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do_order_of_regions: simplify

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- remove duplicate code via inline def for the try-catch
This commit is contained in:
Robert Sachunsky 2025-10-03 02:06:08 +02:00
parent e674ea08f3
commit 29b4527bde
1 changed files with 22 additions and 105 deletions
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125
src/eynollah/eynollah.py
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@ -2525,113 +2525,23 @@ class Eynollah:
cx_head, cy_head, mx_head, Mx_head, my_head, My_head, mxy_head = find_new_features_of_contours(
contours_only_text_parent_h)
try:
def match_boxes(only_centers: bool):
arg_text_con_main = np.zeros(len(contours_only_text_parent), dtype=int)
for ii in range(len(contours_only_text_parent)):
check_if_textregion_located_in_a_box = False
for jj, box in enumerate(boxes):
if (mx_main[ii] >= box[0] and
Mx_main[ii] < box[1] and
my_main[ii] >= box[2] and
My_main[ii] < box[3]):
arg_text_con_main[ii] = jj
check_if_textregion_located_in_a_box = True
break
if not check_if_textregion_located_in_a_box:
# dists_tr_from_box = [math.sqrt((cx_main[ii] - 0.5 * box[1] - 0.5 * box[0]) ** 2 +
# (cy_main[ii] - 0.5 * box[3] - 0.5 * box[2]) ** 2)
# for box in boxes]
dists_tr_from_box = np.linalg.norm(c_boxes - np.array([[cy_main[ii]], [cx_main[ii]]]), axis=0)
pcontained_in_box = ((boxes[:, 2] <= cy_main[ii]) & (cy_main[ii] < boxes[:, 3]) &
(boxes[:, 0] <= cx_main[ii]) & (cx_main[ii] < boxes[:, 1]))
ind_min = np.argmin(np.ma.masked_array(dists_tr_from_box, ~pcontained_in_box))
arg_text_con_main[ii] = ind_min
args_contours_main = np.arange(len(contours_only_text_parent))
order_by_con_main = np.zeros_like(arg_text_con_main)
arg_text_con_head = np.zeros(len(contours_only_text_parent_h), dtype=int)
for ii in range(len(contours_only_text_parent_h)):
check_if_textregion_located_in_a_box = False
for jj, box in enumerate(boxes):
if (mx_head[ii] >= box[0] and
Mx_head[ii] < box[1] and
my_head[ii] >= box[2] and
My_head[ii] < box[3]):
arg_text_con_head[ii] = jj
check_if_textregion_located_in_a_box = True
break
if not check_if_textregion_located_in_a_box:
# dists_tr_from_box = [math.sqrt((cx_head[ii] - 0.5 * box[1] - 0.5 * box[0]) ** 2 +
# (cy_head[ii] - 0.5 * box[3] - 0.5 * box[2]) ** 2)
# for box in boxes]
dists_tr_from_box = np.linalg.norm(c_boxes - np.array([[cy_head[ii]], [cx_head[ii]]]), axis=0)
pcontained_in_box = ((boxes[:, 2] <= cy_head[ii]) & (cy_head[ii] < boxes[:, 3]) &
(boxes[:, 0] <= cx_head[ii]) & (cx_head[ii] < boxes[:, 1]))
ind_min = np.argmin(np.ma.masked_array(dists_tr_from_box, ~pcontained_in_box))
arg_text_con_head[ii] = ind_min
args_contours_head = np.arange(len(contours_only_text_parent_h))
order_by_con_head = np.zeros_like(arg_text_con_head)
ref_point = 0
order_of_texts_tot = []
id_of_texts_tot = []
for iij, box in enumerate(boxes):
ys = slice(*box[2:4])
xs = slice(*box[0:2])
args_contours_box_main = args_contours_main[arg_text_con_main == iij]
args_contours_box_head = args_contours_head[arg_text_con_head == iij]
con_inter_box = contours_only_text_parent[args_contours_box_main]
con_inter_box_h = contours_only_text_parent_h[args_contours_box_head]
indexes_sorted, kind_of_texts_sorted, index_by_kind_sorted = order_of_regions(
textline_mask_tot[ys, xs], con_inter_box, con_inter_box_h, box[2])
order_of_texts, id_of_texts = order_and_id_of_texts(
con_inter_box, con_inter_box_h,
indexes_sorted, index_by_kind_sorted, kind_of_texts_sorted, ref_point)
indexes_sorted_main = indexes_sorted[kind_of_texts_sorted == 1]
indexes_by_type_main = index_by_kind_sorted[kind_of_texts_sorted == 1]
