mirror of
https://github.com/qurator-spk/eynollah.git
synced 2025-06-09 04:09:54 +02:00
right2left reading order detection accomplished
This commit is contained in:
vahid
parent
0cda1f3c7a
commit
0b35011847
3 changed files with 52 additions and 260 deletions
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@ -97,6 +97,12 @@ from qurator.eynollah.eynollah import Eynollah
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is_flag=True,
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help="if this parameter set to true, this tool will try to detect tables.",
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)
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@click.option(
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"--right2left/--left2right",
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"-r2l/-l2r",
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is_flag=True,
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help="if this parameter set to true, this tool will extract right-to-left reading order.",
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)
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@click.option(
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"--input_binary/--input-RGB",
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"-ib/-irgb",
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@ -149,6 +155,7 @@ def main(
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textline_light,
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full_layout,
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tables,
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right2left,
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input_binary,
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allow_scaling,
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headers_off,
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@ -184,6 +191,7 @@ def main(
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textline_light=textline_light,
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full_layout=full_layout,
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tables=tables,
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right2left=right2left,
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input_binary=input_binary,
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allow_scaling=allow_scaling,
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headers_off=headers_off,
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@ -72,8 +72,7 @@ from .utils import (
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small_textlines_to_parent_adherence2,
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order_of_regions,
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find_number_of_columns_in_document,
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return_boxes_of_images_by_order_of_reading_new,
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return_boxes_of_images_by_order_of_reading_new_right2left)
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return_boxes_of_images_by_order_of_reading_new)
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from .utils.pil_cv2 import check_dpi, pil2cv
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from .utils.xml import order_and_id_of_texts
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from .plot import EynollahPlotter
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@ -159,6 +158,7 @@ class Eynollah:
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textline_light=False,
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full_layout=False,
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tables=False,
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right2left=False,
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input_binary=False,
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allow_scaling=False,
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headers_off=False,
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@ -190,6 +190,7 @@ class Eynollah:
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self.textline_light = textline_light
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self.full_layout = full_layout
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self.tables = tables
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self.right2left = right2left
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self.input_binary = input_binary
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self.allow_scaling = allow_scaling
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self.headers_off = headers_off
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@ -2623,7 +2624,7 @@ class Eynollah:
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regions_without_separators_d = cv2.erode(regions_without_separators_d[:, :], KERNEL, iterations=6)
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t1 = time.time()
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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boxes, peaks_neg_tot_tables = return_boxes_of_images_by_order_of_reading_new_right2left(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, self.tables)
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boxes, peaks_neg_tot_tables = return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, self.tables, self.right2left)
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boxes_d = None
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self.logger.debug("len(boxes): %s", len(boxes))
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@ -2633,7 +2634,7 @@ class Eynollah:
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img_revised_tab2 = self.add_tables_heuristic_to_layout(text_regions_p_tables, boxes, 0, splitter_y_new, peaks_neg_tot_tables, text_regions_p_tables , num_col_classifier , 0.000005, pixel_line)
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img_revised_tab2, contoures_tables = self.check_iou_of_bounding_box_and_contour_for_tables(img_revised_tab2,table_prediction, 10, num_col_classifier)
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else:
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boxes_d, peaks_neg_tot_tables_d = return_boxes_of_images_by_order_of_reading_new_right2left(splitter_y_new_d, regions_without_separators_d, matrix_of_lines_ch_d, num_col_classifier, erosion_hurts, self.tables)
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boxes_d, peaks_neg_tot_tables_d = return_boxes_of_images_by_order_of_reading_new(splitter_y_new_d, regions_without_separators_d, matrix_of_lines_ch_d, num_col_classifier, erosion_hurts, self.tables, self.right2left)
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boxes = None
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self.logger.debug("len(boxes): %s", len(boxes_d))
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@ -2718,7 +2719,7 @@ class Eynollah:
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pass
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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boxes, peaks_neg_tot_tables = return_boxes_of_images_by_order_of_reading_new_right2left(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, self.tables)
