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return_boxes_of_images_by_order_of_reading_new: simplify, avoid changing dtype during np.append

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Robert Sachunsky 2025-08-19 20:09:09 +02:00
parent 09ece86f0d
commit b48c41e68f
2 changed files with 97 additions and 119 deletions
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2
src/eynollah/eynollah.py
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@ -3678,7 +3678,7 @@ class Eynollah:
for region in all_found_textline_polygons] for region in all_found_textline_polygons]
def dilate_textregions_contours(self, all_found_textline_polygons): def dilate_textregions_contours(self, all_found_textline_polygons):
return [np.array(make_valid(Polygon(poly[:, 0])).buffer(5).exterior.coords, return [np.array(make_valid(Polygon(poly[:, 0]).buffer(5)).exterior.coords,
dtype=int)[:, np.newaxis] dtype=int)[:, np.newaxis]
for poly in all_found_textline_polygons] for poly in all_found_textline_polygons]

214
src/eynollah/utils/__init__.py
View file

@ -1632,6 +1632,7 @@ def return_boxes_of_images_by_order_of_reading_new(
regions_without_separators = cv2.flip(regions_without_separators,1) regions_without_separators = cv2.flip(regions_without_separators,1)
boxes=[] boxes=[]
peaks_neg_tot_tables = [] peaks_neg_tot_tables = []
splitter_y_new = np.array(splitter_y_new, dtype=int)
for i in range(len(splitter_y_new)-1): for i in range(len(splitter_y_new)-1):
#print(splitter_y_new[i],splitter_y_new[i+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_new = matrix_of_lines_ch[:,:][(matrix_of_lines_ch[:,6]> splitter_y_new[i] ) &
@ -1644,14 +1645,9 @@ def return_boxes_of_images_by_order_of_reading_new(
# 0.1 * (np.abs(splitter_y_new[i+1]-splitter_y_new[i]))): # 0.1 * (np.abs(splitter_y_new[i+1]-splitter_y_new[i]))):
if True: if True:
try: try:
if erosion_hurts: num_col, peaks_neg_fin = find_num_col(
num_col, peaks_neg_fin = find_num_col( regions_without_separators[splitter_y_new[i]:splitter_y_new[i+1], :],
regions_without_separators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),:], num_col_classifier, tables, multiplier=6. if erosion_hurts else 7.)
num_col_classifier, tables, multiplier=6.)
else:
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.)
except: except:
peaks_neg_fin=[] peaks_neg_fin=[]
num_col = 0 num_col = 0
@ -1661,7 +1657,7 @@ def return_boxes_of_images_by_order_of_reading_new(
#print('burda') #print('burda')
if len(peaks_neg_fin)==0: if len(peaks_neg_fin)==0:
num_col, peaks_neg_fin = find_num_col( num_col, peaks_neg_fin = find_num_col(
regions_without_separators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),:], regions_without_separators[splitter_y_new[i]:splitter_y_new[i+1], :],
num_col_classifier, tables, multiplier=3.) num_col_classifier, tables, multiplier=3.)
peaks_neg_fin_early=[] peaks_neg_fin_early=[]
peaks_neg_fin_early.append(0) peaks_neg_fin_early.append(0)
@ -1674,21 +1670,21 @@ def return_boxes_of_images_by_order_of_reading_new(
peaks_neg_fin_rev=[] peaks_neg_fin_rev=[]
for i_n in range(len(peaks_neg_fin_early)-1): for i_n in range(len(peaks_neg_fin_early)-1):
#print(i_n,'i_n') #print(i_n,'i_n')
#plt.plot(regions_without_separators[int(splitter_y_new[i]): #plt.plot(regions_without_separators[splitter_y_new[i]:
# int(splitter_y_new[i+1]), # splitter_y_new[i+1],
# peaks_neg_fin_early[i_n]: # peaks_neg_fin_early[i_n]:
# peaks_neg_fin_early[i_n+1]].sum(axis=0) ) # peaks_neg_fin_early[i_n+1]].sum(axis=0) )
#plt.show() #plt.show()
try: try:
num_col, peaks_neg_fin1 = find_num_col( num_col, peaks_neg_fin1 = find_num_col(
regions_without_separators[int(splitter_y_new[i]):int(splitter_y_new[i+1]), regions_without_separators[splitter_y_new[i]:splitter_y_new[i+1],
peaks_neg_fin_early[i_n]:peaks_neg_fin_early[i_n+1]], peaks_neg_fin_early[i_n]:peaks_neg_fin_early[i_n+1]],
num_col_classifier,tables, multiplier=7.) num_col_classifier,tables, multiplier=7.)