indexes_sorted_head = indexes_sorted[kind_of_texts_sorted == 2]
indexes_by_type_head = index_by_kind_sorted[kind_of_texts_sorted == 2]
for zahler, _ in enumerate(args_contours_box_main):
arg_order_v = indexes_sorted_main[zahler]
order_by_con_main[args_contours_box_main[indexes_by_type_main[zahler]]] = \
np.flatnonzero(indexes_sorted == arg_order_v) + ref_point
for zahler, _ in enumerate(args_contours_box_head):
arg_order_v = indexes_sorted_head[zahler]
order_by_con_head[args_contours_box_head[indexes_by_type_head[zahler]]] = \
np.flatnonzero(indexes_sorted == arg_order_v) + ref_point
for jji in range(len(id_of_texts)):
order_of_texts_tot.append(order_of_texts[jji] + ref_point)
id_of_texts_tot.append(id_of_texts[jji])
ref_point += len(id_of_texts)
order_of_texts_tot = np.concatenate((order_by_con_main,
order_by_con_head))
order_text_new = np.argsort(order_of_texts_tot)
except Exception as why:
self.logger.error(why)
arg_text_con_main = np.zeros(len(contours_only_text_parent), dtype=int)
for ii in range(len(contours_only_text_parent)):
check_if_textregion_located_in_a_box = False
for jj, box in enumerate(boxes):
if (cx_main[ii] >= box[0] and
if ((cx_main[ii] >= box[0] and
cx_main[ii] < box[1] and
cy_main[ii] >= box[2] and
cy_main[ii] < box[3]):
# this is valid if the center of region identify in which box it is located
cy_main[ii] < box[3]) if only_centers else
(mx_main[ii] >= box[0] and
Mx_main[ii] < box[1] and
my_main[ii] >= box[2] and
My_main[ii] < box[3])):
arg_text_con_main[ii] = jj
check_if_textregion_located_in_a_box = True
break
if not check_if_textregion_located_in_a_box:
# dists_tr_from_box = [math.sqrt((cx_main[ii] - 0.5 * box[1] - 0.5 * box[0]) ** 2 +
# (cy_main[ii] - 0.5 * box[3] - 0.5 * box[2]) ** 2)
# for box in boxes]
dists_tr_from_box = np.linalg.norm(c_boxes - np.array([[cy_main[ii]], [cx_main[ii]]]), axis=0)
pcontained_in_box = ((boxes[:, 2] <= cy_main[ii]) & (cy_main[ii] < boxes[:, 3]) &
(boxes[:, 0] <= cx_main[ii]) & (cx_main[ii] < boxes[:, 1]))
@ -2644,18 +2554,18 @@ class Eynollah:
for ii in range(len(contours_only_text_parent_h)):
check_if_textregion_located_in_a_box = False
for jj, box in enumerate(boxes):
if (cx_head[ii] >= box[0] and
if ((cx_head[ii] >= box[0] and
cx_head[ii] < box[1] and
cy_head[ii] >= box[2] and
cy_head[ii] < box[3]):
# this is valid if the center of region identify in which box it is located
cy_head[ii] < box[3]) if only_centers else
(mx_head[ii] >= box[0] and
Mx_head[ii] < box[1] and
my_head[ii] >= box[2] and
My_head[ii] < box[3])):
arg_text_con_head[ii] = jj
check_if_textregion_located_in_a_box = True
break
if not check_if_textregion_located_in_a_box:
# dists_tr_from_box = [math.sqrt((cx_head[ii] - 0.5 * box[1] - 0.5 * box[0]) ** 2 +
# (cy_head[ii] - 0.5 * box[3] - 0.5 * box[2]) ** 2)
# for box in boxes]
dists_tr_from_box = np.linalg.norm(c_boxes - np.array([[cy_head[ii]], [cx_head[ii]]]), axis=0)
pcontained_in_box = ((boxes[:, 2] <= cy_head[ii]) & (cy_head[ii] < boxes[:, 3]) &
(boxes[:, 0] <= cx_head[ii]) & (cx_head[ii] < boxes[:, 1]))
@ -2705,9 +2615,16 @@ class Eynollah:
order_of_texts_tot = np.concatenate((order_by_con_main,
order_by_con_head))
order_text_new = np.argsort(order_of_texts_tot)
return order_text_new, id_of_texts_tot
try:
results = match_boxes(False)
except Exception as why:
self.logger.error(why)
results = match_boxes(True)
self.logger.debug("exit do_order_of_regions")
return order_text_new, id_of_texts_tot
return results
def check_iou_of_bounding_box_and_contour_for_tables(
self, layout, table_prediction_early, pixel_table, num_col_classifier):