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boxes, peaks_neg_tot_tables = return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, self.tables, self.right2left)
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text_regions_p_tables = np.copy(text_regions_p)
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text_regions_p_tables[:,:][(table_prediction[:,:]==1)] = 10
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pixel_line = 3
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@ -2727,7 +2728,7 @@ class Eynollah:
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img_revised_tab2,contoures_tables = self.check_iou_of_bounding_box_and_contour_for_tables(img_revised_tab2, table_prediction, 10, num_col_classifier)
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else:
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boxes_d, peaks_neg_tot_tables_d = return_boxes_of_images_by_order_of_reading_new_right2left(splitter_y_new_d, regions_without_separators_d, matrix_of_lines_ch_d, num_col_classifier, erosion_hurts, self.tables)
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boxes_d, peaks_neg_tot_tables_d = return_boxes_of_images_by_order_of_reading_new(splitter_y_new_d, regions_without_separators_d, matrix_of_lines_ch_d, num_col_classifier, erosion_hurts, self.tables, self.right2left)
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text_regions_p_tables = np.copy(text_regions_p_1_n)
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text_regions_p_tables = np.round(text_regions_p_tables)
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text_regions_p_tables[:,:][(text_regions_p_tables[:,:]!=3) & (table_prediction_n[:,:]==1)] = 10
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@ -3070,11 +3071,17 @@ class Eynollah:
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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boxes, peaks_neg_tot_tables = return_boxes_of_images_by_order_of_reading_new_right2left(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, self.tables)
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boxes, peaks_neg_tot_tables = return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, self.tables, self.right2left)
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else:
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boxes_d, peaks_neg_tot_tables_d = return_boxes_of_images_by_order_of_reading_new_right2left(splitter_y_new_d, regions_without_separators_d, matrix_of_lines_ch_d, num_col_classifier, erosion_hurts, self.tables)
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boxes_d, peaks_neg_tot_tables_d = return_boxes_of_images_by_order_of_reading_new(splitter_y_new_d, regions_without_separators_d, matrix_of_lines_ch_d, num_col_classifier, erosion_hurts, self.tables, self.right2left)
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#print(boxes_d,'boxes_d')
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#img_once = np.zeros((textline_mask_tot_d.shape[0],textline_mask_tot_d.shape[1]))
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#for box_i in boxes_d:
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#img_once[int(box_i[2]):int(box_i[3]),int(box_i[0]):int(box_i[1]) ] =1
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#plt.imshow(img_once)
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#plt.show()
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#print(np.unique(img_once),'img_once')
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if self.plotter:
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self.plotter.write_images_into_directory(polygons_of_images, image_page)
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t_order = time.time()
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@ -1672,7 +1672,9 @@ def find_number_of_columns_in_document(region_pre_p, num_col_classifier, tables,
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return num_col_fin, peaks_neg_fin_fin,matrix_of_lines_ch,splitter_y_new,separators_closeup_n
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def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, tables):
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def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, tables, right2left_readingorder):
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if right2left_readingorder:
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regions_without_separators = cv2.flip(regions_without_separators,1)
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boxes=[]
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peaks_neg_tot_tables = []
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@ -1763,6 +1765,13 @@ def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_witho
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cy_hor_diff=matrix_new[:,7][ (matrix_new[:,9]==0) ]
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arg_org_hor_some=matrix_new[:,0][ (matrix_new[:,9]==0) ]
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if right2left_readingorder:
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x_max_hor_some_new = regions_without_separators.shape[1] - x_min_hor_some
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x_min_hor_some_new = regions_without_separators.shape[1] - x_max_hor_some
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x_min_hor_some =list(np.copy(x_min_hor_some_new))
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x_max_hor_some =list(np.copy(x_max_hor_some_new))
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@ -2027,6 +2036,7 @@ def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_witho
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columns_not_covered_child_no_mother=np.sort(columns_not_covered_child_no_mother)
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ind_args=np.array(range(len(y_type_2)))
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@ -2335,254 +2345,21 @@ def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_witho
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#else:
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#boxes.append([ 0, regions_without_separators[:,:].shape[1] ,splitter_y_new[i],splitter_y_new[i+1]])
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return boxes, peaks_neg_tot_tables
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def return_boxes_of_images_by_order_of_reading_new_right2left(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, tables):
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boxes=[]
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peaks_neg_tot_tables = []
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for i in range(len(splitter_y_new)-1):
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#print(splitter_y_new[i],splitter_y_new[i+1])
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matrix_new=matrix_of_lines_ch[:,:][ (matrix_of_lines_ch[:,6]> splitter_y_new[i] ) & (matrix_of_lines_ch[:,7]< splitter_y_new[i+1] ) ]
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#print(len( matrix_new[:,9][matrix_new[:,9]==1] ))
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#print(matrix_new[:,8][matrix_new[:,9]==1],'gaddaaa')
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# check to see is there any vertical separator to find holes.
