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return_hor_spliter_by_index is unused

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This commit is contained in:
Konstantin Baierer 2021-02-24 15:15:37 +01:00
parent 2952a1ca13
commit d7d388671d
3 changed files with 67 additions and 68 deletions
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1
sbb_newspapers_org_image/eynollah.py
View file

@ -75,7 +75,6 @@ from .utils import (
order_and_id_of_texts, order_and_id_of_texts,
order_of_regions, order_of_regions,
implent_law_head_main_not_parallel, implent_law_head_main_not_parallel,
return_hor_spliter_by_index,
find_number_of_columns_in_document, find_number_of_columns_in_document,
return_boxes_of_images_by_order_of_reading_new, return_boxes_of_images_by_order_of_reading_new,
) )

67
sbb_newspapers_org_image/unused.py
View file

@ -3185,3 +3185,70 @@ def otsu_copy(img):
img_r[:, :, 2] = threshold1 img_r[:, :, 2] = threshold1
return img_r return img_r
def return_hor_spliter_by_index(peaks_neg_fin_t, x_min_hor_some, x_max_hor_some):
arg_min_hor_sort = np.argsort(x_min_hor_some)
x_min_hor_some_sort = np.sort(x_min_hor_some)
x_max_hor_some_sort = x_max_hor_some[arg_min_hor_sort]
arg_minmax = np.array(range(len(peaks_neg_fin_t)))
indexer_lines = []
indexes_to_delete = []
indexer_lines_deletions_len = []
indexr_uniq_ind = []
for i in range(len(x_min_hor_some_sort)):
min_h = peaks_neg_fin_t - x_min_hor_some_sort[i]
max_h = peaks_neg_fin_t - x_max_hor_some_sort[i]
min_h[0] = min_h[0] # +20
max_h[len(max_h) - 1] = max_h[len(max_h) - 1] ##-20
min_h_neg = arg_minmax[(min_h < 0) & (np.abs(min_h) < 360)]
max_h_neg = arg_minmax[(max_h >= 0) & (np.abs(max_h) < 360)]
if len(min_h_neg) > 0 and len(max_h_neg) > 0:
deletions = list(range(min_h_neg[0] + 1, max_h_neg[0]))
unique_delets_int = []
# print(deletions,len(deletions),'delii')
if len(deletions) > 0:
# print(deletions,len(deletions),'delii2')
for j in range(len(deletions)):
indexes_to_delete.append(deletions[j])
# print(deletions,indexes_to_delete,'badiii')
unique_delets = np.unique(indexes_to_delete)
# print(min_h_neg[0],unique_delets)
unique_delets_int = unique_delets[unique_delets < min_h_neg[0]]
indexer_lines_deletions_len.append(len(deletions))
indexr_uniq_ind.append([deletions])
else:
indexer_lines_deletions_len.append(0)
indexr_uniq_ind.append(-999)
index_line_true = min_h_neg[0] - len(unique_delets_int)
# print(index_line_true)
if index_line_true > 0 and min_h_neg[0] >= 2:
index_line_true = index_line_true
else:
index_line_true = min_h_neg[0]
indexer_lines.append(index_line_true)
if len(unique_delets_int) > 0:
for dd in range(len(unique_delets_int)):
indexes_to_delete.append(unique_delets_int[dd])
else:
indexer_lines.append(-999)
indexer_lines_deletions_len.append(-999)
indexr_uniq_ind.append(-999)
peaks_true = []
for m in range(len(peaks_neg_fin_t)):
if m in indexes_to_delete:
pass
else:
peaks_true.append(peaks_neg_fin_t[m])
return indexer_lines, peaks_true, arg_min_hor_sort, indexer_lines_deletions_len, indexr_uniq_ind

67
sbb_newspapers_org_image/utils/__init__.py
View file

@ -1295,73 +1295,6 @@ def implent_law_head_main_not_parallel(text_regions):
return text_regions return text_regions
def return_hor_spliter_by_index(peaks_neg_fin_t, x_min_hor_some, x_max_hor_some):
arg_min_hor_sort = np.argsort(x_min_hor_some)
x_min_hor_some_sort = np.sort(x_min_hor_some)
x_max_hor_some_sort = x_max_hor_some[arg_min_hor_sort]
arg_minmax = np.array(range(len(peaks_neg_fin_t)))
indexer_lines = []
indexes_to_delete = []
indexer_lines_deletions_len = []
indexr_uniq_ind = []
for i in range(len(x_min_hor_some_sort)):
min_h = peaks_neg_fin_t - x_min_hor_some_sort[i]
max_h = peaks_neg_fin_t - x_max_hor_some_sort[i]
min_h[0] = min_h[0] # +20
max_h[len(max_h) - 1] = max_h[len(max_h) - 1] ##-20
min_h_neg = arg_minmax[(min_h < 0) & (np.abs(min_h) < 360)]
max_h_neg = arg_minmax[(max_h >= 0) & (np.abs(max_h) < 360)]
if len(min_h_neg) > 0 and len(max_h_neg) > 0:
deletions = list(range(min_h_neg[0] + 1, max_h_neg[0]))
unique_delets_int = []
# print(deletions,len(deletions),'delii')
if len(deletions) > 0:
# print(deletions,len(deletions),'delii2')
for j in range(len(deletions)):
indexes_to_delete.append(deletions[j])
# print(deletions,indexes_to_delete,'badiii')
unique_delets = np.unique(indexes_to_delete)
# print(min_h_neg[0],unique_delets)
unique_delets_int = unique_delets[unique_delets < min_h_neg[0]]
indexer_lines_deletions_len.append(len(deletions))
indexr_uniq_ind.append([deletions])
else:
indexer_lines_deletions_len.append(0)
indexr_uniq_ind.append(-999)
index_line_true = min_h_neg[0] - len(unique_delets_int)
# print(index_line_true)
if index_line_true > 0 and min_h_neg[0] >= 2:
index_line_true = index_line_true
else:
index_line_true = min_h_neg[0]
indexer_lines.append(index_line_true)
if len(unique_delets_int) > 0:
for dd in range(len(unique_delets_int)):
indexes_to_delete.append(unique_delets_int[dd])
else:
indexer_lines.append(-999)
indexer_lines_deletions_len.append(-999)
indexr_uniq_ind.append(-999)
peaks_true = []
for m in range(len(peaks_neg_fin_t)):
if m in indexes_to_delete:
pass
else:
peaks_true.append(peaks_neg_fin_t[m])
return indexer_lines, peaks_true, arg_min_hor_sort, indexer_lines_deletions_len, indexr_uniq_ind
def combine_hor_lines_and_delete_cross_points_and_get_lines_features_back_new(img_p_in_ver, img_in_hor,num_col_classifier): def combine_hor_lines_and_delete_cross_points_and_get_lines_features_back_new(img_p_in_ver, img_in_hor,num_col_classifier):
#img_p_in_ver = cv2.erode(img_p_in_ver, self.kernel, iterations=2) #img_p_in_ver = cv2.erode(img_p_in_ver, self.kernel, iterations=2)
img_p_in_ver=img_p_in_ver.astype(np.uint8) img_p_in_ver=img_p_in_ver.astype(np.uint8)