertical lines')
else:
KLogger.set_log('COUNT_HORIZONTAL_LINES200',
'Counting horizontal lines')
lines = cv2.HoughLines(Mat, 1, np.pi/180, 0)
# vertical_lines, horizontal_lines = [], []
lines_counted = []
for line in lines:
for rho, theta in line:
a = np.cos(theta)
# Stores the value of sin(theta) in b
b = np.sin(theta)
x0 = a*rho
y0 = b*rho
# x1 stores the rounded off value of (rcos(theta)-1000sin(theta))
x1 = int(x0 + 1000*(-b))
# y1 stores the rounded off value of (rsin(theta)+1000cos(theta))
y1 = int(y0 + 1000*(a))
# x2 stores the rounded off value of (rcos(theta)+1000sin(theta))
x2 = int(x0 - 1000*(-b))
# y2 stores the rounded off value of (rsin(theta)-1000cos(theta))
y2 = int(y0 - 1000*(a))
if not vertical and b == 1: # calculate the horizontal lines
# cv2.line(Mat, (x1, y1), (x2, y2),(255, 255, 255), 1, cv2.CV_AA)
lines_counted.append([x1, y1, x2, y2])
if vertical and theta == 0: # calculate the vertical lines only
# cv2.line(Mat, (x1, y1), (x2, y2),(255, 255, 255), 1, cv2.CV_AA)
lines_counted.append([x1, y1, x2, y2])
KLogger.set_log('RETURNING_VERT_HORZ_COUNTED_LINES200',
'Returing vertical and horizontal lines')
return lines_counted
def get_mat_binary(self):
''' Method to get binary image '''
KLogger.set_log('BINARY204', 'Getting Binary Mat')
return self.Mat_Thresh
def get_mat_rgb(self):
''' Method to get rgb image '''
KLogger.set_log('RGB204', 'Getting RGB Mat')
return self.Mat_Rgb
def get_mat_gray(self):
''' Method to get gray image '''
KLogger.set_log('Gray204', 'Getting Gray Mat')
return self.Mat_Gray
def set_mat_gray(self, mat_gray):
''' Method to set gray image '''
self.Mat_Gray = mat_gray
KLogger.set_log('GRAY202', 'Setting GrayScale from method')
def set_mat_binary(self, mat_binary):
''' Method to set rgb image '''
self.Mat_Thresh = mat_binary
KLogger.set_log('BINARY202', 'Setting Threshold/Binary from method')
def set_mat_rgb(self, mat_rgb):
''' Method to set rgb image '''
self.Mat_Rgb = mat_rgb
KLogger.set_log('RGB202', 'Setting RGB from method')
def convert_to_zero_and_one(self):
''' Method to create binary image into zero and one '''
KLogger.set_log(
'ZERO2ONE404', 'Not implemented')
def image_thresholding(self, min_thresh, max_thresh, THRESH_CODE=cv2.THRESH_BINARY):
self.Mat_Thresh = cv2.threshold(
self.Mat_Gray, min_thresh, max_thresh, THRESH_CODE)[1]
KLogger.set_log(
'THRESH200', f'Thresholding from {min_thresh} to {max_thresh}')
def convert_to_grayscale(self):
''' Convert an Image From RGB to GrayScale '''
self.Mat_Gray = cv2.cvtColor(self.Mat_Rgb, cv2.COLOR_BGR2GRAY)
KLogger.set_log('GRAY200', 'Converting RGB to Grayscale')
def load_image(self, image_path):
''' Load image from the path into the Mat RGB '''
self.Image_Path = image_path
self.Mat_Rgb = cv2.imread(self.Image_Path, cv2.IMREAD_COLOR)
KLogger.set_log('RGB200', 'Reading RGB')