def generate_report():
report = MdUtils(file_name=f'./report.md')
report.new_header(level=1, title='Текстурный анализ')
report.new_line(text='Выполнил Ахманов Алексей Б18-514')
for im in IMAGES:
image_path = f'{helpers.folder_helper.IMAGES_FOLDER_PATH}/{im}'
processed_image_folder_path = f'{image_path}_processed'
os.makedirs(processed_image_folder_path, exist_ok=True)
series_length_matrix_image_path = f'{processed_image_folder_path}/{im}_series_length_matrix.png'
image = Image.open(image_path).convert(constants.constants.RGB_MODE)
grayscaled = grayscale.grayscale.mean_grayscale(image)
# Series length matrix
draw.draw.draw_series_length_matrix(grayscale.grayscale.mean_grayscale(image)).save(series_length_matrix_image_path)
# SRE
sre = texturing.texturing.sre_coefficient(grayscaled)
# Report
report.new_header(level=2, title=f'{im} (SRE = {sre})')
report.new_header(level=3, title='Исходная картинка')
report.new_line(report.new_inline_image(text='Исходная картинка', path=image_path))
report.new_header(level=3, title='Матрица длин серий')
report.new_line(report.new_inline_image(text='Матрица длин серий', path=series_length_matrix_image_path))
report.create_md_file()
def generate_report():
report = MdUtils(file_name=f'./report.md')
report.new_header(level=1, title='Контрастирование')
report.new_line(text='Выполнил Ахманов Алексей Б18-514')
for im in IMAGES:
image_path = f'{helpers.folder_helper.IMAGES_FOLDER_PATH}/{im}'
processed_image_folder_path = f'{image_path}_processed'
os.makedirs(processed_image_folder_path, exist_ok=True)
grayscaled_image_path = f'{processed_image_folder_path}/{im}_grayscaled.png'
linear_contrasted_image_path = f'{processed_image_folder_path}/{im}_linear_contrasted.png'
power_transformed_image_path = f'{processed_image_folder_path}/{im}_power_transformed_gamma=#.png'
image = Image.open(fp=image_path).convert(constants.RGB_MODE)
grayscaled = grayscale.mean_grayscale(image)
grayscaled.save(grayscaled_image_path)
# Contrasting
enhancement.contrasting.linear_contrasting(grayscaled).save(
linear_contrasted_image_path)
for gamma in numpy.arange(START_GAMMA, STOP_GAMMA, STEP_GAMMA):
gamma = round(gamma, GAMMA_ROUND_SIGNS)
enhancement.contrasting.power_transformation(grayscaled, gamma=gamma)\
.save(power_transformed_image_path.replace('#', str(gamma)))
# Report
report.new_header(level=2, title=f'{im}')
report.new_header(level=3, title='Исходная картинка')
report.new_line(
report.new_inline_image(text='Исходная картинка', path=image_path))
report.new_header(level=3, title='Оттенки серого')
report.new_line(
report.new_inline_image(text='Оттенки серого',
path=grayscaled_image_path))
report.new_header(level=3, title='Линейное контрастирование')
report.new_line(
report.new_inline_image(text='Линейное контрастирование',
path=linear_contrasted_image_path))
report.new_header(level=3, title='Степенное преобразование')
for gamma in numpy.arange(START_GAMMA, STOP_GAMMA, STEP_GAMMA):
gamma = round(gamma, GAMMA_ROUND_SIGNS)
report.new_header(level=4, title=f'Gamma = {gamma}')
report.new_line(
report.new_inline_image(
text='Степенное преобразование',
path=power_transformed_image_path.replace('#',
str(gamma))))
report.create_md_file()
def generate_report():
report = MdUtils(file_name=f'./report.md')
report.new_header(level=1, title='Сегментация текста')
report.new_line(text='Выполнил Ахманов Алексей Б18-514')
report.new_line(text=f'Алфавит - {ALPHABET}')
report.new_line(text=f'Исходная фраза - {PHRASE}')
# Phrase
phrase_image_path = f'{folder_helper.IMAGES_FOLDER_PATH}/phrase.png'
phrase_projections_image_path = f'{folder_helper.IMAGES_FOLDER_PATH}/phrase_projections.png'
phrase_segments_image_path = f'{folder_helper.IMAGES_FOLDER_PATH}/phrase_segments.png'
phrase_result_image_path = f'{folder_helper.IMAGES_FOLDER_PATH}/phrase_result.png'
phrase_image = Image.new(mode=GRAYSCALE_MODE,
size=(1200, FONT_SIZE),
color=WHITE)
result = ImageDraw.Draw(im=phrase_image, mode=GRAYSCALE_MODE)
result.text(xy=(0, 0), text=PHRASE, font=FONT, fill=0, anchor='lt')
phrase_image = cut_empty_rows_and_cols(phrase_image)
phrase_image.save(phrase_image_path)
phrase_projections_image = draw.draw_projections(phrase_image)
phrase_projections_image.save(phrase_projections_image_path)
phrase_segments_image = draw.draw_symbol_segments(phrase_image,