except: except:
peaks_neg_fin1=[] peaks_neg_fin1=[]
try: try:
num_col, peaks_neg_fin2 = find_num_col( num_col, peaks_neg_fin2 = find_num_col(
regions_without_separators[int(splitter_y_new[i]):int(splitter_y_new[i+1]), regions_without_separators[splitter_y_new[i]:splitter_y_new[i+1],
peaks_neg_fin_early[i_n]:peaks_neg_fin_early[i_n+1]], peaks_neg_fin_early[i_n]:peaks_neg_fin_early[i_n+1]],
num_col_classifier,tables, multiplier=5.) num_col_classifier,tables, multiplier=5.)
except: except:
@ -1716,7 +1712,7 @@ def return_boxes_of_images_by_order_of_reading_new(
except: except:
pass pass
#num_col, peaks_neg_fin = find_num_col( #num_col, peaks_neg_fin = find_num_col(
# regions_without_separators[int(splitter_y_new[i]):int(splitter_y_new[i+1]),:], # regions_without_separators[splitter_y_new[i]:splitter_y_new[i+1],:],
# multiplier=7.0) # multiplier=7.0)
x_min_hor_some=matrix_new[:,2][ (matrix_new[:,9]==0) ] x_min_hor_some=matrix_new[:,2][ (matrix_new[:,9]==0) ]
x_max_hor_some=matrix_new[:,3][ (matrix_new[:,9]==0) ] x_max_hor_some=matrix_new[:,3][ (matrix_new[:,9]==0) ]
@ -1738,31 +1734,28 @@ def return_boxes_of_images_by_order_of_reading_new(
y_lines_with_child_without_mother, x_start_with_child_without_mother, x_end_with_child_without_mother, \ 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( 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) x_min_hor_some, x_max_hor_some, cy_hor_some, peaks_neg_tot, cy_hor_diff)
x_starting = np.array(x_starting)
x_ending = np.array(x_ending)
y_type_2 = np.array(y_type_2)
y_diff_type_2 = np.array(y_diff_type_2)
all_columns = set(range(len(peaks_neg_tot) - 1))
if ((reading_order_type==1) or if ((reading_order_type==1) or
(reading_order_type==0 and (reading_order_type==0 and
(len(y_lines_without_mother)>=2 or there_is_sep_with_child==1))): (len(y_lines_without_mother)>=2 or there_is_sep_with_child==1))):
try: try:
y_grenze=int(splitter_y_new[i])+300 y_grenze = splitter_y_new[i] + 300
#check if there is a big separator in this y_mains_sep_ohne_grenzen #check if there is a big separator in this y_mains_sep_ohne_grenzen
args_early_ys=np.arange(len(y_type_2)) args_early_ys=np.arange(len(y_type_2))
#print(args_early_ys,'args_early_ys') #print(args_early_ys,'args_early_ys')
#print(int(splitter_y_new[i]),int(splitter_y_new[i+1])) #print(splitter_y_new[i], splitter_y_new[i+1])
x_starting_up = x_starting[(y_type_2 > int(splitter_y_new[i])) & x_starting_up = x_starting[(y_type_2 > splitter_y_new[i]) &
(y_type_2 <= y_grenze)] (y_type_2 <= y_grenze)]
x_ending_up = x_ending[(y_type_2 > int(splitter_y_new[i])) & x_ending_up = x_ending[(y_type_2 > splitter_y_new[i]) &
(y_type_2 <= y_grenze)] (y_type_2 <= y_grenze)]
y_type_2_up = y_type_2[(y_type_2 > int(splitter_y_new[i])) & y_type_2_up = y_type_2[(y_type_2 > splitter_y_new[i]) &
(y_type_2 <= y_grenze)] (y_type_2 <= y_grenze)]
y_diff_type_2_up = y_diff_type_2[(y_type_2 > int(splitter_y_new[i])) & y_diff_type_2_up = y_diff_type_2[(y_type_2 > splitter_y_new[i]) &
(y_type_2 <= y_grenze)] (y_type_2 <= y_grenze)]
args_up = args_early_ys[(y_type_2 > int(splitter_y_new[i])) & args_up = args_early_ys[(y_type_2 > splitter_y_new[i]) &
