From 375e9771e21dbc6cd32222d903b642d8a8f73531 Mon Sep 17 00:00:00 2001 From: Konstantin Baierer Date: Mon, 1 Mar 2021 17:44:51 +0100 Subject: [PATCH] typo: s,spliter,splitter,g --- qurator/eynollah/eynollah.py | 22 +++--- qurator/eynollah/utils/__init__.py | 122 ++++++++++++++--------------- 2 files changed, 72 insertions(+), 72 deletions(-) diff --git a/qurator/eynollah/eynollah.py b/qurator/eynollah/eynollah.py index d001753..ca23a16 100644 --- a/qurator/eynollah/eynollah.py +++ b/qurator/eynollah/eynollah.py @@ -1486,10 +1486,10 @@ class Eynollah: regions_without_seperators_d = None pixel_lines = 3 if np.abs(slope_deskew) < SLOPE_THRESHOLD: - _, _, matrix_of_lines_ch, spliter_y_new, _ = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines) + _, _, matrix_of_lines_ch, splitter_y_new, _ = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines) if np.abs(slope_deskew) >= SLOPE_THRESHOLD: - _, _, matrix_of_lines_ch_d, spliter_y_new_d, _ = find_number_of_columns_in_document(np.repeat(text_regions_p_1_n[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines) + _, _, matrix_of_lines_ch_d, splitter_y_new_d, _ = find_number_of_columns_in_document(np.repeat(text_regions_p_1_n[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines) K.clear_session() self.logger.info("num_col_classifier: %s", num_col_classifier) @@ -1503,11 +1503,11 @@ class Eynollah: regions_without_seperators_d = cv2.erode(regions_without_seperators_d[:, :], KERNEL, iterations=6) t1 = time.time() if np.abs(slope_deskew) < SLOPE_THRESHOLD: - boxes = return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_without_seperators, matrix_of_lines_ch, num_col_classifier) + boxes = return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_seperators, matrix_of_lines_ch, num_col_classifier) boxes_d = None self.logger.debug("len(boxes): %s", len(boxes)) else: - boxes_d = return_boxes_of_images_by_order_of_reading_new(spliter_y_new_d, regions_without_seperators_d, matrix_of_lines_ch_d, num_col_classifier) + boxes_d = return_boxes_of_images_by_order_of_reading_new(splitter_y_new_d, regions_without_seperators_d, matrix_of_lines_ch_d, num_col_classifier) boxes = None self.logger.debug("len(boxes): %s", len(boxes_d)) @@ -1760,17 +1760,17 @@ class Eynollah: if not self.headers_off: if np.abs(slope_deskew) < SLOPE_THRESHOLD: - num_col, _, matrix_of_lines_ch, spliter_y_new, _ = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines, contours_only_text_parent_h) + num_col, _, matrix_of_lines_ch, splitter_y_new, _ = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines, contours_only_text_parent_h) else: - _, _, matrix_of_lines_ch_d, spliter_y_new_d, _ = find_number_of_columns_in_document(np.repeat(text_regions_p_1_n[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines, contours_only_text_parent_h_d_ordered) + _, _, matrix_of_lines_ch_d, splitter_y_new_d, _ = find_number_of_columns_in_document(np.repeat(text_regions_p_1_n[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines, contours_only_text_parent_h_d_ordered) elif self.headers_off: if np.abs(slope_deskew) < SLOPE_THRESHOLD: - num_col, _, matrix_of_lines_ch, spliter_y_new, _ = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines) + num_col, _, matrix_of_lines_ch, splitter_y_new, _ = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines) else: - _, _, matrix_of_lines_ch_d, spliter_y_new_d, _ = find_number_of_columns_in_document(np.repeat(text_regions_p_1_n[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines) + _, _, matrix_of_lines_ch_d, splitter_y_new_d, _ = find_number_of_columns_in_document(np.repeat(text_regions_p_1_n[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines) # print(peaks_neg_fin,peaks_neg_fin_d,'num_col2') - # print(spliter_y_new,spliter_y_new_d,'num_col_classifier') + # print(splitter_y_new,splitter_y_new_d,'num_col_classifier') # print(matrix_of_lines_ch.shape,matrix_of_lines_ch_d.shape,'matrix_of_lines_ch') if