SYMBOLS_DIFF_THRESHOLD)
phrase_segments_image.save(phrase_segments_image_path)
phrase_result_image = phrase_projections_image.copy()
phrase_result_image.paste(im=phrase_segments_image, box=(30, 0))
phrase_result_image.save(phrase_result_image_path)
# Report
report.new_header(level=2, title='Картинка с фразой')
report.new_line(
report.new_inline_image(text='Картинка с фразой',
path=phrase_image_path))
report.new_header(level=2, title='Картинка с профилями')
report.new_line(
report.new_inline_image(text='Картинка с профилями',
path=phrase_projections_image_path))
report.new_header(level=2, title='Картинка с сегментами символов')
report.new_line(
report.new_inline_image(text='Картинка с сегментами символов',
path=phrase_segments_image_path))
report.new_header(level=2, title='Картинка с результатом')
report.new_line(
report.new_inline_image(text='Картинка с результатом',
path=phrase_result_image_path))
report.create_md_file()
def generate_report():
report = MdUtils(file_name='./report.md')
report.new_header(level=1, title='Фильтры и морфология')
report.new_line(text='Выполнил Ахманов Алексей Б18-514')
for im in IMAGES:
image_path = f'{folder_helper.IMAGES_FOLDER_PATH}/{im}'
processed_image_folder_path = f'{image_path}_processed'
os.makedirs(processed_image_folder_path, exist_ok=True)
image = Image.open(image_path).convert(constants.RGB_MODE)
# Smoothing
spatial_smoothed_image_path = f'{processed_image_folder_path}/{im}_spatial_smoothed.png'
spatial_smoothed_difference_image_path = f'{processed_image_folder_path}/{im}_spatial_smoothed_difference.png'
grayscaled = grayscale.mean_grayscale(image)
filtration.spatial_smoothing(grayscaled).save(
spatial_smoothed_image_path)
filtration.spatial_smoothing_difference(grayscaled).save(
spatial_smoothed_difference_image_path)
# Report
report.new_header(level=2, title=f'{im}')
report.new_header(level=3, title='Исходная картинка')
report.new_line(
report.new_inline_image(text='Исходная картинка', path=image_path))
report.new_header(level=3, title='Пространственное сглаживание')
report.new_line(
report.new_inline_image(text='Пространственное сглаживание',
path=spatial_smoothed_image_path))
report.new_header(level=3, title='Разница сглаженной и исходной')
report.new_line(
report.new_inline_image(
text='Разница сглаженной и исходной',
path=spatial_smoothed_difference_image_path))
report.create_md_file()
def generate_report():
report = MdUtils(file_name='./report.md')
report.new_header(level=1, title='Контуры')
report.new_line(text='Выполнил Ахманов Алексей Б18-514')
for im in IMAGES:
image_path = f'{folder_helper.IMAGES_FOLDER_PATH}/{im}'
processed_image_folder_path = f'{image_path}_processed'
os.makedirs(processed_image_folder_path, exist_ok=True)
image = Image.open(image_path).convert(constants.RGB_MODE)
# Outline
smoothed_image_path = f'{processed_image_folder_path}/{im}_grayscaled.png'
roberts_cross_x_image_path = f'{processed_image_folder_path}/{im}_roberts_cross_x.png'
roberts_cross_y_image_path = f'{processed_image_folder_path}/{im}_roberts_cross_y.png'
roberts_cross_image_path = f'{processed_image_folder_path}/{im}_roberts_cross.png'
roberts_cross_normalized_image_path = f'{processed_image_folder_path}/{im}_roberts_cross_normalized_#.png'
grayscaled = grayscale.mean_grayscale(image)
smoothed = filtration.spatial_smoothing(grayscaled)
smoothed.save(smoothed_image_path)
filtration.roberts_cross_x(smoothed).save(roberts_cross_x_image_path)
filtration.roberts_cross_y(smoothed).save(roberts_cross_y_image_path)
filtration.roberts_cross(smoothed).save(roberts_cross_image_path)
for i in range(10, 31):
filtration.roberts_cross_threshold(smoothed, i).save(
roberts_cross_normalized_image_path.replace('#', f'{i}'))
# Report
report.new_header(level=2, title=f'{im}')
report.new_header(level=3, title='Исходная картинка')
report.new_line(
report.new_inline_image(text='Исходная картинка', path=image_path))
report.new_header(level=3, title='Сглаженные оттенки серого')
report.new_line(
report.new_inline_image(text='Сглаженные оттенки серого',
path=smoothed_image_path))
report.new_header(level=3, title='Оператор Робертса 2x2 (x)')
report.new_line(
report.new_inline_image(text='Оператор Робертса 2x2 (x)',
path=roberts_cross_x_image_path))
report.new_header(level=3, title='Оператор Робертса 2x2 (y)')
report.new_line(