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if 1>0:#len( matrix_new[:,9][matrix_new[:,9]==1] )>0 and np.max(matrix_new[:,8][matrix_new[:,9]==1])>=0.1*(np.abs(splitter_y_new[i+1]-splitter_y_new[i] )):
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try:
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if erosion_hurts:
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num_col, peaks_neg_fin=find_num_col(regions_without_separators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),:], num_col_classifier, tables, multiplier=6.)
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else:
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num_col, peaks_neg_fin=find_num_col(regions_without_separators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),:],num_col_classifier, tables, multiplier=7.)
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except:
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peaks_neg_fin=[]
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num_col = 0
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try:
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peaks_neg_fin_org=np.copy(peaks_neg_fin)
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if (len(peaks_neg_fin)+1)<num_col_classifier or num_col_classifier==6:
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#print('burda')
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if len(peaks_neg_fin)==0:
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num_col, peaks_neg_fin=find_num_col(regions_without_separators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),:],num_col_classifier, tables, multiplier=3.)
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peaks_neg_fin_early=[]
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peaks_neg_fin_early.append(0)
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#print(peaks_neg_fin,'peaks_neg_fin')
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for p_n in peaks_neg_fin:
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peaks_neg_fin_early.append(p_n)
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peaks_neg_fin_early.append(regions_without_separators.shape[1]-1)
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#print(peaks_neg_fin_early,'burda2')
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peaks_neg_fin_rev=[]
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for i_n in range(len(peaks_neg_fin_early)-1):
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#print(i_n,'i_n')
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#plt.plot(regions_without_separators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),peaks_neg_fin_early[i_n]:peaks_neg_fin_early[i_n+1]].sum(axis=0) )
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#plt.show()
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try:
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num_col, peaks_neg_fin1=find_num_col(regions_without_separators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),peaks_neg_fin_early[i_n]:peaks_neg_fin_early[i_n+1]],num_col_classifier,tables, multiplier=7.)
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except:
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peaks_neg_fin1=[]
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try:
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num_col, peaks_neg_fin2=find_num_col(regions_without_separators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),peaks_neg_fin_early[i_n]:peaks_neg_fin_early[i_n+1]],num_col_classifier,tables, multiplier=5.)
