def split_cell_ragion(intersections, square_ragion):
cell_contours = Points.get_quadrilaterals(intersections, SUDOKU_SIZE, SUDOKU_SIZE)
threshed_square_ragion = square_ragion
# blured_ragion = cv2.GaussianBlur(square_ragion, ksize=(5,5), sigmaX=0)
# threshed_square_ragion = cv2.adaptiveThreshold(blured_ragion,WHITE,
# cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY_INV, blockSize=3, C=3)
# test
# Display.image(threshed_square_ragion)
get_ragion_func = lambda c: Contour.get_rect_ragion(c, threshed_square_ragion)
cell_ragions = map(get_ragion_func, cell_contours)
# from picture_sudoku.helpers.common import Resource
# cv2.imwrite(Resource.get_path('test', 'sample_15_null_38_image.jpg'), cell_ragions[38])
def adjust_one(the_ragion):
# the_ragion = cv2.GaussianBlur(the_ragion, ksize=(5,5), sigmaX=0)
# blockSize = the_ragion.shape[1]/2
# if blockSize % 2 == 0:
# blockSize += 1
# thresholded_ragion = cv2.adaptiveThreshold(the_ragion,WHITE,
# cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY_INV, blockSize=blockSize, C=2)
# thresholded_ragion = Image.threshold_white_with_mean_percent(the_ragion, 0.70)
threshold_value = Ragion.cal_threshold_value(the_ragion, square_ragion, 0.70)
thresholded_ragion = Image.threshold_white(the_ragion, threshold_value)
return thresholded_ragion
cell_ragions = map(adjust_one, cell_ragions)
# flag_test()
# Display.ragions(cell_ragions)
return cell_ragions
def extract_square_from_contour(contour):
the_image = Image.generate_mask(Contour.get_shape(contour))
# Display.contours(the_image, [contour])
cv2.drawContours(the_image, [contour], -1, 255, 1)
# Display.image(the_image)
# lines = PolarLines.find_suitable_lines(the_image)
square_ragion = the_image
vertical_lines = find_vertical_lines(square_ragion)
border_line_count = 2
if len(vertical_lines) > border_line_count:
raise SudokuError("The count of vertical border lines is larger than {0}".format(border_line_count))
horizontal_lines = find_horizontal_lines(square_ragion)
if len(horizontal_lines) > border_line_count:
raise SudokuError("The count of horizontal border lines is larger than {0}".format(border_line_count))
Display.polar_lines(square_ragion, vertical_lines + horizontal_lines)
# Display.polar_lines(square_ragion, horizontal_lines)
intersections = main_analyzer.find_intersections(vertical_lines, horizontal_lines)
# intersections.ppl()
Points.to_contour(intersections).ppl()
def extract_square_from_contour(contour):
'''
it will extract square from the contour which could have many noise points.
'''
the_image = Image.generate_mask(Contour.get_shape(contour))
# Display.contours(the_image, [contour])
cv2.drawContours(the_image, [contour], -1, 255 ,1)
# Display.image(the_image)
# lines = PolarLines.find_suitable_lines(the_image)
square_ragion = the_image
vertical_lines = find_vertical_lines(square_ragion)
horizontal_lines = find_horizontal_lines(square_ragion)
# flag_test()
# Display.polar_lines(square_ragion, vertical_lines+horizontal_lines)
border_line_count = 2
if len(vertical_lines) > border_line_count:
logger.info("The count of vertical border lines is larger than {0}"
.format(border_line_count))
vertical_lines = [vertical_lines[0],vertical_lines[-1]]
if len(horizontal_lines) > border_line_count:
logger.info("The count of horizontal border lines is larger than {0}"
.format(border_line_count))
horizontal_lines = [horizontal_lines[0],horizontal_lines[-1]]
# flag_test()
# Display.polar_lines(square_ragion, vertical_lines+horizontal_lines)
intersections = find_intersections(vertical_lines, horizontal_lines)
# intersections.ppl()
square_contour = Points.to_contour(intersections)
# order the points
square_contour = Points.to_contour(Quadrilateral.vertices(square_contour))
# 'test'.pl()
# Display.contours(the_image,[square_contour])
return square_contour