File size: 16,586 Bytes
fc8c192
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
from __future__ import absolute_import, division, print_function

from itertools import groupby

import cv2
import numpy as np
from skimage.morphology._skeletonize import thin


def get_dict(character_dict_path):
    character_str = ""
    with open(character_dict_path, "rb") as fin:
        lines = fin.readlines()
        for line in lines:
            line = line.decode("utf-8").strip("\n").strip("\r\n")
            character_str += line
        dict_character = list(character_str)
    return dict_character


def softmax(logits):
    """
    logits: N x d
    """
    max_value = np.max(logits, axis=1, keepdims=True)
    exp = np.exp(logits - max_value)
    exp_sum = np.sum(exp, axis=1, keepdims=True)
    dist = exp / exp_sum
    return dist


def get_keep_pos_idxs(labels, remove_blank=None):
    """
    Remove duplicate and get pos idxs of keep items.
    The value of keep_blank should be [None, 95].
    """
    duplicate_len_list = []
    keep_pos_idx_list = []
    keep_char_idx_list = []
    for k, v_ in groupby(labels):
        current_len = len(list(v_))
        if k != remove_blank:
            current_idx = int(sum(duplicate_len_list) + current_len // 2)
            keep_pos_idx_list.append(current_idx)
            keep_char_idx_list.append(k)
        duplicate_len_list.append(current_len)
    return keep_char_idx_list, keep_pos_idx_list


def remove_blank(labels, blank=0):
    new_labels = [x for x in labels if x != blank]
    return new_labels


def insert_blank(labels, blank=0):
    new_labels = [blank]
    for l in labels:
        new_labels += [l, blank]
    return new_labels


def ctc_greedy_decoder(probs_seq, blank=95, keep_blank_in_idxs=True):
    """
    CTC greedy (best path) decoder.
    """
    raw_str = np.argmax(np.array(probs_seq), axis=1)
    remove_blank_in_pos = None if keep_blank_in_idxs else blank
    dedup_str, keep_idx_list = get_keep_pos_idxs(
        raw_str, remove_blank=remove_blank_in_pos
    )
    dst_str = remove_blank(dedup_str, blank=blank)
    return dst_str, keep_idx_list


def instance_ctc_greedy_decoder(gather_info, logits_map, pts_num=4):
    _, _, C = logits_map.shape
    ys, xs = zip(*gather_info)
    logits_seq = logits_map[list(ys), list(xs)]
    probs_seq = logits_seq
    labels = np.argmax(probs_seq, axis=1)
    dst_str = [k for k, v_ in groupby(labels) if k != C - 1]
    detal = len(gather_info) // (pts_num - 1)
    keep_idx_list = [0] + [detal * (i + 1) for i in range(pts_num - 2)] + [-1]
    keep_gather_list = [gather_info[idx] for idx in keep_idx_list]
    return dst_str, keep_gather_list


def ctc_decoder_for_image(gather_info_list, logits_map, Lexicon_Table, pts_num=6):
    """
    CTC decoder using multiple processes.
    """
    decoder_str = []
    decoder_xys = []
    for gather_info in gather_info_list:
        if len(gather_info) < pts_num:
            continue
        dst_str, xys_list = instance_ctc_greedy_decoder(
            gather_info, logits_map, pts_num=pts_num
        )
        dst_str_readable = "".join([Lexicon_Table[idx] for idx in dst_str])
        if len(dst_str_readable) < 2:
            continue
        decoder_str.append(dst_str_readable)
        decoder_xys.append(xys_list)
    return decoder_str, decoder_xys


def sort_with_direction(pos_list, f_direction):
    """
    f_direction: h x w x 2
    pos_list: [[y, x], [y, x], [y, x] ...]
    """

    def sort_part_with_direction(pos_list, point_direction):
        pos_list = np.array(pos_list).reshape(-1, 2)
        point_direction = np.array(point_direction).reshape(-1, 2)
        average_direction = np.mean(point_direction, axis=0, keepdims=True)
        pos_proj_leng = np.sum(pos_list * average_direction, axis=1)
        sorted_list = pos_list[np.argsort(pos_proj_leng)].tolist()
        sorted_direction = point_direction[np.argsort(pos_proj_leng)].tolist()
        return sorted_list, sorted_direction