(y_type_2 <= y_grenze)] (y_type_2 <= y_grenze)]
if len(y_type_2_up) > 0: if len(y_type_2_up) > 0:
y_main_separator_up = y_type_2_up [(x_starting_up==0) & y_main_separator_up = y_type_2_up [(x_starting_up==0) &
@ -1776,8 +1769,8 @@ def return_boxes_of_images_by_order_of_reading_new(
args_to_be_kept = np.array(list( set(args_early_ys) - set(args_main_to_deleted) )) 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') #print(args_to_be_kept,'args_to_be_kept')
boxes.append([0, peaks_neg_tot[len(peaks_neg_tot)-1], 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], y_diff_main_separator_up.max()])
splitter_y_new[i]=[ np.max(y_diff_main_separator_up) ][0] splitter_y_new[i] = y_diff_main_separator_up.max()
#print(splitter_y_new[i],'splitter_y_new[i]') #print(splitter_y_new[i],'splitter_y_new[i]')
y_type_2 = y_type_2[args_to_be_kept] y_type_2 = y_type_2[args_to_be_kept]
@ -1786,29 +1779,28 @@ def return_boxes_of_images_by_order_of_reading_new(
y_diff_type_2 = y_diff_type_2[args_to_be_kept] y_diff_type_2 = y_diff_type_2[args_to_be_kept]
#print('galdiha') #print('galdiha')
y_grenze=int(splitter_y_new[i])+200 y_grenze = splitter_y_new[i] + 200
args_early_ys2=np.arange(len(y_type_2)) args_early_ys2=np.arange(len(y_type_2))
y_type_2_up=y_type_2[(y_type_2 > int(splitter_y_new[i])) & y_type_2_up=y_type_2[(y_type_2 > splitter_y_new[i]) &
(y_type_2 <= y_grenze)] (y_type_2 <= y_grenze)]
x_starting_up=x_starting[(y_type_2 > int(splitter_y_new[i])) & x_starting_up=x_starting[(y_type_2 > splitter_y_new[i]) &
(y_type_2 <= y_grenze)] (y_type_2 <= y_grenze)]
x_ending_up=x_ending[(y_type_2 > int(splitter_y_new[i])) & x_ending_up=x_ending[(y_type_2 > splitter_y_new[i]) &
(y_type_2 <= y_grenze)] (y_type_2 <= y_grenze)]
y_diff_type_2_up=y_diff_type_2[(y_type_2 > int(splitter_y_new[i])) & y_diff_type_2_up=y_diff_type_2[(y_type_2 > splitter_y_new[i]) &
(y_type_2 <= y_grenze)] (y_type_2 <= y_grenze)]
args_up2=args_early_ys2[(y_type_2 > int(splitter_y_new[i])) & args_up2=args_early_ys2[(y_type_2 > splitter_y_new[i]) &
(y_type_2 <= y_grenze)] (y_type_2 <= y_grenze)]
#print(y_type_2_up,x_starting_up,x_ending_up,'didid') #print(y_type_2_up,x_starting_up,x_ending_up,'didid')
nodes_in = [] nodes_in = set()
for ij in range(len(x_starting_up)): for ij in range(len(x_starting_up)):
nodes_in = nodes_in + list(range(x_starting_up[ij], nodes_in.update(range(x_starting_up[ij],
x_ending_up[ij])) x_ending_up[ij]))
nodes_in = np.unique(nodes_in)
#print(nodes_in,'nodes_in') #print(nodes_in,'nodes_in')
if set(nodes_in)==set(range(len(peaks_neg_tot)-1)): if nodes_in == set(range(len(peaks_neg_tot)-1)):
pass pass
elif set(nodes_in)==set(range(1, len(peaks_neg_tot)-1)): elif nodes_in == set(range(1, len(peaks_neg_tot)-1)):
pass pass
else: else:
#print('burdaydikh') #print('burdaydikh')
@ -1823,17 +1815,16 @@ def return_boxes_of_images_by_order_of_reading_new(
pass pass
#print('burdaydikh2') #print('burdaydikh2')
elif len(y_diff_main_separator_up)==0: elif len(y_diff_main_separator_up)==0:
nodes_in = [] nodes_in = set()
for ij in range(len(x_starting_up)): for ij in range(len(x_starting_up)):
nodes_in = nodes_in + list(range(x_starting_up[ij], nodes_in.update(range(x_starting_up[ij],