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except:
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peaks_neg_fin2=[]
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if len(peaks_neg_fin1)>=len(peaks_neg_fin2):
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peaks_neg_fin=list(np.copy(peaks_neg_fin1))
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else:
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peaks_neg_fin=list(np.copy(peaks_neg_fin2))
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peaks_neg_fin=list(np.array(peaks_neg_fin)+peaks_neg_fin_early[i_n])
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if i_n!=(len(peaks_neg_fin_early)-2):
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peaks_neg_fin_rev.append(peaks_neg_fin_early[i_n+1])
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#print(peaks_neg_fin,'peaks_neg_fin')
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peaks_neg_fin_rev=peaks_neg_fin_rev+peaks_neg_fin
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if len(peaks_neg_fin_rev)>=len(peaks_neg_fin_org):
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peaks_neg_fin=list(np.sort(peaks_neg_fin_rev))
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num_col=len(peaks_neg_fin)
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else:
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peaks_neg_fin=list(np.copy(peaks_neg_fin_org))
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num_col=len(peaks_neg_fin)
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#print(peaks_neg_fin,'peaks_neg_fin')
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except:
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pass
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#num_col, peaks_neg_fin=find_num_col(regions_without_separators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),:],multiplier=7.0)
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x_min_hor_some=matrix_new[:,2][ (matrix_new[:,9]==0) ]
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x_max_hor_some=matrix_new[:,3][ (matrix_new[:,9]==0) ]
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cy_hor_some=matrix_new[:,5][ (matrix_new[:,9]==0) ]
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cy_hor_diff=matrix_new[:,7][ (matrix_new[:,9]==0) ]
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arg_org_hor_some=matrix_new[:,0][ (matrix_new[:,9]==0) ]
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peaks_neg_tot=return_points_with_boundies(peaks_neg_fin,0, regions_without_separators[:,:].shape[1])
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peaks_neg_tot_tables.append(peaks_neg_tot)
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reading_order_type,x_starting,x_ending,y_type_2,y_diff_type_2,y_lines_without_mother,x_start_without_mother,x_end_without_mother,there_is_sep_with_child,y_lines_with_child_without_mother,x_start_with_child_without_mother,x_end_with_child_without_mother,new_main_sep_y=return_x_start_end_mothers_childs_and_type_of_reading_order(x_min_hor_some,x_max_hor_some,cy_hor_some,peaks_neg_tot,cy_hor_diff)
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y_lines_by_order=[]
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x_start_by_order=[]
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x_end_by_order=[]
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if len(x_starting)>0:
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all_columns = np.array(range(len(peaks_neg_tot)-1))
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columns_covered_by_lines_covered_more_than_2col=[]
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for dj in range(len(x_starting)):
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if set( list(np.array(range(x_starting[dj],x_ending[dj])) ) ) == set(all_columns):
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pass
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else:
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columns_covered_by_lines_covered_more_than_2col=columns_covered_by_lines_covered_more_than_2col+list(np.array(range(x_starting[dj],x_ending[dj])) )
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columns_covered_by_lines_covered_more_than_2col=list(set(columns_covered_by_lines_covered_more_than_2col))
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columns_not_covered=list( set(all_columns)-set(columns_covered_by_lines_covered_more_than_2col) )
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y_type_2=list(y_type_2)
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x_starting=list(x_starting)
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x_ending=list(x_ending)
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for lj in columns_not_covered:
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y_type_2.append(int(splitter_y_new[i]))
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x_starting.append(lj)
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x_ending.append(lj+1)
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##y_lines_by_order.append(int(splitter_y_new[i]))