    pos_list = np.array(pos_list).reshape(-1, 2)
    point_direction = f_direction[pos_list[:, 0], pos_list[:, 1]]  # x, y
    point_direction = point_direction[:, ::-1]  # x, y -> y, x
    sorted_point, sorted_direction = sort_part_with_direction(pos_list, point_direction)

    point_num = len(sorted_point)
    if point_num >= 16:
        middle_num = point_num // 2
        first_part_point = sorted_point[:middle_num]
        first_point_direction = sorted_direction[:middle_num]
        sorted_fist_part_point, sorted_fist_part_direction = sort_part_with_direction(
            first_part_point, first_point_direction
        )

        last_part_point = sorted_point[middle_num:]
        last_point_direction = sorted_direction[middle_num:]
        sorted_last_part_point, sorted_last_part_direction = sort_part_with_direction(
            last_part_point, last_point_direction
        )
        sorted_point = sorted_fist_part_point + sorted_last_part_point
        sorted_direction = sorted_fist_part_direction + sorted_last_part_direction

    return sorted_point, np.array(sorted_direction)


def add_id(pos_list, image_id=0):
    """
    Add id for gather feature, for inference.
    """
    new_list = []
    for item in pos_list:
        new_list.append((image_id, item[0], item[1]))
    return new_list


def sort_and_expand_with_direction(pos_list, f_direction):
    """
    f_direction: h x w x 2
    pos_list: [[y, x], [y, x], [y, x] ...]
    """
    h, w, _ = f_direction.shape
    sorted_list, point_direction = sort_with_direction(pos_list, f_direction)

    point_num = len(sorted_list)
    sub_direction_len = max(point_num // 3, 2)
    left_direction = point_direction[:sub_direction_len, :]
    right_dirction = point_direction[point_num - sub_direction_len :, :]

    left_average_direction = -np.mean(left_direction, axis=0, keepdims=True)
    left_average_len = np.linalg.norm(left_average_direction)
    left_start = np.array(sorted_list[0])
    left_step = left_average_direction / (left_average_len + 1e-6)

    right_average_direction = np.mean(right_dirction, axis=0, keepdims=True)
    right_average_len = np.linalg.norm(right_average_direction)
    right_step = right_average_direction / (right_average_len + 1e-6)
    right_start = np.array(sorted_list[-1])

    append_num = max(int((left_average_len + right_average_len) / 2.0 * 0.15), 1)
    left_list = []
    right_list = []
    for i in range(append_num):
        ly, lx = (
            np.round(left_start + left_step * (i + 1))
            .flatten()
            .astype("int32")
            .tolist()
        )
        if ly < h and lx < w and (ly, lx) not in left_list:
            left_list.append((ly, lx))
        ry, rx = (
            np.round(right_start + right_step * (i + 1))
            .flatten()
            .astype("int32")
            .tolist()
        )
        if ry < h and rx < w and (ry, rx) not in right_list:
            right_list.append((ry, rx))

    all_list = left_list[::-1] + sorted_list + right_list
    return all_list


def sort_and_expand_with_direction_v2(pos_list, f_direction, binary_tcl_map):
    """
    f_direction: h x w x 2
    pos_list: [[y, x], [y, x], [y, x] ...]
    binary_tcl_map: h x w
    """
    h, w, _ = f_direction.shape
    sorted_list, point_direction = sort_with_direction(pos_list, f_direction)

    point_num = len(sorted_list)
    sub_direction_len = max(point_num // 3, 2)
    left_direction = point_direction[:sub_direction_len, :]
    right_dirction = point_direction[point_num - sub_direction_len :, :]

    left_average_direction = -np.mean(left_direction, axis=0, keepdims=True)
    left_average_len = np.linalg.norm(left_average_direction)
    left_start = np.array(sorted_list[0])
    left_step = left_average_direction / (left_average_len + 1e-6)

    right_average_direction = np.mean(right_dirction, axis=0, keepdims=True)
    right_average_len = np.linalg.norm(right_average_direction)
    right_step = right_average_direction / (right_average_len + 1e-6)
    right_start = np.array(sorted_list[-1])

    append_num = max(int((left_average_len + right_average_len) / 2.0 * 0.15), 1)
    max_append_num = 2 * append_num