x_ending_up[ij])) x_ending_up[ij]))
nodes_in = np.unique(nodes_in)
#print(nodes_in,'nodes_in2') #print(nodes_in,'nodes_in2')
#print(np.array(range(len(peaks_neg_tot)-1)),'np.array(range(len(peaks_neg_tot)-1))') #print(np.array(range(len(peaks_neg_tot)-1)),'np.array(range(len(peaks_neg_tot)-1))')
if set(nodes_in)==set(range(len(peaks_neg_tot)-1)): if nodes_in == set(range(len(peaks_neg_tot)-1)):
pass pass
elif set(nodes_in)==set(range(1,len(peaks_neg_tot)-1)): elif nodes_in == set(range(1,len(peaks_neg_tot)-1)):
pass pass
else: else:
#print('burdaydikh') #print('burdaydikh')
@ -1858,26 +1849,24 @@ def return_boxes_of_images_by_order_of_reading_new(
x_end_by_order=[] x_end_by_order=[]
if (len(x_end_with_child_without_mother)==0 and reading_order_type==0) or reading_order_type==1: if (len(x_end_with_child_without_mother)==0 and reading_order_type==0) or reading_order_type==1:
if reading_order_type==1: if reading_order_type==1:
y_lines_by_order.append(int(splitter_y_new[i])) y_lines_by_order.append(splitter_y_new[i])
x_start_by_order.append(0) x_start_by_order.append(0)
x_end_by_order.append(len(peaks_neg_tot)-2) x_end_by_order.append(len(peaks_neg_tot)-2)
else: else:
#print(x_start_without_mother,x_end_without_mother,peaks_neg_tot,'dodo') #print(x_start_without_mother,x_end_without_mother,peaks_neg_tot,'dodo')
columns_covered_by_mothers = [] columns_covered_by_mothers = set()
for dj in range(len(x_start_without_mother)): for dj in range(len(x_start_without_mother)):
columns_covered_by_mothers = columns_covered_by_mothers + \ columns_covered_by_mothers.update(
list(range(x_start_without_mother[dj], range(x_start_without_mother[dj],
x_end_without_mother[dj])) x_end_without_mother[dj]))
columns_covered_by_mothers = list(set(columns_covered_by_mothers)) columns_not_covered = list(all_columns - columns_covered_by_mothers)
y_type_2 = np.append(y_type_2, np.ones(len(columns_not_covered) + len(x_start_without_mother),
all_columns=np.arange(len(peaks_neg_tot)-1) dtype=int) * splitter_y_new[i])
columns_not_covered=list(set(all_columns) - set(columns_covered_by_mothers)) ##y_lines_by_order = np.append(y_lines_by_order, [splitter_y_new[i]] * len(columns_not_covered))
y_type_2 = np.append(y_type_2, [int(splitter_y_new[i])] * (len(columns_not_covered) + len(x_start_without_mother)))
##y_lines_by_order = np.append(y_lines_by_order, [int(splitter_y_new[i])] * len(columns_not_covered))
##x_start_by_order = np.append(x_start_by_order, [0] * len(columns_not_covered)) ##x_start_by_order = np.append(x_start_by_order, [0] * len(columns_not_covered))
x_starting = np.append(x_starting, columns_not_covered) x_starting = np.append(x_starting, np.array(columns_not_covered, int))
x_starting = np.append(x_starting, x_start_without_mother) x_starting = np.append(x_starting, x_start_without_mother)
x_ending = np.append(x_ending, np.array(columns_not_covered) + 1) x_ending = np.append(x_ending, np.array(columns_not_covered, int) + 1)
x_ending = np.append(x_ending, x_end_without_mother) x_ending = np.append(x_ending, x_end_without_mother)
ind_args=np.arange(len(y_type_2)) ind_args=np.arange(len(y_type_2))
@ -1906,39 +1895,34 @@ def return_boxes_of_images_by_order_of_reading_new(
x_end_by_order.append(x_end_column_sort[ii]-1) x_end_by_order.append(x_end_column_sort[ii]-1)
else: else:
#print(x_start_without_mother,x_end_without_mother,peaks_neg_tot,'dodo') #print(x_start_without_mother,x_end_without_mother,peaks_neg_tot,'dodo')
columns_covered_by_mothers = [] columns_covered_by_mothers = set()
for dj in range(len(x_start_without_mother)): for dj in range(len(x_start_without_mother)):
columns_covered_by_mothers = columns_covered_by_mothers + \ columns_covered_by_mothers.update(
list(range(x_start_without_mother[dj], range(x_start_without_mother[dj],
x_end_without_mother[dj])) x_end_without_mother[dj]))
columns_covered_by_mothers = list(set(columns_covered_by_mothers)) columns_not_covered = list(all_columns - columns_covered_by_mothers)
y_type_2 = np.append(y_type_2, np.ones(len(columns_not_covered) + len(x_start_without_mother),
all_columns=np.arange(len(peaks_neg_tot)-1) dtype=int) * splitter_y_new[i])
columns_not_covered=list(set(all_columns) - set(columns_covered_by_mothers)) ##y_lines_by_order = np.append(y_lines_by_order, [splitter_y_new[i]] * len(columns_not_covered))
y_type_2 = np.append(y_type_2, [int(splitter_y_new[i])] * (len(columns_not_covered) + len(x_start_without_mother)))
##y_lines_by_order = np.append(y_lines_by_order, [int(splitter_y_new[i])] * len(columns_not_covered))
##x_start_by_order = np.append(x_start_by_order, [0] * len(columns_not_covered)) ##x_start_by_order = np.append(x_start_by_order, [0] * len(columns_not_covered))
x_starting = np.append(x_starting, columns_not_covered) x_starting = np.append(x_starting, np.array(columns_not_covered, int))
x_starting = np.append(x_starting, x_start_without_mother) x_starting = np.append(x_starting, x_start_without_mother)
x_ending = np.append(x_ending, np.array(columns_not_covered) + 1) x_ending = np.append(x_ending, np.array(columns_not_covered, int) + 1)
x_ending = np.append(x_ending, x_end_without_mother) x_ending = np.append(x_ending, x_end_without_mother)
columns_covered_by_with_child_no_mothers = [] columns_covered_by_with_child_no_mothers = set()
for dj in range(len(x_end_with_child_without_mother)): for dj in range(len(x_end_with_child_without_mother)):
columns_covered_by_with_child_no_mothers = columns_covered_by_with_child_no_mothers + \ columns_covered_by_with_child_no_mothers.update(
list(range(x_start_with_child_without_mother[dj], range(x_start_with_child_without_mother[dj],
x_end_with_child_without_mother[dj])) x_end_with_child_without_mother[dj]))
columns_covered_by_with_child_no_mothers = list(set(columns_covered_by_with_child_no_mothers)) columns_not_covered_child_no_mother = list(all_columns - columns_covered_by_with_child_no_mothers)
all_columns = np.arange(len(peaks_neg_tot)-1)
columns_not_covered_child_no_mother = list(set(all_columns) - set(columns_covered_by_with_child_no_mothers))
#indexes_to_be_spanned=[] #indexes_to_be_spanned=[]
for i_s in range(len(x_end_with_child_without_mother)): for i_s in range(len(x_end_with_child_without_mother)):
columns_not_covered_child_no_mother.append(x_start_with_child_without_mother[i_s]) columns_not_covered_child_no_mother.append(x_start_with_child_without_mother[i_s])
columns_not_covered_child_no_mother = np.sort(columns_not_covered_child_no_mother) columns_not_covered_child_no_mother = np.sort(columns_not_covered_child_no_mother)
ind_args = np.arange(len(y_type_2)) ind_args = np.arange(len(y_type_2))
x_end_with_child_without_mother = np.array(x_end_with_child_without_mother) x_end_with_child_without_mother = np.array(x_end_with_child_without_mother, int)
x_start_with_child_without_mother = np.array(x_start_with_child_without_mother) x_start_with_child_without_mother = np.array(x_start_with_child_without_mother, int)
for i_s_nc in columns_not_covered_child_no_mother: for i_s_nc in columns_not_covered_child_no_mother:
if i_s_nc in x_start_with_child_without_mother: if i_s_nc in x_start_with_child_without_mother:
x_end_biggest_column = x_end_with_child_without_mother[x_start_with_child_without_mother==i_s_nc][0] x_end_biggest_column = x_end_with_child_without_mother[x_start_with_child_without_mother==i_s_nc][0]
@ -1951,7 +1935,7 @@ def return_boxes_of_images_by_order_of_reading_new(
for i_c in range(len(y_column_nc)): for i_c in range(len(y_column_nc)):
if i_c==(len(y_column_nc)-1): if i_c==(len(y_column_nc)-1):
ind_all_lines_between_nm_wc=ind_args[(y_type_2>y_column_nc[i_c]) & ind_all_lines_between_nm_wc=ind_args[(y_type_2>y_column_nc[i_c]) &
(y_type_2<int(splitter_y_new[i+1])) & (y_type_2<splitter_y_new[i+1]) &
(x_starting>=i_s_nc) & (x_starting>=i_s_nc) &
(x_ending<=x_end_biggest_column)] (x_ending<=x_end_biggest_column)]
else: else:
@ -1967,21 +1951,19 @@ def return_boxes_of_images_by_order_of_reading_new(
if len(x_diff_all_between_nm_wc)>0: if len(x_diff_all_between_nm_wc)>0:
biggest=np.argmax(x_diff_all_between_nm_wc) biggest=np.argmax(x_diff_all_between_nm_wc)
columns_covered_by_mothers = [] columns_covered_by_mothers = set()
for dj in range(len(x_starting_all_between_nm_wc)): for dj in range(len(x_starting_all_between_nm_wc)):
columns_covered_by_mothers = columns_covered_by_mothers + \ columns_covered_by_mothers.update(
list(range(x_starting_all_between_nm_wc[dj], range(x_starting_all_between_nm_wc[dj],
x_ending_all_between_nm_wc[dj])) x_ending_all_between_nm_wc[dj]))
columns_covered_by_mothers = list(set(columns_covered_by_mothers)) child_columns = set(range(i_s_nc, x_end_biggest_column))
columns_not_covered = list(child_columns - columns_covered_by_mothers)
all_columns=np.arange(i_s_nc, x_end_biggest_column)
columns_not_covered = list(set(all_columns) - set(columns_covered_by_mothers))
should_longest_line_be_extended=0 should_longest_line_be_extended=0
if (len(x_diff_all_between_nm_wc) > 0 and if (len(x_diff_all_between_nm_wc) > 0 and
set(list(range(x_starting_all_between_nm_wc[biggest], set(list(range(x_starting_all_between_nm_wc[biggest],
x_ending_all_between_nm_wc[biggest])) + x_ending_all_between_nm_wc[biggest])) +
list(columns_not_covered)) != set(all_columns)): list(columns_not_covered)) != child_columns):
should_longest_line_be_extended=1 should_longest_line_be_extended=1
index_lines_so_close_to_top_separator = \ index_lines_so_close_to_top_separator = \