report.new_inline_image(text='Оператор Робертса 2x2 (y)',
path=roberts_cross_y_image_path))
report.new_header(level=3, title='Оператор Робертса 2x2')
report.new_line(
report.new_inline_image(text='Оператор Робертса 2x2',
path=roberts_cross_image_path))
report.new_header(level=3,
title='Оператор Робертса 2x2 (нормализованная)')
for i in range(10, 31):
report.new_header(level=4, title=f'Порог {i}')
report.new_line(
report.new_inline_image(
text=f'Порог {i}',
path=roberts_cross_normalized_image_path.replace(
'#', f'{i}')))
report.create_md_file()
def generate_report():
report = MdUtils(file_name='./report.md')
report.new_header(level=1, title='Бинаризация')
report.new_line(text='Выполнил Ахманов Алексей Б18-514')
for im in IMAGES:
image_path = f'{folder_helper.IMAGES_FOLDER_PATH}/{im}'
processed_image_folder_path = f'{image_path}_processed'
os.makedirs(processed_image_folder_path, exist_ok=True)
image = Image.open(image_path).convert(constants.RGB_MODE)
# Sampling
upsampled_integer_number_of_times_image_path = f'{processed_image_folder_path}/{im}_upsampled_m.png'
downsampled_integer_number_of_times_image_path = f'{processed_image_folder_path}/{im}_downsampled_n.png'
oversampled_two_pass_image_path = f'{processed_image_folder_path}/{im}_oversampled_two_pass.png'
oversampled_one_pass_image_path = f'{processed_image_folder_path}/{im}_oversampled_one_pass.png'
sampling.bilinear_interpolation_upsampling(
image,
UPSAMPLE_FACTOR).save(upsampled_integer_number_of_times_image_path)
sampling.decimation_downsampling(image, DOWNSAMPLE_FACTOR).save(
downsampled_integer_number_of_times_image_path)
sampling.decimation_downsampling(
sampling.bilinear_interpolation_upsampling(image, UPSAMPLE_FACTOR),
DOWNSAMPLE_FACTOR).save(oversampled_two_pass_image_path)
sampling.one_pass_resampling(
image, UPSAMPLE_FACTOR,
DOWNSAMPLE_FACTOR).save(oversampled_one_pass_image_path)
# Grayscale
mean_grayscaled_image_path = f'{processed_image_folder_path}/{im}_mean_grayscaled.png'
photoshop_grayscaled_image_path = f'{processed_image_folder_path}/{im}_photoshop_grayscaled.png'
grayscale.mean_grayscale(image).save(mean_grayscaled_image_path)
grayscale.photoshop_grayscale(image).save(
photoshop_grayscaled_image_path)
# Threshold
balansed_hist_thresholded_image_path = f'{processed_image_folder_path}/{im}_balansed_hist_thresholded.png'
thresholding.balansed_histogram_method(grayscale.mean_grayscale(
image)).save(balansed_hist_thresholded_image_path)
# Report
report.new_header(level=2, title=f'{im}')
report.new_header(level=3, title='Исходная картинка')
report.new_line(
report.new_inline_image(text='Исходная картинка', path=image_path))
report.new_header(
level=3, title=f'Интерполяция с коэффициентом {UPSAMPLE_FACTOR}')
report.new_line(
report.new_inline_image(
text=f'Интерполяция с коэффициентом {UPSAMPLE_FACTOR}',
path=upsampled_integer_number_of_times_image_path))
report.new_header(
level=3, title=f'Децимация с коэффициентом {DOWNSAMPLE_FACTOR}')
report.new_line(
report.new_inline_image(
text=f'Децимация с коэффициентом {DOWNSAMPLE_FACTOR}',
path=downsampled_integer_number_of_times_image_path))
report.new_header(
level=3,
title=
f'Двухпроходная передескритизация с коэффициентом {UPSAMPLE_FACTOR}/{DOWNSAMPLE_FACTOR}'
)
report.new_line(
report.new_inline_image(
text=
f'Двухпроходная передескритизация с коэффициентом {UPSAMPLE_FACTOR}/{DOWNSAMPLE_FACTOR}',
path=oversampled_two_pass_image_path))
report.new_header(
level=3,
title=
f'Однопроходная передескритизация с коэффициентом {UPSAMPLE_FACTOR}/{DOWNSAMPLE_FACTOR}'
)
report.new_line(
report.new_inline_image(
text=
f'Однопроходная передескритизация с коэффициентом {UPSAMPLE_FACTOR}/{DOWNSAMPLE_FACTOR}',
path=oversampled_two_pass_image_path))
report.new_header(level=3, title=f'Оттенки серого')
report.new_line(
report.new_inline_image(text=f'Оттенки серого',
path=mean_grayscaled_image_path))
report.new_header(level=3, title=f'Оттенки серого (как в Photoshop)')
report.new_line(
report.new_inline_image(text=f'Оттенки серого (как в Photoshop)',
path=photoshop_grayscaled_image_path))
report.new_header(level=3,
title=f'Бинаризация (балансировка гистограммы)')
report.new_line(
report.new_inline_image(
text=f'Бинаризация (балансировка гистограммы)',
path=balansed_hist_thresholded_image_path))
report.create_md_file()