    left_list = []
    right_list = []
    for i in range(max_append_num):
        ly, lx = (
            np.round(left_start + left_step * (i + 1))
            .flatten()
            .astype("int32")
            .tolist()
        )
        if ly < h and lx < w and (ly, lx) not in left_list:
            if binary_tcl_map[ly, lx] > 0.5:
                left_list.append((ly, lx))
            else:
                break

    for i in range(max_append_num):
        ry, rx = (
            np.round(right_start + right_step * (i + 1))
            .flatten()
            .astype("int32")
            .tolist()
        )
        if ry < h and rx < w and (ry, rx) not in right_list:
            if binary_tcl_map[ry, rx] > 0.5:
                right_list.append((ry, rx))
            else:
                break

    all_list = left_list[::-1] + sorted_list + right_list
    return all_list


def point_pair2poly(point_pair_list):
    """
    Transfer vertical point_pairs into poly point in clockwise.
    """
    point_num = len(point_pair_list) * 2
    point_list = [0] * point_num
    for idx, point_pair in enumerate(point_pair_list):
        point_list[idx] = point_pair[0]
        point_list[point_num - 1 - idx] = point_pair[1]
    return np.array(point_list).reshape(-1, 2)


def shrink_quad_along_width(quad, begin_width_ratio=0.0, end_width_ratio=1.0):
    ratio_pair = np.array([[begin_width_ratio], [end_width_ratio]], dtype=np.float32)
    p0_1 = quad[0] + (quad[1] - quad[0]) * ratio_pair
    p3_2 = quad[3] + (quad[2] - quad[3]) * ratio_pair
    return np.array([p0_1[0], p0_1[1], p3_2[1], p3_2[0]])


def expand_poly_along_width(poly, shrink_ratio_of_width=0.3):
    """
    expand poly along width.
    """
    point_num = poly.shape[0]
    left_quad = np.array([poly[0], poly[1], poly[-2], poly[-1]], dtype=np.float32)
    left_ratio = (
        -shrink_ratio_of_width
        * np.linalg.norm(left_quad[0] - left_quad[3])
        / (np.linalg.norm(left_quad[0] - left_quad[1]) + 1e-6)
    )
    left_quad_expand = shrink_quad_along_width(left_quad, left_ratio, 1.0)
    right_quad = np.array(
        [
            poly[point_num // 2 - 2],
            poly[point_num // 2 - 1],
            poly[point_num // 2],
            poly[point_num // 2 + 1],
        ],
        dtype=np.float32,
    )
    right_ratio = 1.0 + shrink_ratio_of_width * np.linalg.norm(
        right_quad[0] - right_quad[3]
    ) / (np.linalg.norm(right_quad[0] - right_quad[1]) + 1e-6)
    right_quad_expand = shrink_quad_along_width(right_quad, 0.0, right_ratio)
    poly[0] = left_quad_expand[0]
    poly[-1] = left_quad_expand[-1]
    poly[point_num // 2 - 1] = right_quad_expand[1]
    poly[point_num // 2] = right_quad_expand[2]
    return poly


def restore_poly(
    instance_yxs_list, seq_strs, p_border, ratio_w, ratio_h, src_w, src_h, valid_set
):
    poly_list = []
    keep_str_list = []
    for yx_center_line, keep_str in zip(instance_yxs_list, seq_strs):
        if len(keep_str) < 2:
            print("--> too short, {}".format(keep_str))
            continue

        offset_expand = 1.0
        if valid_set == "totaltext":
            offset_expand = 1.2

        point_pair_list = []
        for y, x in yx_center_line:
            offset = p_border[:, y, x].reshape(2, 2) * offset_expand
            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)

        detected_poly = 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)

        keep_str_list.append(keep_str)
        if 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 valid_set == "totaltext":
            poly_list.append(detected_poly)
        else:
            print("--> Not supported format.")
            exit(-1)
    return poly_list, keep_str_list


def generate_pivot_list_fast(
    p_score, p_char_maps, f_direction, Lexicon_Table, score_thresh=0.5
):
    """
    return center point and end point of TCL instance; filter with the char maps;
    """
    p_score = p_score[0]
    f_direction = f_direction.transpose(1, 2, 0)
    p_tcl_map = (p_score > score_thresh) * 1.0
    skeleton_map = thin(p_tcl_map.astype(np.uint8))
    instance_count, instance_label_map = cv2.connectedComponents(
        skeleton_map.astype(np.uint8), connectivity=8
    )

