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further untangle run

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Konstantin Baierer 2021-02-05 17:26:45 +01:00
parent bf6eaafbc7
commit 9dca742694
1 changed files with 424 additions and 430 deletions
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102
sbb_newspapers_org_image/eynollah.py
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@ -705,7 +705,9 @@ class eynollah:
del img
del imgray
K.clear_session()
gc.collect()
self.logger.debug("exit extract_page")
return croped_page, page_coord
def extract_text_regions(self, img, patches, cols):
@ -2140,6 +2142,45 @@ class eynollah:
return self.do_order_of_regions_full_layout(*args, **kwargs)
return self.do_order_of_regions_no_full_layout(*args, **kwargs)
def run_graphics_and_columns(self, text_regions_p_1, num_column_is_classified):
img_g = cv2.imread(self.image_filename, cv2.IMREAD_GRAYSCALE)
img_g = img_g.astype(np.uint8)
img_g3 = np.zeros((img_g.shape[0], img_g.shape[1], 3))
img_g3 = img_g3.astype(np.uint8)
img_g3[:, :, 0] = img_g[:, :]
img_g3[:, :, 1] = img_g[:, :]
img_g3[:, :, 2] = img_g[:, :]
image_page, page_coord = self.extract_page()
if self.plotter:
self.plotter.save_page_image(image_page)
img_g3_page = img_g3[page_coord[0] : page_coord[1], page_coord[2] : page_coord[3], :]
text_regions_p_1 = text_regions_p_1[page_coord[0] : page_coord[1], page_coord[2] : page_coord[3]]
mask_images = (text_regions_p_1[:, :] == 2) * 1
mask_images = mask_images.astype(np.uint8)
mask_images = cv2.erode(mask_images[:, :], self.kernel, iterations=10)
mask_lines = (text_regions_p_1[:, :] == 3) * 1
mask_lines = mask_lines.astype(np.uint8)
img_only_regions_with_sep = ((text_regions_p_1[:, :] != 3) & (text_regions_p_1[:, :] != 0)) * 1
img_only_regions_with_sep = img_only_regions_with_sep.astype(np.uint8)
img_only_regions = cv2.erode(img_only_regions_with_sep[:, :], self.kernel, iterations=6)
try:
num_col, peaks_neg_fin = find_num_col(img_only_regions, multiplier=6.0)
if not num_column_is_classified:
num_col_classifier = num_col + 1
except:
num_col = None
peaks_neg_fin = []
num_col_classifier = None
return num_col, num_col_classifier, img_only_regions, page_coord, image_page, mask_images, mask_lines
def run_enhancement(self):
self.logger.info("resize and enhance image")
is_image_enhanced, img_org, img_res, _, num_column_is_classified = self.resize_and_enhance_image_with_column_classifier()
@ -2163,6 +2204,7 @@ class eynollah:
self.get_image_and_scales_after_enhancing(img_org, img_res)
return img_res, is_image_enhanced, num_column_is_classified
def run(self):
"""
Get image and scales, then extract the page of scanned image
@ -2177,65 +2219,17 @@ class eynollah:
t1 = time.time()
text_regions_p_1 = self.get_regions_from_xy_2models(img_res, is_image_enhanced)
self.logger.info("Textregion detection took %ss ", str(time.time() - t1))
t1 = time.time()
img_g = cv2.imread(self.image_filename, cv2.IMREAD_GRAYSCALE)
img_g = img_g.astype(np.uint8)
img_g3 = np.zeros((img_g.shape[0], img_g.shape[1], 3))
img_g3 = img_g3.astype(np.uint8)
img_g3[:, :, 0] = img_g[:, :]
img_g3[:, :, 1] = img_g[:, :]
img_g3[:, :, 2] = img_g[:, :]
image_page, page_coord = self.extract_page()
# print(image_page.shape,'page')
if self.plotter:
self.plotter.save_page_image(image_page)
K.clear_session()
gc.collect()
img_g3_page = img_g3[page_coord[0] : page_coord[1], page_coord[2] : page_coord[3], :]
del img_g3
del img_g
text_regions_p_1 = text_regions_p_1[page_coord[0] : page_coord[1], page_coord[2] : page_coord[3]]
mask_images = (text_regions_p_1[:, :] == 2) * 1
mask_images = mask_images.astype(np.uint8)
mask_images = cv2.erode(mask_images[:, :], self.kernel, iterations=10)
mask_lines = (text_regions_p_1[:, :] == 3) * 1
mask_lines = mask_lines.astype(np.uint8)
img_only_regions_with_sep = ((text_regions_p_1[:, :] != 3) & (text_regions_p_1[:, :] != 0)) * 1
img_only_regions_with_sep = img_only_regions_with_sep.astype(np.uint8)
img_only_regions = cv2.erode(img_only_regions_with_sep[:, :], self.kernel, iterations=6)
try:
num_col, peaks_neg_fin = find_num_col(img_only_regions, multiplier=6.0)
if not num_column_is_classified:
num_col_classifier = num_col + 1
except:
num_col = None
peaks_neg_fin = []
num_col, num_col_classifier, img_only_regions, page_coord, image_page, mask_images, mask_lines = self.run_graphics_and_columns(text_regions_p_1, num_column_is_classified)
self.logger.info("Graphics detection took %ss ", str(time.time() - t1))
#print(num_col, "num_colnum_col")
if not num_col:
self.logger.info("No columns detected, outputting an empty PAGE-XML")
txt_con_org = []
order_text_new = []
id_of_texts_tot = []
all_found_texline_polygons = []
all_box_coord = []
polygons_of_images = []
polygons_of_marginals = []
all_found_texline_polygons_marginals = []
all_box_coord_marginals = []
slopes = []
slopes_marginals = []
self.write_into_page_xml(txt_con_org, page_coord, self.dir_out, order_text_new, id_of_texts_tot, all_found_texline_polygons, all_box_coord, polygons_of_images, polygons_of_marginals, all_found_texline_polygons_marginals, all_box_coord_marginals, self.curved_line, slopes, slopes_marginals)
else:
self.write_into_page_xml([], page_coord, self.dir_out, [], [], [], [], [], [], [], [], self.curved_line, [], [])
self.logger.info("Job done in %ss", str(time.time() - t1))
return
patches = True
scaler_h_textline = 1 # 1.2#1.2
scaler_w_textline = 1 # 0.9#1