qurator-spk/eynollah
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consistently handle textline mask with respect to drop-capital mask…

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- suppress drop-capital in textline mask for textline contours
- elevate drop-capital in textline mask for reading order boxes
This commit is contained in:
Robert Sachunsky 2026-04-27 13:04:09 +02:00
parent 2641171fb1
commit da9e00cfe5
1 changed files with 6 additions and 6 deletions
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12
src/eynollah/eynollah.py
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@ -2326,18 +2326,17 @@ class Eynollah:
return return
if num_col_classifier in (1,2): if num_col_classifier in (1,2):
org_h_l_m = textline_mask_tot_ea.shape[0] img_h_org, img_w_org = text_regions_p.shape
org_w_l_m = textline_mask_tot_ea.shape[1]
if num_col_classifier == 1: if num_col_classifier == 1:
img_w_new = 2000 img_w_new = 2000
else: else:
img_w_new = 2400 img_w_new = 2400
img_h_new = img_w_new * textline_mask_tot_ea.shape[0] // textline_mask_tot_ea.shape[1] img_h_new = img_w_new * img_h_org // img_w_org
text_regions_p_new = resize_image(text_regions_p, img_h_new, img_w_new) text_regions_p_new = resize_image(text_regions_p, img_h_new, img_w_new)
table_prediction_new = resize_image(table_prediction, img_h_new, img_w_new) table_prediction_new = resize_image(table_prediction, img_h_new, img_w_new)
self.run_marginals(num_col_classifier, slope_deskew, text_regions_p_new, table_prediction_new) self.run_marginals(num_col_classifier, slope_deskew, text_regions_p_new, table_prediction_new)
text_regions_p = resize_image(text_regions_p_new, org_h_l_m, org_w_l_m) text_regions_p = resize_image(text_regions_p_new, img_h_org, img_w_org)
if self.plotter: if self.plotter:
self.plotter.save_plot_of_layout_main_all(text_regions_p, image_page, image['name']) self.plotter.save_plot_of_layout_main_all(text_regions_p, image_page, image['name'])
@ -2353,7 +2352,8 @@ class Eynollah:
table_prediction) table_prediction)
if self.full_layout: if self.full_layout:
textline_mask_tot_ea_org[text_regions_p == label_drop_fl] = 0 textline_mask_tot_ea_org[text_regions_p == label_drop_fl] = 0 # skip for textlines
textline_mask_tot_ea[text_regions_p == label_drop_fl] = 1 # needed for reading order
polygons_of_drop_capitals = return_contours_of_interested_region(text_regions_p, polygons_of_drop_capitals = return_contours_of_interested_region(text_regions_p,
label_drop_fl, label_drop_fl,
min_area=0.00003) min_area=0.00003)
@ -2435,7 +2435,7 @@ class Eynollah:
else: else:
self.logger.info("Mode: Curved line detection") self.logger.info("Mode: Curved line detection")
textline_mask_tot_ea_erode = cv2.erode(textline_mask_tot_ea, kernel=KERNEL, iterations=2) textline_mask_tot_ea_erode = cv2.erode(textline_mask_tot_ea_org, kernel=KERNEL, iterations=2)
all_found_textline_polygons, slopes = \ all_found_textline_polygons, slopes = \
self.get_slopes_and_deskew_new_curved( self.get_slopes_and_deskew_new_curved(
polygons_of_textregions, textline_mask_tot_ea_erode, polygons_of_textregions, textline_mask_tot_ea_erode,