    # get TCL Instance
    all_pos_yxs = []
    if instance_count > 0:
        for instance_id in range(1, instance_count):
            pos_list = []
            ys, xs = np.where(instance_label_map == instance_id)
            pos_list = list(zip(ys, xs))

            if len(pos_list) < 3:
                continue

            pos_list_sorted = sort_and_expand_with_direction_v2(
                pos_list, f_direction, p_tcl_map
            )
            all_pos_yxs.append(pos_list_sorted)

    p_char_maps = p_char_maps.transpose([1, 2, 0])
    decoded_str, keep_yxs_list = ctc_decoder_for_image(
        all_pos_yxs, logits_map=p_char_maps, Lexicon_Table=Lexicon_Table
    )
    return keep_yxs_list, decoded_str


def extract_main_direction(pos_list, f_direction):
    """
    f_direction: h x w x 2
    pos_list: [[y, x], [y, x], [y, x] ...]
    """
    pos_list = np.array(pos_list)
    point_direction = f_direction[pos_list[:, 0], pos_list[:, 1]]
    point_direction = point_direction[:, ::-1]  # x, y -> y, x
    average_direction = np.mean(point_direction, axis=0, keepdims=True)
    average_direction = average_direction / (np.linalg.norm(average_direction) + 1e-6)
    return average_direction


def sort_by_direction_with_image_id_deprecated(pos_list, f_direction):
    """
    f_direction: h x w x 2
    pos_list: [[id, y, x], [id, y, x], [id, y, x] ...]
    """
    pos_list_full = np.array(pos_list).reshape(-1, 3)
    pos_list = pos_list_full[:, 1:]
    point_direction = f_direction[pos_list[:, 0], pos_list[:, 1]]  # x, y
    point_direction = point_direction[:, ::-1]  # x, y -> y, x
    average_direction = np.mean(point_direction, axis=0, keepdims=True)
    pos_proj_leng = np.sum(pos_list * average_direction, axis=1)
    sorted_list = pos_list_full[np.argsort(pos_proj_leng)].tolist()
    return sorted_list


def sort_by_direction_with_image_id(pos_list, f_direction):
    """
    f_direction: h x w x 2
    pos_list: [[y, x], [y, x], [y, x] ...]
    """

    def sort_part_with_direction(pos_list_full, point_direction):
        pos_list_full = np.array(pos_list_full).reshape(-1, 3)
        pos_list = pos_list_full[:, 1:]
        point_direction = np.array(point_direction).reshape(-1, 2)
        average_direction = np.mean(point_direction, axis=0, keepdims=True)
        pos_proj_leng = np.sum(pos_list * average_direction, axis=1)
        sorted_list = pos_list_full[np.argsort(pos_proj_leng)].tolist()
        sorted_direction = point_direction[np.argsort(pos_proj_leng)].tolist()
        return sorted_list, sorted_direction

    pos_list = np.array(pos_list).reshape(-1, 3)
    point_direction = f_direction[pos_list[:, 1], pos_list[:, 2]]  # x, y
    point_direction = point_direction[:, ::-1]  # x, y -> y, x
    sorted_point, sorted_direction = sort_part_with_direction(pos_list, point_direction)

    point_num = len(sorted_point)
    if point_num >= 16:
        middle_num = point_num // 2
        first_part_point = sorted_point[:middle_num]
        first_point_direction = sorted_direction[:middle_num]
        sorted_fist_part_point, sorted_fist_part_direction = sort_part_with_direction(
            first_part_point, first_point_direction
        )

        last_part_point = sorted_point[middle_num:]
        last_point_direction = sorted_direction[middle_num:]
        sorted_last_part_point, sorted_last_part_direction = sort_part_with_direction(
            last_part_point, last_point_direction
        )
        sorted_point = sorted_fist_part_point + sorted_last_part_point
        sorted_direction = sorted_fist_part_direction + sorted_last_part_direction

    return sorted_point