num_col_classifier >= 3: @@ -1790,9 +1790,9 @@ class Eynollah: regions_without_seperators_d[(random_pixels_for_image[:, :] == 1) & (text_regions_p_1_n[:, :] == 5)] = 1 if np.abs(slope_deskew) < SLOPE_THRESHOLD: - boxes = return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_without_seperators, matrix_of_lines_ch, num_col_classifier) + boxes = return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_seperators, matrix_of_lines_ch, num_col_classifier) else: - boxes_d = return_boxes_of_images_by_order_of_reading_new(spliter_y_new_d, regions_without_seperators_d, matrix_of_lines_ch_d, num_col_classifier) + boxes_d = return_boxes_of_images_by_order_of_reading_new(splitter_y_new_d, regions_without_seperators_d, matrix_of_lines_ch_d, num_col_classifier) if self.plotter: self.plotter.write_images_into_directory(polygons_of_images, image_page) diff --git a/qurator/eynollah/utils/__init__.py b/qurator/eynollah/utils/__init__.py index a43abb7..078eb31 100644 --- a/qurator/eynollah/utils/__init__.py +++ b/qurator/eynollah/utils/__init__.py @@ -1549,30 +1549,30 @@ def find_number_of_columns_in_document(region_pre_p, num_col_classifier, pixel_l matrix_of_lines_ch=np.copy(matrix_l_n) - cy_main_spliters=cy_main_hor[ (x_min_main_hor<=.16*region_pre_p.shape[1]) & (x_max_main_hor>=.84*region_pre_p.shape[1] )] + cy_main_splitters=cy_main_hor[ (x_min_main_hor<=.16*region_pre_p.shape[1]) & (x_max_main_hor>=.84*region_pre_p.shape[1] )] - cy_main_spliters=np.array( list(cy_main_spliters)+list(special_seperators)) + cy_main_splitters=np.array( list(cy_main_splitters)+list(special_seperators)) if contours_h is not None: try: - cy_main_spliters_head=cy_main_head[ (x_min_main_head<=.16*region_pre_p.shape[1]) & (x_max_main_head>=.84*region_pre_p.shape[1] )] - cy_main_spliters=np.array( list(cy_main_spliters)+list(cy_main_spliters_head)) + cy_main_splitters_head=cy_main_head[ (x_min_main_head<=.16*region_pre_p.shape[1]) & (x_max_main_head>=.84*region_pre_p.shape[1] )] + cy_main_splitters=np.array( list(cy_main_splitters)+list(cy_main_splitters_head)) except: pass - args_cy_spliter=np.argsort(cy_main_spliters) + args_cy_splitter=np.argsort(cy_main_splitters) - cy_main_spliters_sort=cy_main_spliters[args_cy_spliter] + cy_main_splitters_sort=cy_main_splitters[args_cy_splitter] - spliter_y_new=[] - spliter_y_new.append(0) - for i in range(len(cy_main_spliters_sort)): - spliter_y_new.append( cy_main_spliters_sort[i] ) + splitter_y_new=[] + splitter_y_new.append(0) + for i in range(len(cy_main_splitters_sort)): + splitter_y_new.append( cy_main_splitters_sort[i] ) - spliter_y_new.append(region_pre_p.shape[0]) + splitter_y_new.append(region_pre_p.shape[0]) - spliter_y_new_diff=np.diff(spliter_y_new)/float(region_pre_p.shape[0])*100 + splitter_y_new_diff=np.diff(splitter_y_new)/float(region_pre_p.shape[0])*100 - args_big_parts=np.array(range(len(spliter_y_new_diff))) [ spliter_y_new_diff>22 ] + args_big_parts=np.array(range(len(splitter_y_new_diff))) [ splitter_y_new_diff>22 ] @@ -1587,8 +1587,8 @@ def find_number_of_columns_in_document(region_pre_p, num_col_classifier, pixel_l for itiles in args_big_parts: - regions_without_seperators_tile=regions_without_seperators[int(spliter_y_new[iteils]):int(spliter_y_new[iteils+1]),:,0] - #image_page_background_zero_tile=image_page_background_zero[int(spliter_y_new[iteils]):int(spliter_y_new[iteils+1]),:] + regions_without_seperators_tile=regions_without_seperators[int(splitter_y_new[iteils]):int(splitter_y_new[iteils+1]),:,0] + #image_page_background_zero_tile=image_page_background_zero[int(splitter_y_new[iteils]):int(splitter_y_new[iteils+1]),:] #print(regions_without_seperators_tile.shape) ##plt.imshow(regions_without_seperators_tile) @@ -1614,25 +1614,25 @@ def find_number_of_columns_in_document(region_pre_p, num_col_classifier, pixel_l #print(peaks_neg_fin_fin,'peaks_neg_fin_fintaza') - return num_col_fin, peaks_neg_fin_fin,matrix_of_lines_ch,spliter_y_new,seperators_closeup_n + return num_col_fin, peaks_neg_fin_fin,matrix_of_lines_ch,splitter_y_new,seperators_closeup_n -def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_without_seperators, matrix_of_lines_ch, num_col_classifier): +def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_seperators, matrix_of_lines_ch, num_col_classifier): boxes=[] - for i in range(len(spliter_y_new)-1): - #print(spliter_y_new[i],spliter_y_new[i+1]) - matrix_new=matrix_of_lines_ch[:,:][ (matrix_of_lines_ch[:,6]> spliter_y_new[i] ) & (matrix_of_lines_ch[:,7]< spliter_y_new[i+1] ) ] + for i in range(len(splitter_y_new)-1): + #print(splitter_y_new[i],splitter_y_new[i+1]) + 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] ) ] #print(len( matrix_new[:,9][matrix_new[:,9]==1] )) #print(matrix_new[:,8][matrix_new[:,9]==1],'gaddaaa') # check to see is there any vertical seperator to find holes. - 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(spliter_y_new[i+1]-spliter_y_new[i] )): + 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] )): try: - num_col, peaks_neg_fin=find_num_col(regions_without_seperators[int(spliter_y_new[i]):int(spliter_y_new[i+1]),:],multiplier=7.) + num_col, peaks_neg_fin=find_num_col(regions_without_seperators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),:],multiplier=7.) except: peaks_neg_fin=[] @@ -1644,7 +1644,7 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou #print('burda') if len(peaks_neg_fin)==0: - num_col, peaks_neg_fin=find_num_col(regions_without_seperators[int(spliter_y_new[i]):int(spliter_y_new[i+1]),:],multiplier=3.) + num_col, peaks_neg_fin=find_num_col(regions_without_seperators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),:],multiplier=3.) peaks_neg_fin_early=[] peaks_neg_fin_early.append(0) #print(peaks_neg_fin,'peaks_neg_fin') @@ -1657,15 +1657,15 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou for i_n in range(len(peaks_neg_fin_early)-1): #print(i_n,'i_n') - #plt.plot(regions_without_seperators[int(spliter_y_new[i]):int(spliter_y_new[i+1]),peaks_neg_fin_early[i_n]:peaks_neg_fin_early[i_n+1]].sum(axis=0) ) + #plt.plot(regions_without_seperators[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) ) #plt.show() try: - num_col, peaks_neg_fin1=find_num_col(regions_without_seperators[int(spliter_y_new[i]):int(spliter_y_new[i+1]),peaks_neg_fin_early[i_n]:peaks_neg_fin_early[i_n+1]],multiplier=7.) + num_col, peaks_neg_fin1=find_num_col(regions_without_seperators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),peaks_neg_fin_early[i_n]:peaks_neg_fin_early[i_n+1]],multiplier=7.) except: peaks_neg_fin1=[] try: - num_col, peaks_neg_fin2=find_num_col(regions_without_seperators[int(spliter_y_new[i]):int(spliter_y_new[i+1]),peaks_neg_fin_early[i_n]:peaks_neg_fin_early[i_n+1]],multiplier=5.) + num_col, peaks_neg_fin2=find_num_col(regions_without_seperators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),peaks_neg_fin_early[i_n]:peaks_neg_fin_early[i_n+1]],multiplier=5.) except: peaks_neg_fin2=[] @@ -1698,7 +1698,7 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou #print(peaks_neg_fin,'peaks_neg_fin') except: pass - #num_col, peaks_neg_fin=find_num_col(regions_without_seperators[int(spliter_y_new[i]):int(spliter_y_new[i+1]),:],multiplier=7.0) + #num_col, peaks_neg_fin=find_num_col(regions_without_seperators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),:],multiplier=7.0) x_min_hor_some=matrix_new[:,2][ (matrix_new[:,9]==0) ] x_max_hor_some=matrix_new[:,3][ (matrix_new[:,9]==0) ] cy_hor_some=matrix_new[:,5][ (matrix_new[:,9]==0) ] @@ -1719,7 +1719,7 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou try: - y_grenze=int(spliter_y_new[i])+300 + y_grenze=int(splitter_y_new[i])+300 @@ -1728,13 +1728,13 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou args_early_ys=np.array(range(len(y_type_2))) #print(args_early_ys,'args_early_ys') - #print(int(spliter_y_new[i]),int(spliter_y_new[i+1])) + #print(int(splitter_y_new[i]),int(splitter_y_new[i+1])) - y_type_2_up=np.array(y_type_2)[( np.array(y_type_2)>int(spliter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] - x_starting_up=np.array(x_starting)[( np.array(y_type_2)>int(spliter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] - x_ending_up=np.array(x_ending)[( np.array(y_type_2)>int(spliter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] - y_diff_type_2_up=np.array(y_diff_type_2)[( np.array(y_type_2)>int(spliter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] - args_up=args_early_ys[( np.array(y_type_2)>int(spliter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] + y_type_2_up=np.array(y_type_2)[( np.array(y_type_2)>int(splitter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] + x_starting_up=np.array(x_starting)[( np.array(y_type_2)>int(splitter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] + x_ending_up=np.array(x_ending)[( np.array(y_type_2)>int(splitter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] + y_diff_type_2_up=np.array(y_diff_type_2)[( np.array(y_type_2)>int(splitter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] + args_up=args_early_ys[( np.array(y_type_2)>int(splitter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] @@ -1747,25 +1747,25 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou if len(y_diff_main_separator_up)>0: args_to_be_kept=np.array( list( set(args_early_ys)-set(args_main_to_deleted) ) ) #print(args_to_be_kept,'args_to_be_kept') - boxes.append([0,peaks_neg_tot[len(peaks_neg_tot)-1],int(spliter_y_new[i]),int( np.max(y_diff_main_separator_up))]) - spliter_y_new[i]=[ np.max(y_diff_main_separator_up) ][0] + boxes.append([0,peaks_neg_tot[len(peaks_neg_tot)-1],int(splitter_y_new[i]),int( np.max(y_diff_main_separator_up))]) + splitter_y_new[i]=[ np.max(y_diff_main_separator_up) ][0] - #print(spliter_y_new[i],'spliter_y_new[i]') + #print(splitter_y_new[i],'splitter_y_new[i]') y_type_2=np.array(y_type_2)[args_to_be_kept] x_starting=np.array(x_starting)[args_to_be_kept] x_ending=np.array(x_ending)[args_to_be_kept] y_diff_type_2=np.array(y_diff_type_2)[args_to_be_kept] #print('galdiha') - y_grenze=int(spliter_y_new[i])+200 + y_grenze=int(splitter_y_new[i])+200 args_early_ys2=np.array(range(len(y_type_2))) - y_type_2_up=np.array(y_type_2)[( np.array(y_type_2)>int(spliter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] - x_starting_up=np.array(x_starting)[( np.array(y_type_2)>int(spliter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] - x_ending_up=np.array(x_ending)[( np.array(y_type_2)>int(spliter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] - y_diff_type_2_up=np.array(y_diff_type_2)[( np.array(y_type_2)>int(spliter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] - args_up2=args_early_ys2[( np.array(y_type_2)>int(spliter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] + y_type_2_up=np.array(y_type_2)[( np.array(y_type_2)>int(splitter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] + x_starting_up=np.array(x_starting)[( np.array(y_type_2)>int(splitter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] + x_ending_up=np.array(x_ending)[( np.array(y_type_2)>int(splitter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] + y_diff_type_2_up=np.array(y_diff_type_2)[( np.array(y_type_2)>int(splitter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] + args_up2=args_early_ys2[( np.array(y_type_2)>int(splitter_y_new[i]) ) & (np.array(y_type_2)<=y_grenze)] #print(y_type_2_up,x_starting_up,x_ending_up,'didid') @@ -1840,7 +1840,7 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou y_type_2=np.array(y_type_2) y_diff_type_2_up=np.array(y_diff_type_2_up) - #int(spliter_y_new[i]) + #int(splitter_y_new[i]) y_lines_by_order=[] x_start_by_order=[] @@ -1850,7 +1850,7 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou if reading_order_type==1: - y_lines_by_order.append(int(spliter_y_new[i])) + y_lines_by_order.append(int(splitter_y_new[i])) x_start_by_order.append(0) x_end_by_order.append(len(peaks_neg_tot)-2) else: @@ -1872,13 +1872,13 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou x_ending=list(x_ending) for lj in columns_not_covered: - y_type_2.append(int(spliter_y_new[i])) + y_type_2.append(int(splitter_y_new[i])) x_starting.append(lj) x_ending.append(lj+1) - ##y_lines_by_order.append(int(spliter_y_new[i])) + ##y_lines_by_order.append(int(splitter_y_new[i])) ##x_start_by_order.append(0) for lk in range(len(x_start_without_mother)): - y_type_2.append(int(spliter_y_new[i])) + y_type_2.append(int(splitter_y_new[i])) x_starting.append(x_start_without_mother[lk]) x_ending.append(x_end_without_mother[lk]) @@ -1935,13 +1935,13 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou x_ending=list(x_ending) for lj in columns_not_covered: - y_type_2.append(int(spliter_y_new[i])) + y_type_2.append(int(splitter_y_new[i])) x_starting.append(lj) x_ending.append(lj+1) - ##y_lines_by_order.append(int(spliter_y_new[i])) + ##y_lines_by_order.append(int(splitter_y_new[i])) ##x_start_by_order.append(0) for lk in range(len(x_start_without_mother)): - y_type_2.append(int(spliter_y_new[i])) + y_type_2.append(int(splitter_y_new[i])) x_starting.append(x_start_without_mother[lk]) x_ending.append(x_end_without_mother[lk]) @@ -1986,7 +1986,7 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou for i_c in range(len(y_column_nc)): if i_c==(len(y_column_nc)-1): - ind_all_lines_betweeen_nm_wc=ind_args[(y_type_2>y_column_nc[i_c]) & (y_type_2=i_s_nc) & (x_ending<=x_end_biggest_column)] + ind_all_lines_betweeen_nm_wc=ind_args[(y_type_2>y_column_nc[i_c]) & (y_type_2=i_s_nc) & (x_ending<=x_end_biggest_column)] else: ind_all_lines_betweeen_nm_wc=ind_args[(y_type_2>y_column_nc[i_c]) & (y_type_2=i_s_nc) & (x_ending<=x_end_biggest_column)] @@ -2141,11 +2141,11 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou if len(y_in_cols)>0: y_down=np.min(y_in_cols) else: - y_down=[int(spliter_y_new[i+1])][0] + 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]) except: - boxes.append([0,peaks_neg_tot[len(peaks_neg_tot)-1],int(spliter_y_new[i]),int(spliter_y_new[i+1])]) + boxes.append([0,peaks_neg_tot[len(peaks_neg_tot)-1],int(splitter_y_new[i]),int(splitter_y_new[i+1])]) @@ -2170,13 +2170,13 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou x_ending=list(x_ending) for lj in columns_not_covered: - y_type_2.append(int(spliter_y_new[i])) + y_type_2.append(int(splitter_y_new[i])) x_starting.append(lj) x_ending.append(lj+1) - ##y_lines_by_order.append(int(spliter_y_new[i])) + ##y_lines_by_order.append(int(splitter_y_new[i])) ##x_start_by_order.append(0) - y_type_2.append(int(spliter_y_new[i])) + y_type_2.append(int(splitter_y_new[i])) x_starting.append(x_starting[0]) x_ending.append(x_ending[0]) @@ -2194,10 +2194,10 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou x_ending=list(x_ending) for lj in columns_not_covered: - y_type_2.append(int(spliter_y_new[i])) + y_type_2.append(int(splitter_y_new[i])) x_starting.append(lj) x_ending.append(lj+1) - ##y_lines_by_order.append(int(spliter_y_new[i])) + ##y_lines_by_order.append(int(splitter_y_new[i])) ##x_start_by_order.append(0) @@ -2256,13 +2256,13 @@ def return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_withou if len(y_in_cols)>0: y_down=np.min(y_in_cols) else: - y_down=[int(spliter_y_new[i+1])][0] + 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_seperators[:,:].shape[1] ,spliter_y_new[i],spliter_y_new[i+1]]) + #boxes.append([ 0, regions_without_seperators[:,:].shape[1] ,splitter_y_new[i],splitter_y_new[i+1]]) return boxes