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##x_start_by_order.append(0)
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#y_type_2.append(int(splitter_y_new[i]))
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#x_starting.append(x_starting[0])
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#x_ending.append(x_ending[0])
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if len(new_main_sep_y)>0:
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y_type_2.append(int(splitter_y_new[i]))
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x_starting.append(0)
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x_ending.append(len(peaks_neg_tot)-1)
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else:
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y_type_2.append(int(splitter_y_new[i]))
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x_starting.append(x_starting[0])
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x_ending.append(x_ending[0])
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y_type_2=np.array(y_type_2)
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x_starting=np.array(x_starting)
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x_ending=np.array(x_ending)
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else:
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all_columns=np.array(range(len(peaks_neg_tot)-1))
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columns_not_covered=list( set(all_columns) )
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y_type_2=list(y_type_2)
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x_starting=list(x_starting)
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x_ending=list(x_ending)
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for lj in columns_not_covered:
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y_type_2.append(int(splitter_y_new[i]))
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x_starting.append(lj)
|
||||
x_ending.append(lj+1)
|
||||
##y_lines_by_order.append(int(splitter_y_new[i]))
|
||||
##x_start_by_order.append(0)
|
||||
|
||||
|
||||
|
||||
y_type_2=np.array(y_type_2)
|
||||
x_starting=np.array(x_starting)
|
||||
x_ending=np.array(x_ending)
|
||||
|
||||
ind_args=np.array(range(len(y_type_2)))
|
||||
#ind_args=np.array(ind_args)
|
||||
#print(ind_args,'ind_args')
|
||||
for column in range(len(peaks_neg_tot)-1,0,-1):
|
||||
#print(column,'column')
|
||||
ind_args_in_col=ind_args[x_ending==column]
|
||||
ind_args_in_col=np.array(ind_args_in_col)
|
||||
#print(len(y_type_2))
|
||||
y_column=y_type_2[ind_args_in_col]
|
||||
x_start_column=x_starting[ind_args_in_col]
|
||||
x_end_column=x_ending[ind_args_in_col]
|
||||
|
||||
ind_args_col_sorted=np.argsort(y_column)
|
||||
y_col_sort=y_column[ind_args_col_sorted]
|
||||
x_start_column_sort=x_start_column[ind_args_col_sorted]
|
||||
x_end_column_sort=x_end_column[ind_args_col_sorted]
|
||||
#print('babali4')
|
||||
for ii in range(len(y_col_sort)):
|
||||
#print('babali5')
|
||||
y_lines_by_order.append(y_col_sort[ii])
|
||||
x_start_by_order.append(x_start_column_sort[ii])
|
||||
x_end_by_order.append(x_end_column_sort[ii]-1)
|
||||
|
||||
for il in range(len(y_lines_by_order)):
|
||||
|
||||
|
||||
y_copy=list( np.copy(y_lines_by_order) )
|
||||
x_start_copy=list( np.copy(x_start_by_order) )
|
||||
x_end_copy=list ( np.copy(x_end_by_order) )
|
||||
|
||||
#print(y_copy,'y_copy')
|
||||
y_itself=y_copy.pop(il)
|
||||
x_start_itself=x_start_copy.pop(il)
|
||||
x_end_itself=x_end_copy.pop(il)
|
||||
|
||||
#print(y_copy,'y_copy2')
|
||||
|
||||
for column in range(x_end_itself+1-1,x_start_itself-1,-1):
|
||||
#print(column,'cols')
|
||||
y_in_cols=[]
|
||||
for yic in range(len(y_copy)):
|
||||
#print('burda')
|
||||
if y_copy[yic]>y_itself and column>=x_start_copy[yic] and column<=x_end_copy[yic]:
|
||||
y_in_cols.append(y_copy[yic])
|
||||
#print('burda2')
|
||||
#print(y_in_cols,'y_in_cols')
|
||||
if len(y_in_cols)>0:
|
||||
y_down=np.min(y_in_cols)
|
||||
else:
|
||||
y_down=[int(splitter_y_new[i+1])][0]
|
||||
#print(y_itself,'y_itself')
|
||||
boxes.append([peaks_neg_tot[column],peaks_neg_tot[column+1],y_itself,y_down])
|
||||
|
||||
|
||||
|
||||
#else:
|
||||
#boxes.append([ 0, regions_without_separators[:,:].shape[1] ,splitter_y_new[i],splitter_y_new[i+1]])
|
||||
return boxes, peaks_neg_tot_tables
|
||||
|
||||
if right2left_readingorder:
|
||||
peaks_neg_tot_tables_new = []
|
||||
if len(peaks_neg_tot_tables)>=1:
|
||||
for peaks_tab_ind in peaks_neg_tot_tables:
|
||||
peaks_neg_tot_tables_ind = regions_without_separators.shape[1] - np.array(peaks_tab_ind)
|
||||
peaks_neg_tot_tables_ind = list(peaks_neg_tot_tables_ind[::-1])
|
||||
peaks_neg_tot_tables_new.append(peaks_neg_tot_tables_ind)
|
||||
|
||||
|
||||
for i in range(len(boxes)):
|
||||
x_start_new = regions_without_separators.shape[1] - boxes[i][1]
|
||||
x_end_new = regions_without_separators.shape[1] - boxes[i][0]
|
||||
boxes[i][0] = x_start_new
|
||||
boxes[i][1] = x_end_new
|
||||
return boxes, peaks_neg_tot_tables_new
|
||||
else:
|
||||
return boxes, peaks_neg_tot_tables
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue