| 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): |
| |
| 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 |
|
|
