def show_difference(pic_file_path, actual, difference):
the_image = cv2.imread(pic_file_path, 0)
the_image = Image.resize_keeping_ratio_by_height(the_image)
# Display.image(the_image)
actual_number_indexs, actual_digits, actual_number_ragions = actual
if difference:
identified_number_ragions = identify_wrong_number(actual_number_ragions, difference, False)
# identified_number_ragions = identify_wrong_number(actual_number_ragions, difference)
else:
identified_number_ragions = actual_number_ragions
all_number_ragion = join_number_ragions(actual_number_indexs, identified_number_ragions)
all_number_ragion = numpy_helper.transfer_values_quickly(all_number_ragion,{1:255})
# all_number_ragion = Image.colorize(all_number_ragion)
# Display.image(all_number_ragion)
if difference:
wrong_number_ragions = generate_wrong_number_ragions(difference)
wrong_number_ragion = join_number_ragions(actual_number_indexs, wrong_number_ragions)
wrong_number_ragion = Image.resize_keeping_ratio_by_height(wrong_number_ragion, all_number_ragion.shape[0])
wrong_number_ragion = numpy_helper.transfer_values_quickly(wrong_number_ragion,{1:255})
# Display.image(Ragions.join((all_number_ragion, wrong_number_ragion), 1))
# Display.ragions([the_image, all_number_ragion, wrong_number_ragion])
Display.images([Ragions.join((all_number_ragion, wrong_number_ragion),1), the_image])
else:
Display.images([all_number_ragion, the_image])
def show_all(square_ragion, index_and_number_ragions):
'''
just for test
'''
all_number_ragion = []
for index, number_ragion in index_and_number_ragions:
ragion_index = len(all_number_ragion)
if ragion_index < index:
all_number_ragion += [numpy.zeros((1,1)) for i in range(index-ragion_index)]
all_number_ragion.append(number_ragion)
all_number_ragion = Ragions.join_same_size(
Ragions.fill_to_same_size(all_number_ragion), 9)
from picture_sudoku.cv2_helpers.display import Display
Display.ragions([square_ragion, all_number_ragion])
def digit_recognize():
mb = MultipleSvm.load_variables(Smo, RESULT_PATH)
# file_path = '../resource/svm_wrong_digits/pic04_no17_real8_cal3.dataset'
file_path = '../resource/svm_wrong_digits/pic04_no33_real8_cal3.dataset'
# file_path = '../resource/svm_wrong_digits/pic15_no19_real5_cal6_1.dataset'
# file_path = '../resource/svm_wrong_digits/pic15_no19_real5_cal6.dataset'
number_ragion = numpy.mat(Image.read_from_number_file(file_path))
transfered_ragion = numpy_helper.transfer_1to255(number_ragion)
# adjusted_ragion = main_sudoku.adjust_number_ragion(transfered_ragion)
adjusted_ragion = adjust_number_ragion2(transfered_ragion)
# adjusted_ragion = transfered_ragion
Display.ragions([transfered_ragion, adjusted_ragion])
adjusted_ragion = numpy_helper.transfer_255to1(adjusted_ragion)
number_matrix = main_sudoku.transfer_to_digit_matrix(adjusted_ragion)
mb.dag_classify(number_matrix).ppl()
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 show_number_ragions(number_ragions):
all_number_ragions = Ragions.join_same_size(
Ragions.fill_to_same_size(number_ragions), 9)
all_number_ragions = numpy_helper.transfer_values_quickly(all_number_ragions, {1:255})
Display.image(all_number_ragions)
def show_number_matrix(number_matrix):
binary_number_image = number_matrix.reshape((data_file_helper.IMG_SIZE, data_file_helper.IMG_SIZE))
number_image = numpy_helper.transfer_values_quickly(binary_number_image, {1: 255})
number_image = numpy.array(number_image, dtype=numpy.uint8)
# Image.save_to_txt(number_image,'test1.dataset')
Display.image(number_image)
