segmentation_characters.py

import os
import numpy as np
import cv2

from functions_characters import fix_i_j

def get_characters(raw_image,max_line_height,line,word):

	# === Find Contours

	mo_image = raw_image.copy()
	_,contour0,__ = cv2.findContours(mo_image.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
	#print('segmentation_char, contour0',contour0[0])
	contours = [cv2.approxPolyDP(cnt,2,True) for cnt in contour0[0]]

	# === Extract Bounding Rectangles
	maxArea = 0
	rect=[]
	for ctr in contours:
		maxArea = max(maxArea,cv2.contourArea(ctr))

	areaRatio = 0.008

	for ctr in contour0:
		if cv2.contourArea(ctr) > maxArea * areaRatio:
			rect.append(cv2.boundingRect(cv2.approxPolyDP(ctr,1,True)))

	#Find max_line_height and width
	max_w = 0

	for i in rect:
		x = i[0]
		y = i[1]
		w = i[2]
		h = i[3]

		if(w>max_w):
			max_w = w

	# Sort rect left to right, top to bottom, plus correct the dots and commas

	#sort all rect by their x
	rect.sort(key=lambda b: b[0])

	#There are two contours detected for the characters such as i and j. So we need to merge two contours of 'dot' and the 'base' of i and j
	#Fix i and j
	rect = fix_i_j(rect, max_line_height, max_w)

	# remove artifacts - usually artifacts found are manipulated as 0 height by the i&j dot fixing functions
	minus_count = 0
	minus_list = []
	for i in rect:
		x = i[0]
		y = i[1]
		w = i[2]
		h = i[3]

		if h<0:
			minus_list.append(minus_count)

		minus_count = minus_count + 1

	rect = np.delete(rect, minus_list, axis=0)
	# ================= end ===============================

	rect_segmented_image = mo_image.copy()

	symbols=[]

	all_letters = []

	#count used for filename naming
	count = 0

	#raw_input('>')
	for i in rect:
		x = i[0]
		y = i[1]
		w = i[2]
		h = i[3]

		p1 = (x,y)
		p2 = (x+w,y+h)

		letter = mo_image[y:y+h,x:x+w]

		#resize letter image to 32x32 ======================================
		#resize letter content to 28x28

		o_height = letter.shape[0]
		o_width = letter.shape[1]

		#if errors occurs due to the unwanted artifacts, then the height will somehow become zero.
		if (o_height == 0):
			letter = np.zeros((30, 30, 1), np.uint8)
			o_height = letter.shape[0]
			o_width = letter.shape[1]

		#resize height to 28 pixels
		#we need three different conditions to work well with the aspect ratios

		if(o_height>o_width): # height greater than width

			aspectRatio = o_width / (o_height*1.0)

			height = 26
			width = int(height * aspectRatio)
			letter = cv2.resize(letter, (width,height))

			#add border which results adding of padding

			remaining_pixels_w = abs(32 - letter.shape[1])
			add_left = remaining_pixels_w // 2
			type(add_left)
			add_right = remaining_pixels_w - add_left
			letter = cv2.copyMakeBorder(letter, 0, 0, add_left, add_right, cv2.BORDER_CONSTANT, value=(0,0,0))

			remaining_pixels_h = abs(32 - letter.shape[0])
			add_top = remaining_pixels_h // 2
			add_bottom = remaining_pixels_h - add_top
			letter = cv2.copyMakeBorder(letter, add_top, add_bottom, 0, 0, cv2.BORDER_CONSTANT, value=(0,0,0))

			# =================

		elif(o_width>o_height): # width greater than height

			aspectRatio = o_height / (o_width*1.0)

			width = 26
			height = int(width * aspectRatio)

			letter = cv2.resize(letter, (width,height))

			#add border which results adding of padding
			remaining_pixels_w = abs(32 - letter.shape[1])
			add_left = remaining_pixels_w // 2
			add_right = remaining_pixels_w - add_left
			letter = cv2.copyMakeBorder(letter, 0, 0, add_left, add_right, cv2.BORDER_CONSTANT, value=(0,0,0))

			remaining_pixels_h = abs(32 - letter.shape[0])
			add_top = remaining_pixels_h // 2
			add_bottom = remaining_pixels_h - add_top
			letter = cv2.copyMakeBorder(letter, add_top, add_bottom, 0, 0, cv2.BORDER_CONSTANT, value=(0,0,0))

			# =================

		else: # both height and width equal
			letter = cv2.resize(letter, (26,26))

			#add border which results adding of padding
			remaining_pixels_w = abs(32 - letter.shape[1])
			add_left = remaining_pixels_w // 2
			add_right = remaining_pixels_w - add_left
			letter = cv2.copyMakeBorder(letter, 0, 0, add_left, add_right, cv2.BORDER_CONSTANT, value=(0,0,0))

			remaining_pixels_h = abs(32 - letter.shape[0])
			add_top = remaining_pixels_h // 2
			add_bottom = remaining_pixels_h - add_top
			letter = cv2.copyMakeBorder(letter, add_top, add_bottom, 0, 0, cv2.BORDER_CONSTANT, value=(0,0,0))

			# =================


		cv2.imwrite('img/'+str(line)+'_'+str(word)+'_'+str(count)+'.png', letter)
		count = count + 1

		letter = letter / 255.0

		letter = np.reshape(letter,(1024,1))

		all_letters.append(letter)

		#=================================

		cv2.rectangle(rect_segmented_image,p1,p2,255,1)

	cv2.imwrite('segmented.png', rect_segmented_image)

	return all_letters