np.arange(len(y_all_between_nm_wc))[(y_all_between_nm_wc>y_column_nc[i_c]) & np.arange(len(y_all_between_nm_wc))[(y_all_between_nm_wc>y_column_nc[i_c]) &
@ -2008,8 +1990,8 @@ def return_boxes_of_images_by_order_of_reading_new(
pass pass
y_all_between_nm_wc = np.append(y_all_between_nm_wc, [y_column_nc[i_c]] * len(columns_not_covered)) y_all_between_nm_wc = np.append(y_all_between_nm_wc, [y_column_nc[i_c]] * len(columns_not_covered))
x_starting_all_between_nm_wc = np.append(x_starting_all_between_nm_wc, columns_not_covered) x_starting_all_between_nm_wc = np.append(x_starting_all_between_nm_wc, np.array(columns_not_covered, int))
x_ending_all_between_nm_wc = np.append(x_ending_all_between_nm_wc, np.array(columns_not_covered) + 1) x_ending_all_between_nm_wc = np.append(x_ending_all_between_nm_wc, np.array(columns_not_covered, int) + 1)
ind_args_between=np.arange(len(x_ending_all_between_nm_wc)) ind_args_between=np.arange(len(x_ending_all_between_nm_wc))
for column in range(i_s_nc, x_end_biggest_column): for column in range(i_s_nc, x_end_biggest_column):
@ -2078,7 +2060,7 @@ def return_boxes_of_images_by_order_of_reading_new(
if len(y_in_cols)>0: if len(y_in_cols)>0:
y_down=np.min(y_in_cols) y_down=np.min(y_in_cols)
else: else:
y_down=[int(splitter_y_new[i+1])][0] y_down=splitter_y_new[i+1]
#print(y_itself,'y_itself') #print(y_itself,'y_itself')
boxes.append([peaks_neg_tot[column], boxes.append([peaks_neg_tot[column],
peaks_neg_tot[column+1], peaks_neg_tot[column+1],
@ -2086,45 +2068,42 @@ def return_boxes_of_images_by_order_of_reading_new(
y_down]) y_down])
except: except:
boxes.append([0, peaks_neg_tot[len(peaks_neg_tot)-1], boxes.append([0, peaks_neg_tot[len(peaks_neg_tot)-1],
int(splitter_y_new[i]), int(splitter_y_new[i+1])]) splitter_y_new[i], splitter_y_new[i+1]])
else: else:
y_lines_by_order=[] y_lines_by_order=[]
x_start_by_order=[] x_start_by_order=[]
x_end_by_order=[] x_end_by_order=[]
if len(x_starting)>0: if len(x_starting)>0:
all_columns = np.arange(len(peaks_neg_tot)-1) columns_covered_by_lines_covered_more_than_2col = set()
columns_covered_by_lines_covered_more_than_2col = []
for dj in range(len(x_starting)): for dj in range(len(x_starting)):
if set(list(range(x_starting[dj],x_ending[dj]))) == set(all_columns): if set(range(x_starting[dj], x_ending[dj])) != all_columns:
pass columns_covered_by_lines_covered_more_than_2col.update(
else: range(x_starting[dj], x_ending[dj]))
columns_covered_by_lines_covered_more_than_2col = columns_covered_by_lines_covered_more_than_2col + \ columns_not_covered = list(all_columns - columns_covered_by_lines_covered_more_than_2col)
list(range(x_starting[dj],x_ending[dj]))
columns_covered_by_lines_covered_more_than_2col = list(set(columns_covered_by_lines_covered_more_than_2col))
columns_not_covered = list(set(all_columns) - set(columns_covered_by_lines_covered_more_than_2col))
y_type_2 = np.append(y_type_2, [int(splitter_y_new[i])] * (len(columns_not_covered) + 1)) y_type_2 = np.append(y_type_2, np.ones(len(columns_not_covered) + 1,
##y_lines_by_order = np.append(y_lines_by_order, [int(splitter_y_new[i])] * len(columns_not_covered)) dtype=int) * splitter_y_new[i])
##y_lines_by_order = np.append(y_lines_by_order, [splitter_y_new[i]] * len(columns_not_covered))
##x_start_by_order = np.append(x_start_by_order, [0] * len(columns_not_covered)) ##x_start_by_order = np.append(x_start_by_order, [0] * len(columns_not_covered))
x_starting = np.append(x_starting, columns_not_covered) x_starting = np.append(x_starting, np.array(columns_not_covered, x_starting.dtype))
x_ending = np.append(x_ending, np.array(columns_not_covered) + 1) x_ending = np.append(x_ending, np.array(columns_not_covered, x_ending.dtype) + 1)
if len(new_main_sep_y) > 0: if len(new_main_sep_y) > 0:
x_starting = np.append(x_starting, 0) x_starting = np.append(x_starting, 0)
x_ending = np.append(x_ending, len(peaks_neg_tot)-1) x_ending = np.append(x_ending, len(peaks_neg_tot) - 1)
else: else:
x_starting = np.append(x_starting, x_starting[0]) x_starting = np.append(x_starting, x_starting[0])
x_ending = np.append(x_ending, x_ending[0]) x_ending = np.append(x_ending, x_ending[0])
else: else:
all_columns = np.arange(len(peaks_neg_tot)-1) columns_not_covered = list(all_columns)
columns_not_covered = list(set(all_columns)) y_type_2 = np.append(y_type_2, np.ones(len(columns_not_covered),
y_type_2 = np.append(y_type_2, [int(splitter_y_new[i])] * len(columns_not_covered)) dtype=int) * splitter_y_new[i])
##y_lines_by_order = np.append(y_lines_by_order, [int(splitter_y_new[i])] * len(columns_not_covered)) ##y_lines_by_order = np.append(y_lines_by_order, [splitter_y_new[i]] * len(columns_not_covered))
##x_start_by_order = np.append(x_start_by_order, [0] * len(columns_not_covered)) ##x_start_by_order = np.append(x_start_by_order, [0] * len(columns_not_covered))
x_starting = np.append(x_starting, columns_not_covered) x_starting = np.append(x_starting, np.array(columns_not_covered, x_starting.dtype))
x_ending = np.append(x_ending, np.array(columns_not_covered) + 1) x_ending = np.append(x_ending, np.array(columns_not_covered, x_ending.dtype) + 1)
ind_args = np.arange(len(y_type_2))
ind_args=np.array(range(len(y_type_2)))
#ind_args=np.array(ind_args)
for column in range(len(peaks_neg_tot)-1): for column in range(len(peaks_neg_tot)-1):
#print(column,'column') #print(column,'column')
ind_args_in_col=ind_args[x_starting==column] ind_args_in_col=ind_args[x_starting==column]
@ -2155,7 +2134,6 @@ def return_boxes_of_images_by_order_of_reading_new(
x_start_itself=x_start_copy.pop(il) x_start_itself=x_start_copy.pop(il)
x_end_itself=x_end_copy.pop(il) x_end_itself=x_end_copy.pop(il)
#print(y_copy,'y_copy2')
for column in range(x_start_itself, x_end_itself+1): for column in range(x_start_itself, x_end_itself+1):
#print(column,'cols') #print(column,'cols')
y_in_cols=[] y_in_cols=[]
@ -2170,7 +2148,7 @@ def return_boxes_of_images_by_order_of_reading_new(
if len(y_in_cols)>0: if len(y_in_cols)>0:
y_down=np.min(y_in_cols) y_down=np.min(y_in_cols)
else: else:
y_down=[int(splitter_y_new[i+1])][0] y_down=splitter_y_new[i+1]
#print(y_itself,'y_itself') #print(y_itself,'y_itself')
boxes.append([peaks_neg_tot[column], boxes.append([peaks_neg_tot[column],
peaks_neg_tot[column+1], peaks_neg_tot[column+1],