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import torch
import os
import sys
__dir__ = os.path.dirname(__file__)
sys.path.append(__dir__)
sys.path.append(os.path.join(__dir__, ".."))
from extract_textpoint_slow import *
from extract_textpoint_fast import generate_pivot_list_fast, restore_poly
class PGNet_PostProcess(object):
# two different post-process
def __init__(
self,
character_dict_path,
valid_set,
score_thresh,
outs_dict,
shape_list,
point_gather_mode=None, ):
self.Lexicon_Table = get_dict(character_dict_path)
self.valid_set = valid_set
self.score_thresh = score_thresh
self.outs_dict = outs_dict
self.shape_list = shape_list
self.point_gather_mode = point_gather_mode
def pg_postprocess_fast(self):
p_score = self.outs_dict["f_score"]
p_border = self.outs_dict["f_border"]
p_char = self.outs_dict["f_char"]
p_direction = self.outs_dict["f_direction"]
if isinstance(p_score, torch.Tensor):
p_score = p_score[0].numpy()
p_border = p_border[0].numpy()
p_direction = p_direction[0].numpy()
p_char = p_char[0].numpy()
else:
p_score = p_score[0]
p_border = p_border[0]
p_direction = p_direction[0]
p_char = p_char[0]
src_h, src_w, ratio_h, ratio_w = self.shape_list[0]
instance_yxs_list, seq_strs = generate_pivot_list_fast(
p_score,
p_char,
p_direction,
self.Lexicon_Table,
score_thresh=self.score_thresh,
point_gather_mode=self.point_gather_mode, )
poly_list, keep_str_list = restore_poly(
instance_yxs_list,
seq_strs,
p_border,
ratio_w,
ratio_h,
src_w,
src_h,
self.valid_set, )
data = {
"points": poly_list,
"texts": keep_str_list,
}
return data
def pg_postprocess_slow(self):
p_score = self.outs_dict["f_score"]
p_border = self.outs_dict["f_border"]
p_char = self.outs_dict["f_char"]
p_direction = self.outs_dict["f_direction"]
if isinstance(p_score, torch.Tensor):
p_score = p_score[0].numpy()
p_border = p_border[0].numpy()
p_direction = p_direction[0].numpy()
p_char = p_char[0].numpy()
else:
p_score = p_score[0]
p_border = p_border[0]
p_direction = p_direction[0]
p_char = p_char[0]
src_h, src_w, ratio_h, ratio_w = self.shape_list[0]
is_curved = self.valid_set == "totaltext"
char_seq_idx_set, instance_yxs_list = generate_pivot_list_slow(
p_score,
p_char,
p_direction,
score_thresh=self.score_thresh,
is_backbone=True,
is_curved=is_curved, )
seq_strs = []
for char_idx_set in char_seq_idx_set:
pr_str = "".join([self.Lexicon_Table[pos] for pos in char_idx_set])
seq_strs.append(pr_str)
poly_list = []
keep_str_list = []
all_point_list = []
all_point_pair_list = []
for yx_center_line, keep_str in zip(instance_yxs_list, seq_strs):
if len(yx_center_line) == 1:
yx_center_line.append(yx_center_line[-1])
offset_expand = 1.0
if self.valid_set == "totaltext":
offset_expand = 1.2
point_pair_list = []
for batch_id, y, x in yx_center_line:
offset = p_border[:, y, x].reshape(2, 2)
if offset_expand != 1.0:
offset_length = np.linalg.norm(
offset, axis=1, keepdims=True)
expand_length = np.clip(
offset_length * (offset_expand - 1),
a_min=0.5,
a_max=3.0)
offset_detal = offset / offset_length * expand_length
offset = offset + offset_detal
ori_yx = np.array([y, x], dtype=np.float32)
point_pair = ((ori_yx + offset)[:, ::-1] * 4.0 /
np.array([ratio_w, ratio_h]).reshape(-1, 2))
point_pair_list.append(point_pair)
all_point_list.append([
int(round(x * 4.0 / ratio_w)),
int(round(y * 4.0 / ratio_h))
])
all_point_pair_list.append(point_pair.round().astype(np.int32)
.tolist())
detected_poly, pair_length_info = point_pair2poly(point_pair_list)
detected_poly = expand_poly_along_width(
detected_poly, shrink_ratio_of_width=0.2)
detected_poly[:, 0] = np.clip(
detected_poly[:, 0], a_min=0, a_max=src_w)
detected_poly[:, 1] = np.clip(
detected_poly[:, 1], a_min=0, a_max=src_h)
if len(keep_str) < 2:
continue
keep_str_list.append(keep_str)
detected_poly = np.round(detected_poly).astype("int32")
if self.valid_set == "partvgg":
middle_point = len(detected_poly) // 2
detected_poly = detected_poly[
[0, middle_point - 1, middle_point, -1], :]
poly_list.append(detected_poly)
elif self.valid_set == "totaltext":
poly_list.append(detected_poly)
else:
print("--> Not supported format.")
exit(-1)
data = {
"points": poly_list,
"texts": keep_str_list,
}
return data
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