qurator-spk/eynollah
1
0
Fork 0
mirror of https://github.com/qurator-spk/eynollah.git synced 2025-11-17 01:44:14 +01:00
Code Issues Projects Releases Wiki Activity

back to rotate_image instead of rotation_image_new for deskewing

Browse source 
(because the latter does not preserve coordinates;
 it scales, even when resizing the image;
 this caused coordinate problems when matching deskewed contours)
This commit is contained in:
Robert Sachunsky 2025-11-15 14:29:41 +01:00
parent 4475183f08
commit 3c15c4f7d4
1 changed files with 13 additions and 45 deletions
Download patch file Download diff file Expand all files Collapse all files

58
src/eynollah/eynollah.py
View file

@ -88,12 +88,7 @@ from .utils.contour import (
join_polygons, join_polygons,
make_intersection, make_intersection,
) )
from .utils.rotate import ( from .utils.rotate import rotate_image
rotate_image,
rotation_not_90_func,
rotation_not_90_func_full_layout,
rotation_image_new
)
from .utils.utils_ocr import ( from .utils.utils_ocr import (
return_start_and_end_of_common_text_of_textline_ocr_without_common_section, return_start_and_end_of_common_text_of_textline_ocr_without_common_section,
return_textline_contour_with_added_box_coordinate, return_textline_contour_with_added_box_coordinate,
@ -3131,11 +3126,9 @@ class Eynollah:
self.logger.debug('enter run_boxes_no_full_layout') self.logger.debug('enter run_boxes_no_full_layout')
t_0_box = time.time() t_0_box = time.time()
if np.abs(slope_deskew) >= SLOPE_THRESHOLD: if np.abs(slope_deskew) >= SLOPE_THRESHOLD:
_, textline_mask_tot_d, text_regions_p_d, table_prediction_n = rotation_not_90_func( textline_mask_tot_d = rotate_image(textline_mask_tot, slope_deskew)
image_page, textline_mask_tot, text_regions_p, table_prediction, slope_deskew) text_regions_p_d = rotate_image(text_regions_p, slope_deskew)
text_regions_p_d = resize_image(text_regions_p_d, text_regions_p.shape[0], text_regions_p.shape[1]) table_prediction_n = rotate_image(table_prediction, slope_deskew)
textline_mask_tot_d = resize_image(textline_mask_tot_d, text_regions_p.shape[0], text_regions_p.shape[1])
table_prediction_n = resize_image(table_prediction_n, text_regions_p.shape[0], text_regions_p.shape[1])
regions_without_separators_d = (text_regions_p_d[:, :] == 1) * 1 regions_without_separators_d = (text_regions_p_d[:, :] == 1) * 1
if self.tables: if self.tables:
regions_without_separators_d[table_prediction_n[:,:] == 1] = 1 regions_without_separators_d[table_prediction_n[:,:] == 1] = 1
@ -3276,20 +3269,9 @@ class Eynollah:
text_regions_p[:,:][table_prediction[:,:]==1] = 10 text_regions_p[:,:][table_prediction[:,:]==1] = 10
img_revised_tab = text_regions_p[:,:] img_revised_tab = text_regions_p[:,:]
if np.abs(slope_deskew) >= SLOPE_THRESHOLD: if np.abs(slope_deskew) >= SLOPE_THRESHOLD:
_, textline_mask_tot_d, text_regions_p_d, table_prediction_n = \ textline_mask_tot_d = rotate_image(textline_mask_tot, slope_deskew)
rotation_not_90_func(image_page, textline_mask_tot, text_regions_p, text_regions_p_d = rotate_image(text_regions_p, slope_deskew)
table_prediction, slope_deskew) table_prediction_n = rotate_image(table_prediction, slope_deskew)
text_regions_p_d = resize_image(text_regions_p_d,
text_regions_p.shape[0],
text_regions_p.shape[1])
textline_mask_tot_d = resize_image(textline_mask_tot_d,
text_regions_p.shape[0],
text_regions_p.shape[1])
table_prediction_n = resize_image(table_prediction_n,
text_regions_p.shape[0],
text_regions_p.shape[1])
regions_without_separators_d = (text_regions_p_d[:,:] == 1)*1 regions_without_separators_d = (text_regions_p_d[:,:] == 1)*1
regions_without_separators_d[table_prediction_n[:,:] == 1] = 1 regions_without_separators_d[table_prediction_n[:,:] == 1] = 1
else: else:
@ -3303,20 +3285,9 @@ class Eynollah:
else: else:
if np.abs(slope_deskew) >= SLOPE_THRESHOLD: if np.abs(slope_deskew) >= SLOPE_THRESHOLD:
_, textline_mask_tot_d, text_regions_p_d, table_prediction_n = \ textline_mask_tot_d = rotate_image(textline_mask_tot, slope_deskew)
rotation_not_90_func(image_page, textline_mask_tot, text_regions_p, text_regions_p_d = rotate_image(text_regions_p, slope_deskew)
table_prediction, slope_deskew) table_prediction_n = rotate_image(table_prediction, slope_deskew)
text_regions_p_d = resize_image(text_regions_p_d,
text_regions_p.shape[0],
text_regions_p.shape[1])
textline_mask_tot_d = resize_image(textline_mask_tot_d,
text_regions_p.shape[0],
text_regions_p.shape[1])
table_prediction_n = resize_image(table_prediction_n,
text_regions_p.shape[0],
text_regions_p.shape[1])
regions_without_separators_d = (text_regions_p_d[:,:] == 1)*1 regions_without_separators_d = (text_regions_p_d[:,:] == 1)*1
regions_without_separators_d[table_prediction_n[:,:] == 1] = 1 regions_without_separators_d[table_prediction_n[:,:] == 1] = 1
else: else:
@ -3465,12 +3436,9 @@ class Eynollah:
#plt.show() #plt.show()
####if not self.tables: ####if not self.tables:
if np.abs(slope_deskew) >= SLOPE_THRESHOLD: if np.abs(slope_deskew) >= SLOPE_THRESHOLD:
_, textline_mask_tot_d, text_regions_p_d, regions_fully_n = rotation_not_90_func_full_layout( textline_mask_tot_d = rotate_image(textline_mask_tot, slope_deskew)
image_page, textline_mask_tot, text_regions_p, regions_fully, slope_deskew) text_regions_p_d = rotate_image(text_regions_p, slope_deskew)
regions_fully_n = rotate_image(regions_fully, slope_deskew)
text_regions_p_d = resize_image(text_regions_p_d, text_regions_p.shape[0], text_regions_p.shape[1])
textline_mask_tot_d = resize_image(textline_mask_tot_d, text_regions_p.shape[0], text_regions_p.shape[1])
regions_fully_n = resize_image(regions_fully_n, text_regions_p.shape[0], text_regions_p.shape[1])
if not self.tables: if not self.tables:
regions_without_separators_d = (text_regions_p_d[:, :] == 1) * 1 regions_without_separators_d = (text_regions_p_d[:, :] == 1) * 1
else: else: