add table eval and predict script

ppocr/postprocess/rec_postprocess.py

@@ -44,16 +44,16 @@ class BaseRecLabelDecode(object):
             self.character_str = string.printable[:-6]
             dict_character = list(self.character_str)
         elif character_type in support_character_type:
-            self.character_str = ""
+            self.character_str = []
             assert character_dict_path is not None, "character_dict_path should not be None when character_type is {}".format(
                 character_type)
             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")
-                    self.character_str += line
+                    self.character_str.append(line)
             if use_space_char:
-                self.character_str += " "
+                self.character_str.append(" ")
             dict_character = list(self.character_str)
 
         else:
@@ -288,3 +288,172 @@ class SRNLabelDecode(BaseRecLabelDecode):
             assert False, "unsupport type %s in get_beg_end_flag_idx" \
                           % beg_or_end
         return idx
+
+
+class TableLabelDecode(object):
+    """  """
+
+    def __init__(self,
+                 max_text_length,
+                 max_elem_length,
+                 max_cell_num,
+                 character_dict_path,
+                 **kwargs):
+        self.max_text_length = max_text_length
+        self.max_elem_length = max_elem_length
+        self.max_cell_num = max_cell_num
+        list_character, list_elem = self.load_char_elem_dict(character_dict_path)
+        list_character = self.add_special_char(list_character)
+        list_elem = self.add_special_char(list_elem)
+        self.dict_character = {}
+        self.dict_idx_character = {}
+        for i, char in enumerate(list_character):
+            self.dict_idx_character[i] = char
+            self.dict_character[char] = i
+        self.dict_elem = {}
+        self.dict_idx_elem = {}
+        for i, elem in enumerate(list_elem):
+            self.dict_idx_elem[i] = elem
+            self.dict_elem[elem] = i
+
+    def load_char_elem_dict(self, character_dict_path):
+        list_character = []
+        list_elem = []
+        with open(character_dict_path, "rb") as fin:
+            lines = fin.readlines()
+            substr = lines[0].decode('utf-8').strip("\n").split("\t")
+            character_num = int(substr[0])
+            elem_num = int(substr[1])
+            for cno in range(1, 1 + character_num):
+                character = lines[cno].decode('utf-8').strip("\n")
+                list_character.append(character)
+            for eno in range(1 + character_num, 1 + character_num + elem_num):
+                elem = lines[eno].decode('utf-8').strip("\n")
+                list_elem.append(elem)
+        return list_character, list_elem
+
+    def add_special_char(self, list_character):
+        self.beg_str = "sos"
+        self.end_str = "eos"
+        list_character = [self.beg_str] + list_character + [self.end_str]
+        return list_character
+
+    def get_sp_tokens(self):
+        char_beg_idx = self.get_beg_end_flag_idx('beg', 'char')
+        char_end_idx = self.get_beg_end_flag_idx('end', 'char')
+        elem_beg_idx = self.get_beg_end_flag_idx('beg', 'elem')
+        elem_end_idx = self.get_beg_end_flag_idx('end', 'elem')
+        elem_char_idx1 = self.dict_elem['<td>']
+        elem_char_idx2 = self.dict_elem['<td']
+        sp_tokens = np.array([char_beg_idx, char_end_idx, elem_beg_idx,
+                              elem_end_idx, elem_char_idx1, elem_char_idx2, self.max_text_length,
+                              self.max_elem_length, self.max_cell_num])
+        return sp_tokens
+
+    def __call__(self, preds):
+        structure_probs = preds['structure_probs']
+        loc_preds = preds['loc_preds']
+        if isinstance(structure_probs,paddle.Tensor):
+            structure_probs = structure_probs.numpy()
+        if isinstance(loc_preds,paddle.Tensor):
+            loc_preds = loc_preds.numpy()
+        structure_idx = structure_probs.argmax(axis=2)
+        structure_probs = structure_probs.max(axis=2)
+        structure_str, structure_pos, result_score_list, result_elem_idx_list = self.decode(structure_idx,
+                                                                                            structure_probs, 'elem')
+        res_html_code_list = []
+        res_loc_list = []
+        batch_num = len(structure_str)
+        for bno in range(batch_num):
+            res_loc = []
+            for sno in range(len(structure_str[bno])):
+                text = structure_str[bno][sno]
+                if text in ['<td>', '<td']:
+                    pos = structure_pos[bno][sno]
+                    res_loc.append(loc_preds[bno, pos])
+            res_html_code = ''.join(structure_str[bno])
+            res_loc = np.array(res_loc)
+            res_html_code_list.append(res_html_code)
+            res_loc_list.append(res_loc)
+        return {'res_html_code': res_html_code_list, 'res_loc': res_loc_list, 'res_score_list': result_score_list,
+                'res_elem_idx_list': result_elem_idx_list,'structure_str_list':structure_str}
+
+    def decode(self, text_index, structure_probs, char_or_elem):
+        """convert text-label into text-index.
+        """
+        if char_or_elem == "char":
+            max_len = self.max_text_length
+            current_dict = self.dict_idx_character
+        else:
+            max_len = self.max_elem_length
+            current_dict = self.dict_idx_elem
+            ignored_tokens = self.get_ignored_tokens('elem')
+            beg_idx, end_idx = ignored_tokens
+
+        #         select_td_tokens = []
+        #         select_span_tokens = []
+        #         for elem in self.dict_elem:
+        # #             if elem == '<td>' or elem == '<td' or elem == '<tr>'\
+        # #                 or 'rowspan' in elem or 'colspan' in elem:
+        #             if elem == '<td>' or elem == '<td' or elem == '<tr>':
+        #                 select_td_tokens.append(self.dict_elem[elem])
+        #             if 'rowspan' in elem or 'colspan' in elem:
+        #                 select_span_tokens.append(self.dict_elem[elem])
+        result_list = []
+        result_pos_list = []
+        result_score_list = []
+        result_elem_idx_list = []
+        batch_size = len(text_index)
+        for batch_idx in range(batch_size):
+            char_list = []
+            elem_pos_list = []
+            elem_idx_list = []
+            score_list = []
+            for idx in range(len(text_index[batch_idx])):
+                tmp_elem_idx = int(text_index[batch_idx][idx])
+                if idx > 0 and tmp_elem_idx == end_idx:
+                    break
+                if tmp_elem_idx in ignored_tokens:
+                    continue
+                #                 if tmp_elem_idx in select_td_tokens:
+                #                     total_td_score += structure_probs[batch_idx, idx]
+                #                     total_td_num += 1
+                #                 if tmp_elem_idx in select_span_tokens:
+                #                     total_span_score += structure_probs[batch_idx, idx]
+                #                     total_span_num += 1
+                char_list.append(current_dict[tmp_elem_idx])
+                elem_pos_list.append(idx)
+                score_list.append(structure_probs[batch_idx, idx])
+                elem_idx_list.append(tmp_elem_idx)
+            result_list.append(char_list)
+            result_pos_list.append(elem_pos_list)
+            result_score_list.append(score_list)
+            result_elem_idx_list.append(elem_idx_list)
+        return result_list, result_pos_list, result_score_list, result_elem_idx_list
+
+    def get_ignored_tokens(self, char_or_elem):
+        beg_idx = self.get_beg_end_flag_idx("beg", char_or_elem)
+        end_idx = self.get_beg_end_flag_idx("end", char_or_elem)
+        return [beg_idx, end_idx]
+
+    def get_beg_end_flag_idx(self, beg_or_end, char_or_elem):
+        if char_or_elem == "char":
+            if beg_or_end == "beg":
+                idx = self.dict_character[self.beg_str]
+            elif beg_or_end == "end":
+                idx = self.dict_character[self.end_str]
+            else:
+                assert False, "Unsupport type %s in get_beg_end_flag_idx of char" \
+                              % beg_or_end
+        elif char_or_elem == "elem":
+            if beg_or_end == "beg":
+                idx = self.dict_elem[self.beg_str]
+            elif beg_or_end == "end":
+                idx = self.dict_elem[self.end_str]
+            else:
+                assert False, "Unsupport type %s in get_beg_end_flag_idx of elem" \
+                              % beg_or_end
+        else:
+            assert False, "Unsupport type %s in char_or_elem" \
+                          % char_or_elem
+        return idx

ppocr/utils/dict/table_dict.txt

+←
+</overline>
+☆
+─
+α
+
+ 
+⋅
+$
+ω
+ψ
+χ
+(
+υ
+≥
+σ
+,
+ρ
+ε
+0
+■
+4
+8
+✗
+b
+<
+✓
+Ψ
+Ω
+€
+D
+3
+Π
+H
+║
+</
+>
+L
+Φ
+Χ
+θ
+P
+κ
+λ
+μ
+T
+ξ
+X
+β
+γ
+δ
+\
+ζ
+η
+`
+d
+<strike>
+h
+f
+l
+Θ
+p
+√
+t
+</sub>
+x
+Β
+Γ
+Δ
+|
+ǂ
+ɛ
+j
+̧
+➢
+⁡
+̌
+′
+«
+△
+▲
+#
+</b>
+'
+Ι
++
+¶
+/
+▼
+⇑
+□
+·
+7
+▪
+;
+?
+➔
+∩
+C
+÷
+G
+⇒
+K
+<sup>
+O
+S
+С
+W
+Α
+[
+○
+_
+●
+‡
+c
+z
+g
+<i>
+o
+<sub>
+〈
+〉
+s
+⩽
+w
+φ
+ʹ
+{
+»
+∣
+̆
+e
+ˆ
+∈
+τ
+◆
+ι
+∅
+∆
+∙
+∘
+Ø
+ß
+✔
+∞
+∑
+−
+×
+◊
+∗
+∖
+˃
+˂
+∫
+"
+i
+&
+π
+↔
+*
+∥
+æ
+∧
+.
+⁄
+ø
+Q
+∼
+6
+⁎
+:
+★
+>
+a
+B
+≈
+F
+J
+̄
+N
+♯
+R
+V
+<overline>
+―
+Z
+♣
+^
+¤
+¥
+§
+<underline>
+¢
+£
+≦
+­
+≤
+‖
+Λ
+©
+n
+↓
+→
+↑
+r
+°
+±
+v
+<b>
+♂
+k
+♀
+~
+ᅟ
+̇
+@
+”
+♦
+ł
+®
+⊕
+„
+!
+</sup>
+%
+⇓
+)
+-
+1
+5
+9
+=
+А
+A
+‰
+⋆
+Σ
+E
+◦
+I
+※
+M
+m
+̨
+⩾
+†
+</i>
+•
+U
+Y
+

+]
+̸
+2
+‐
+–
+‒
+̂
+—
+̀
+́
+’
+‘
+⋮
+⋯
+̊
+“
+̈
+≧
+q
+u
+ı
+y
+</underline>
+​
+̃
+}
+ν

ppocr/utils/dict/table_structure_dict.txt

+277	28	1267	1186
+<b>
+V
+a
+r
+i
+b
+l
+e
+</b>
+H
+z
+d
+ 
+t
+o
+9
+5
+%
+C
+I
+<i>
+p
+</i>
+v
+u
+*
+A
+g
+(
+m
+n
+)
+0
+.
+7
+1
+6
+≤
+>
+8
+3
+–
+2
+G
+4
+M
+F
+T
+y
+f
+s
+L
+w
+c
+U
+h
+D
+S
+Q
+R
+x
+P
+-
+E
+O
+/
+k
+,
++
+N
+K
+q
+′
+[
+]
+<
+≥
+<sup>
+−
+</sup>
+μ
+±
+J
+j
+W
+_
+Δ
+B
+“
+:
+Y
+α
+λ
+;
+<sub>
+</sub>
+?
+∼
+=
+°
+#
+̊
+̈
+̂
+’
+Z
+X
+∗
+—
+β
+'
+†
+~
+@
+"
+γ
+↓
+↑
+&
+‡
+χ
+”
+σ
+§
+|
+¶
+‐
+×
+$
+→
+√
+✓
+‘
+\
+∞
+π
+•
+®
+^
+∆
+≧
+<underline>
+</underline>
+́
+♀
+♂
+‒
+⁎
+▲
+·
+£
+φ
+Ψ
+ß
+△
+☆
+▪
+η
+€
+∧
+̃
+Φ
+ρ
+̄
+δ
+‰
+̧
+Ω
+♦
+{
+}
+̀
+∑
+∫
+ø
+κ
+ε
+¥
+※
+`
+ω
+Σ
+➔
+‖
+Β
+̸
+

+─
+●
+⩾
+Χ
+Α
+⋅
+◆
+★
+■
+ψ
+ǂ
+□
+ζ
+!
+Γ
+↔
+θ
+⁄
+〈
+〉
+―
+υ
+τ
+⋆
+Ø
+©
+∥
+С
+˂
+➢
+ɛ
+⁡
+✗
+←
+○
+¢
+⩽
+∖
+˃
+­
+≈
+Π
+̌
+≦
+∅
+ᅟ
+<overline>
+</overline>
+∣
+¤
+♯
+̆
+ξ
+÷
+▼
+
+ι
+ν
+║
+<strike>
+</strike>
+◦
+​
+◊
+∙
+«
+»
+ł
+ı
+Θ
+∈
+„
+∘
+✔
+̇
+æ
+ʹ
+ˆ
+♣
+⇓
+∩
+⊕
+⇒
+⇑
+̨
+Ι
+Λ
+⋯
+А
+⋮
+<thead>
+<tr>
+<td>
+</td>
+</tr>
+</thead>
+<tbody>
+</tbody>
+<td
+ colspan="5"
+>
+ colspan="2"
+ colspan="3"
+ rowspan="2"
+ colspan="4"
+ colspan="6"
+ rowspan="3"
+ colspan="9"
+ colspan="10"
+ colspan="7"
+ rowspan="4"
+ rowspan="5"
+ rowspan="9"
+ colspan="8"
+ rowspan="8"
+ rowspan="6"
+ rowspan="7"
+ rowspan="10"
+0	2924682
+1	3405345
+2	2363468
+3	2709165
+4	4078680
+5	3250792
+6	1923159
+7	1617890
+8	1450532
+9	1717624
+10	1477550
+11	1489223
+12	915528
+13	819193
+14	593660
+15	518924
+16	682065
+17	494584
+18	400591
+19	396421
+20	340994
+21	280688
+22	250328
+23	226786
+24	199927
+25	182707
+26	164629
+27	141613
+28	127554
+29	116286
+30	107682
+31	96367
+32	88002
+33	79234
+34	72186
+35	65921
+36	60374
+37	55976
+38	52166
+39	47414
+40	44932
+41	41279
+42	38232
+43	35463
+44	33703
+45	30557
+46	29639
+47	27000
+48	25447
+49	23186
+50	22093
+51	20412
+52	19844
+53	18261
+54	17561
+55	16499
+56	15597
+57	14558
+58	14372
+59	13445
+60	13514
+61	12058
+62	11145
+63	10767
+64	10370
+65	9630
+66	9337
+67	8881
+68	8727
+69	8060
+70	7994
+71	7740
+72	7189
+73	6729
+74	6749
+75	6548
+76	6321
+77	5957
+78	5740
+79	5407
+80	5370
+81	5035
+82	4921
+83	4656
+84	4600
+85	4519
+86	4277
+87	4023
+88	3939
+89	3910
+90	3861
+91	3560
+92	3483
+93	3406
+94	3346
+95	3229
+96	3122
+97	3086
+98	3001
+99	2884
+100	2822
+101	2677
+102	2670
+103	2610
+104	2452
+105	2446
+106	2400
+107	2300
+108	2316
+109	2196
+110	2089
+111	2083
+112	2041
+113	1881
+114	1838
+115	1896
+116	1795
+117	1786
+118	1743
+119	1765
+120	1750
+121	1683
+122	1563
+123	1499
+124	1513
+125	1462
+126	1388
+127	1441
+128	1417
+129	1392
+130	1306
+131	1321
+132	1274
+133	1294
+134	1240
+135	1126
+136	1157
+137	1130
+138	1084
+139	1130
+140	1083
+141	1040
+142	980
+143	1031
+144	974
+145	980
+146	932
+147	898
+148	960
+149	907
+150	852
+151	912
+152	859
+153	847
+154	876
+155	792
+156	791
+157	765
+158	788
+159	787
+160	744
+161	673
+162	683
+163	697
+164	666
+165	680
+166	632
+167	677
+168	657
+169	618
+170	587
+171	585
+172	567
+173	549
+174	562
+175	548
+176	542
+177	539
+178	542
+179	549
+180	547
+181	526
+182	525
+183	514
+184	512
+185	505
+186	515
+187	467
+188	475
+189	458
+190	435
+191	443
+192	427
+193	424
+194	404
+195	389
+196	429
+197	404
+198	386
+199	351
+200	388
+201	408
+202	361
+203	346
+204	324
+205	361
+206	363
+207	364
+208	323
+209	336
+210	342
+211	315
+212	325
+213	328
+214	314
+215	327
+216	320
+217	300
+218	295
+219	315
+220	310
+221	295
+222	275
+223	248
+224	274
+225	232
+226	293
+227	259
+228	286
+229	263
+230	242
+231	214
+232	261
+233	231
+234	211
+235	250
+236	233
+237	206
+238	224
+239	210
+240	233
+241	223
+242	216
+243	222
+244	207
+245	212
+246	196
+247	205
+248	201
+249	202
+250	211
+251	201
+252	215
+253	179
+254	163
+255	179
+256	191
+257	188
+258	196
+259	150
+260	154
+261	176
+262	211
+263	166
+264	171
+265	165
+266	149
+267	182
+268	159
+269	161
+270	164
+271	161
+272	141
+273	151
+274	127
+275	129
+276	142
+277	158
+278	148
+279	135
+280	127
+281	134
+282	138
+283	131
+284	126
+285	125
+286	130
+287	126
+288	135
+289	125
+290	135
+291	131
+292	95
+293	135
+294	106
+295	117
+296	136
+297	128
+298	128
+299	118
+300	109
+301	112
+302	117
+303	108
+304	120
+305	100
+306	95
+307	108
+308	112
+309	77
+310	120
+311	104
+312	109
+313	89
+314	98
+315	82
+316	98
+317	93
+318	77
+319	93
+320	77
+321	98
+322	93
+323	86
+324	89
+325	73
+326	70
+327	71
+328	77
+329	87
+330	77
+331	93
+332	100
+333	83
+334	72
+335	74
+336	69
+337	77
+338	68
+339	78
+340	90
+341	98
+342	75
+343	80
+344	63
+345	71
+346	83
+347	66
+348	71
+349	70
+350	62
+351	62
+352	59
+353	63
+354	62
+355	52
+356	64
+357	64
+358	56
+359	49
+360	57
+361	63
+362	60
+363	68
+364	62
+365	55
+366	54
+367	40
+368	75
+369	70
+370	53
+371	58
+372	57
+373	55
+374	69
+375	57
+376	53
+377	43
+378	45
+379	47
+380	56
+381	51
+382	59
+383	51
+384	43
+385	34
+386	57
+387	49
+388	39
+389	46
+390	48
+391	43
+392	40
+393	54
+394	50
+395	41
+396	43
+397	33
+398	27
+399	49
+400	44
+401	44
+402	38
+403	30
+404	32
+405	37
+406	39
+407	42
+408	53
+409	39
+410	34
+411	31
+412	32
+413	52
+414	27
+415	41
+416	34
+417	36
+418	50
+419	35
+420	32
+421	33
+422	45
+423	35
+424	40
+425	29
+426	41
+427	40
+428	39
+429	32
+430	31
+431	34
+432	29
+433	27
+434	26
+435	22
+436	34
+437	28
+438	30
+439	38
+440	35
+441	36
+442	36
+443	27
+444	24
+445	33
+446	31
+447	25
+448	33
+449	27
+450	32
+451	46
+452	31
+453	35
+454	35
+455	34
+456	26
+457	21
+458	25
+459	26
+460	24
+461	27
+462	33
+463	30
+464	35
+465	21
+466	32
+467	19
+468	27
+469	16
+470	28
+471	26
+472	27
+473	26
+474	25
+475	25
+476	27
+477	20
+478	28
+479	22
+480	23
+481	16
+482	25
+483	27
+484	19
+485	23
+486	19
+487	15
+488	15
+489	23
+490	24
+491	19
+492	20
+493	18
+494	17
+495	30
+496	28
+497	20
+498	29
+499	17
+500	19
+501	21
+502	15
+503	24
+504	15
+505	19
+506	25
+507	16
+508	23
+509	26
+510	21
+511	15
+512	12
+513	16
+514	18
+515	24
+516	26
+517	18
+518	8
+519	25
+520	14
+521	8
+522	24
+523	20
+524	18
+525	15
+526	13
+527	17
+528	18
+529	22
+530	21
+531	9
+532	16
+533	17
+534	13
+535	17
+536	15
+537	13
+538	20
+539	13
+540	19
+541	29
+542	10
+543	8
+544	18
+545	13
+546	9
+547	18
+548	10
+549	18
+550	18
+551	9
+552	9
+553	15
+554	13
+555	15
+556	14
+557	14
+558	18
+559	8
+560	13
+561	9
+562	7
+563	12
+564	6
+565	9
+566	9
+567	18
+568	9
+569	10
+570	13
+571	14
+572	13
+573	21
+574	8
+575	16
+576	12
+577	9
+578	16
+579	17
+580	22
+581	6
+582	14
+583	13
+584	15
+585	11
+586	13
+587	5
+588	12
+589	13
+590	15
+591	13
+592	15
+593	12
+594	7
+595	18
+596	12
+597	13
+598	13
+599	13
+600	12
+601	12
+602	10
+603	11
+604	6
+605	6
+606	2
+607	9
+608	8
+609	12
+610	9
+611	12
+612	13
+613	12
+614	14
+615	9
+616	8
+617	9
+618	14
+619	13
+620	12
+621	6
+622	8
+623	8
+624	8
+625	12
+626	8
+627	7
+628	5
+629	8
+630	12
+631	6
+632	10
+633	10
+634	7
+635	8
+636	9
+637	6
+638	9
+639	4
+640	12
+641	4
+642	3
+643	11
+644	10
+645	6
+646	12
+647	12
+648	4
+649	4
+650	9
+651	8
+652	6
+653	5
+654	14
+655	10
+656	11
+657	8
+658	5
+659	5
+660	9
+661	13
+662	4
+663	5
+664	9
+665	11
+666	12
+667	7
+668	13
+669	2
+670	1
+671	7
+672	7
+673	7
+674	10
+675	9
+676	6
+677	5
+678	7
+679	6
+680	3
+681	3
+682	4
+683	9
+684	8
+685	5
+686	3
+687	11
+688	9
+689	2
+690	6
+691	5
+692	9
+693	5
+694	6
+695	5
+696	9
+697	8
+698	3
+699	7
+700	5
+701	9
+702	8
+703	7
+704	2
+705	3
+706	7
+707	6
+708	6
+709	10
+710	2
+711	10
+712	6
+713	7
+714	5
+715	6
+716	4
+717	6
+718	8
+719	4
+720	6
+721	7
+722	5
+723	7
+724	3
+725	10
+726	10
+727	3
+728	7
+729	7
+730	5
+731	2
+732	1
+733	5
+734	1
+735	5
+736	6
+737	2
+738	2
+739	3
+740	7
+741	2
+742	7
+743	4
+744	5
+745	4
+746	5
+747	3
+748	1
+749	4
+750	4
+751	2
+752	4
+753	6
+754	6
+755	6
+756	3
+757	2
+758	5
+759	5
+760	3
+761	4
+762	2
+763	1
+764	8
+765	3
+766	4
+767	3
+768	1
+769	5
+770	3
+771	3
+772	4
+773	4
+774	1
+775	3
+776	2
+777	2
+778	3
+779	3
+780	1
+781	4
+782	3
+783	4
+784	6
+785	3
+786	5
+787	4
+788	2
+789	4
+790	5
+791	4
+792	6
+794	4
+795	1
+796	1
+797	4
+798	2
+799	3
+800	3
+801	1
+802	5
+803	5
+804	3
+805	3
+806	3
+807	4
+808	4
+809	2
+811	5
+812	4
+813	6
+814	3
+815	2
+816	2
+817	3
+818	5
+819	3
+820	1
+821	1
+822	4
+823	3
+824	4
+825	8
+826	3
+827	5
+828	5
+829	3
+830	6
+831	3
+832	4
+833	8
+834	5
+835	3
+836	3
+837	2
+838	4
+839	2
+840	1
+841	3
+842	2
+843	1
+844	3
+846	4
+847	4
+848	3
+849	3
+850	2
+851	3
+853	1
+854	4
+855	4
+856	2
+857	4
+858	1
+859	2
+860	5
+861	1
+862	1
+863	4
+864	2
+865	2
+867	5
+868	1
+869	4
+870	1
+871	1
+872	1
+873	2
+875	5
+876	3
+877	1
+878	3
+879	3
+880	3
+881	2
+882	1
+883	6
+884	2
+885	2
+886	1
+887	1
+888	3
+889	2
+890	2
+891	3
+892	1
+893	3
+894	1
+895	5
+896	1
+897	3
+899	2
+900	2
+902	1
+903	2
+904	4
+905	4
+906	3
+907	1
+908	1
+909	2
+910	5
+911	2
+912	3
+914	1
+915	1
+916	2
+918	2
+919	2
+920	4
+921	4
+922	1
+923	1
+924	4
+925	5
+926	1
+928	2
+929	1
+930	1
+931	1
+932	1
+933	1
+934	2
+935	1
+936	1
+937	1
+938	2
+939	1
+941	1
+942	4
+944	2
+945	2
+946	2
+947	1
+948	1
+950	1
+951	2
+953	1
+954	2
+955	1
+956	1
+957	2
+958	1
+960	3
+962	4
+963	1
+964	1
+965	3
+966	2
+967	2
+968	1
+969	3
+970	3
+972	1
+974	4
+975	3
+976	3
+977	2
+979	2
+980	1
+981	1
+983	5
+984	1
+985	3
+986	1
+987	2
+988	4
+989	2
+991	2
+992	2
+993	1
+994	1
+996	2
+997	2
+998	1
+999	3
+1000	2
+1001	1
+1002	3
+1003	3
+1004	2
+1005	3
+1006	1
+1007	2
+1009	1
+1011	1
+1013	3
+1014	1
+1016	2
+1017	1
+1018	1
+1019	1
+1020	4
+1021	1
+1022	2
+1025	1
+1026	1
+1027	2
+1028	1
+1030	1
+1031	2
+1032	4
+1034	3
+1035	2
+1036	1
+1038	1
+1039	1
+1040	1
+1041	1
+1042	2
+1043	1
+1044	2
+1045	4
+1048	1
+1050	1
+1051	1
+1052	2
+1054	1
+1055	3
+1056	2
+1057	1
+1059	1
+1061	2
+1063	1
+1064	1
+1065	1
+1066	1
+1067	1
+1068	1
+1069	2
+1074	1
+1075	1
+1077	1
+1078	1
+1079	1
+1082	1
+1085	1
+1088	1
+1090	1
+1091	1
+1092	2
+1094	2
+1097	2
+1098	1
+1099	2
+1101	2
+1102	1
+1104	1
+1105	1
+1107	1
+1109	1
+1111	2
+1112	1
+1114	2
+1115	2
+1116	2
+1117	1
+1118	1
+1119	1
+1120	1
+1122	1
+1123	1
+1127	1
+1128	3
+1132	2
+1138	3
+1142	1
+1145	4
+1150	1
+1153	2
+1154	1
+1158	1
+1159	1
+1163	1
+1165	1
+1169	2
+1174	1
+1176	1
+1177	1
+1178	2
+1179	1
+1180	2
+1181	1
+1182	1
+1183	2
+1185	1
+1187	1
+1191	2
+1193	1
+1195	3
+1196	1
+1201	3
+1203	1
+1206	1
+1210	1
+1213	1
+1214	1
+1215	2
+1218	1
+1220	1
+1221	1
+1225	1
+1226	1
+1233	2
+1241	1
+1243	1
+1249	1
+1250	2
+1251	1
+1254	1
+1255	2
+1260	1
+1268	1
+1270	1
+1273	1
+1274	1
+1277	1
+1284	1
+1287	1
+1291	1
+1292	2
+1294	1
+1295	2
+1297	1
+1298	1
+1301	1
+1307	1
+1308	3
+1311	2
+1313	1
+1316	1
+1321	1
+1324	1
+1325	1
+1330	1
+1333	1
+1334	1
+1338	2
+1340	1
+1341	1
+1342	1
+1343	1
+1345	1
+1355	1
+1357	1
+1360	2
+1375	1
+1376	1
+1380	1
+1383	1
+1387	1
+1389	1
+1393	1
+1394	1
+1396	1
+1398	1
+1410	1
+1414	1
+1419	1
+1425	1
+1434	1
+1435	1
+1438	1
+1439	1
+1447	1
+1455	2
+1460	1
+1461	1
+1463	1
+1466	1
+1470	1
+1473	1
+1478	1
+1480	1
+1483	1
+1484	1
+1485	2
+1492	2
+1499	1
+1509	1
+1512	1
+1513	1
+1523	1
+1524	1
+1525	2
+1529	1
+1539	1
+1544	1
+1568	1
+1584	1
+1591	1
+1598	1
+1600	1
+1604	1
+1614	1
+1617	1
+1621	1
+1622	1
+1626	1
+1638	1
+1648	1
+1658	1
+1661	1
+1679	1
+1682	1
+1693	1
+1700	1
+1705	1
+1707	1
+1722	1
+1728	1
+1758	1
+1762	1
+1763	1
+1775	1
+1776	1
+1801	1
+1810	1
+1812	1
+1827	1
+1834	1
+1846	1
+1847	1
+1848	1
+1851	1
+1862	1
+1866	1
+1877	2
+1884	1
+1888	1
+1903	1
+1912	1
+1925	1
+1938	1
+1955	1
+1998	1
+2054	1
+2058	1
+2065	1
+2069	1
+2076	1
+2089	1
+2104	1
+2111	1
+2133	1
+2138	1
+2156	1
+2204	1
+2212	1
+2237	1
+2246	2
+2298	1
+2304	1
+2360	1
+2400	1
+2481	1
+2544	1
+2586	1
+2622	1
+2666	1
+2682	1
+2725	1
+2920	1
+3997	1
+4019	1
+5211	1
+12	19
+14	1
+16	401
+18	2
+20	421
+22	557
+24	625
+26	50
+28	4481
+30	52
+32	550
+34	5840
+36	4644
+38	87
+40	5794
+41	33
+42	571
+44	11805
+46	4711
+47	7
+48	597
+49	12
+50	678
+51	2
+52	14715
+53	3
+54	7322
+55	3
+56	508
+57	39
+58	3486
+59	11
+60	8974
+61	45
+62	1276
+63	4
+64	15693
+65	15
+66	657
+67	13
+68	6409
+69	10
+70	3188
+71	25
+72	1889
+73	27
+74	10370
+75	9
+76	12432
+77	23
+78	520
+79	15
+80	1534
+81	29
+82	2944
+83	23
+84	12071
+85	36
+86	1502
+87	10
+88	10978
+89	11
+90	889
+91	16
+92	4571
+93	17
+94	7855
+95	21
+96	2271
+97	33
+98	1423
+99	15
+100	11096
+101	21
+102	4082
+103	13
+104	5442
+105	25
+106	2113
+107	26
+108	3779
+109	43
+110	1294
+111	29
+112	7860
+113	29
+114	4965
+115	22
+116	7898
+117	25
+118	1772
+119	28
+120	1149
+121	38
+122	1483
+123	32
+124	10572
+125	25
+126	1147
+127	31
+128	1699
+129	22
+130	5533
+131	22
+132	4669
+133	34
+134	3777
+135	10
+136	5412
+137	21
+138	855
+139	26
+140	2485
+141	46
+142	1970
+143	27
+144	6565
+145	40
+146	933
+147	15
+148	7923
+149	16
+150	735
+151	23
+152	1111
+153	33
+154	3714
+155	27
+156	2445
+157	30
+158	3367
+159	10
+160	4646
+161	27
+162	990
+163	23
+164	5679
+165	25
+166	2186
+167	17
+168	899
+169	32
+170	1034
+171	22
+172	6185
+173	32
+174	2685
+175	17
+176	1354
+177	38
+178	1460
+179	15
+180	3478
+181	20
+182	958
+183	20
+184	6055
+185	23
+186	2180
+187	15
+188	1416
+189	30
+190	1284
+191	22
+192	1341
+193	21
+194	2413
+195	18
+196	4984
+197	13
+198	830
+199	22
+200	1834
+201	19
+202	2238
+203	9
+204	3050
+205	22
+206	616
+207	17
+208	2892
+209	22
+210	711
+211	30
+212	2631
+213	19
+214	3341
+215	21
+216	987
+217	26
+218	823
+219	9
+220	3588
+221	20
+222	692
+223	7
+224	2925
+225	31
+226	1075
+227	16
+228	2909
+229	18
+230	673
+231	20
+232	2215
+233	14
+234	1584
+235	21
+236	1292
+237	29
+238	1647
+239	25
+240	1014
+241	30
+242	1648
+243	19
+244	4465
+245	10
+246	787
+247	11
+248	480
+249	25
+250	842
+251	15
+252	1219
+253	23
+254	1508
+255	8
+256	3525
+257	16
+258	490
+259	12
+260	1678
+261	14
+262	822
+263	16
+264	1729
+265	28
+266	604
+267	11
+268	2572
+269	7
+270	1242
+271	15
+272	725
+273	18
+274	1983
+275	13
+276	1662
+277	19
+278	491
+279	12
+280	1586
+281	14
+282	563
+283	10
+284	2363
+285	10
+286	656
+287	14
+288	725
+289	28
+290	871
+291	9
+292	2606
+293	12
+294	961
+295	9
+296	478
+297	13
+298	1252
+299	10
+300	736
+301	19
+302	466
+303	13
+304	2254
+305	12
+306	486
+307	14
+308	1145
+309	13
+310	955
+311	13
+312	1235
+313	13
+314	931
+315	14
+316	1768
+317	11
+318	330
+319	10
+320	539
+321	23
+322	570
+323	12
+324	1789
+325	13
+326	884
+327	5
+328	1422
+329	14
+330	317
+331	11
+332	509
+333	13
+334	1062
+335	12
+336	577
+337	27
+338	378
+339	10
+340	2313
+341	9
+342	391
+343	13
+344	894
+345	17
+346	664
+347	9
+348	453
+349	6
+350	363
+351	15
+352	1115
+353	13
+354	1054
+355	8
+356	1108
+357	12
+358	354
+359	7
+360	363
+361	16
+362	344
+363	11
+364	1734
+365	12
+366	265
+367	10
+368	969
+369	16
+370	316
+371	12
+372	757
+373	7
+374	563
+375	15
+376	857
+377	9
+378	469
+379	9
+380	385
+381	12
+382	921
+383	15
+384	764
+385	14
+386	246
+387	6
+388	1108
+389	14
+390	230
+391	8
+392	266
+393	11
+394	641
+395	8
+396	719
+397	9
+398	243
+399	4
+400	1108
+401	7
+402	229
+403	7
+404	903
+405	7
+406	257
+407	12
+408	244
+409	3
+410	541
+411	6
+412	744
+413	8
+414	419
+415	8
+416	388
+417	19
+418	470
+419	14
+420	612
+421	6
+422	342
+423	3
+424	1179
+425	3
+426	116
+427	14
+428	207
+429	6
+430	255
+431	4
+432	288
+433	12
+434	343
+435	6
+436	1015
+437	3
+438	538
+439	10
+440	194
+441	6
+442	188
+443	15
+444	524
+445	7
+446	214
+447	7
+448	574
+449	6
+450	214
+451	5
+452	635
+453	9
+454	464
+455	5
+456	205
+457	9
+458	163
+459	2
+460	558
+461	4
+462	171
+463	14
+464	444
+465	11
+466	543
+467	5
+468	388
+469	6
+470	141
+471	4
+472	647
+473	3
+474	210
+475	4
+476	193
+477	7
+478	195
+479	7
+480	443
+481	10
+482	198
+483	3
+484	816
+485	6
+486	128
+487	9
+488	215
+489	9
+490	328
+491	7
+492	158
+493	11
+494	335
+495	8
+496	435
+497	6
+498	174
+499	1
+500	373
+501	5
+502	140
+503	7
+504	330
+505	9
+506	149
+507	5
+508	642
+509	3
+510	179
+511	3
+512	159
+513	8
+514	204
+515	7
+516	306
+517	4
+518	110
+519	5
+520	326
+521	6
+522	305
+523	6
+524	294
+525	7
+526	268
+527	5
+528	149
+529	4
+530	133
+531	2
+532	513
+533	10
+534	116
+535	5
+536	258
+537	4
+538	113
+539	4
+540	138
+541	6
+542	116
+544	485
+545	4
+546	93
+547	9
+548	299
+549	3
+550	256
+551	6
+552	92
+553	3
+554	175
+555	6
+556	253
+557	7
+558	95
+559	2
+560	128
+561	4
+562	206
+563	2
+564	465
+565	3
+566	69
+567	3
+568	157
+569	7
+570	97
+571	8
+572	118
+573	5
+574	130
+575	4
+576	301
+577	6
+578	177
+579	2
+580	397
+581	3
+582	80
+583	1
+584	128
+585	5
+586	52
+587	2
+588	72
+589	1
+590	84
+591	6
+592	323
+593	11
+594	77
+595	5
+596	205
+597	1
+598	244
+599	4
+600	69
+601	3
+602	89
+603	5
+604	254
+605	6
+606	147
+607	3
+608	83
+609	3
+610	77
+611	3
+612	194
+613	1
+614	98
+615	3
+616	243
+617	3
+618	50
+619	8
+620	188
+621	4
+622	67
+623	4
+624	123
+625	2
+626	50
+627	1
+628	239
+629	2
+630	51
+631	4
+632	65
+633	5
+634	188
+636	81
+637	3
+638	46
+639	3
+640	103
+641	1
+642	136
+643	3
+644	188
+645	3
+646	58
+648	122
+649	4
+650	47
+651	2
+652	155
+653	4
+654	71
+655	1
+656	71
+657	3
+658	50
+659	2
+660	177
+661	5
+662	66
+663	2
+664	183
+665	3
+666	50
+667	2
+668	53
+669	2
+670	115
+672	66
+673	2
+674	47
+675	1
+676	197
+677	2
+678	46
+679	3
+680	95
+681	3
+682	46
+683	3
+684	107
+685	1
+686	86
+687	2
+688	158
+689	4
+690	51
+691	1
+692	80
+694	56
+695	4
+696	40
+698	43
+699	3
+700	95
+701	2
+702	51
+703	2
+704	133
+705	1
+706	100
+707	2
+708	121
+709	2
+710	15
+711	3
+712	35
+713	2
+714	20
+715	3
+716	37
+717	2
+718	78
+720	55
+721	1
+722	42
+723	2
+724	218
+725	3
+726	23
+727	2
+728	26
+729	1
+730	64
+731	2
+732	65
+734	24
+735	2
+736	53
+737	1
+738	32
+739	1
+740	60
+742	81
+743	1
+744	77
+745	1
+746	47
+747	1
+748	62
+749	1
+750	19
+751	1
+752	86
+753	3
+754	40
+756	55
+757	2
+758	38
+759	1
+760	101
+761	1
+762	22
+764	67
+765	2
+766	35
+767	1
+768	38
+769	1
+770	22
+771	1
+772	82
+773	1
+774	73
+776	29
+777	1
+778	55
+780	23
+781	1
+782	16
+784	84
+785	3
+786	28
+788	59
+789	1
+790	33
+791	3
+792	24
+794	13
+795	1
+796	110
+797	2
+798	15
+800	22
+801	3
+802	29
+803	1
+804	87
+806	21
+808	29
+810	48
+812	28
+813	1
+814	58
+815	1
+816	48
+817	1
+818	31
+819	1
+820	66
+822	17
+823	2
+824	58
+826	10
+827	2
+828	25
+829	1
+830	29
+831	1
+832	63
+833	1
+834	26
+835	3
+836	52
+837	1
+838	18
+840	27
+841	2
+842	12
+843	1
+844	83
+845	1
+846	7
+847	1
+848	10
+850	26
+852	25
+853	1
+854	15
+856	27
+858	32
+859	1
+860	15
+862	43
+864	32
+865	1
+866	6
+868	39
+870	11
+872	25
+873	1
+874	10
+875	1
+876	20
+877	2
+878	19
+879	1
+880	30
+882	11
+884	53
+886	25
+887	1
+888	28
+890	6
+892	36
+894	10
+896	13
+898	14
+900	31
+902	14
+903	2
+904	43
+906	25
+908	9
+910	11
+911	1
+912	16
+913	1
+914	24
+916	27
+918	6
+920	15
+922	27
+923	1
+924	23
+926	13
+928	42
+929	1
+930	3
+932	27
+934	17
+936	8
+937	1
+938	11
+940	33
+942	4
+943	1
+944	18
+946	15
+948	13
+950	18
+952	12
+954	11
+956	21
+958	10
+960	13
+962	5
+964	32
+966	13
+968	8
+970	8
+971	1
+972	23
+973	2
+974	12
+975	1
+976	22
+978	7
+979	1
+980	14
+982	8
+984	22
+985	1
+986	6
+988	17
+989	1
+990	6
+992	13
+994	19
+996	11
+998	4
+1000	9
+1002	2
+1004	14
+1006	5
+1008	3
+1010	9
+1012	29
+1014	6
+1016	22
+1017	1
+1018	8
+1019	1
+1020	7
+1022	6
+1023	1
+1024	10
+1026	2
+1028	8
+1030	11
+1031	2
+1032	8
+1034	9
+1036	13
+1038	12
+1040	12
+1042	3
+1044	12
+1046	3
+1048	11
+1050	2
+1051	1
+1052	2
+1054	11
+1056	6
+1058	8
+1059	1
+1060	23
+1062	6
+1063	1
+1064	8
+1066	3
+1068	6
+1070	8
+1071	1
+1072	5
+1074	3
+1076	5
+1078	3
+1080	11
+1081	1
+1082	7
+1084	18
+1086	4
+1087	1
+1088	3
+1090	3
+1092	7
+1094	3
+1096	12
+1098	6
+1099	1
+1100	2
+1102	6
+1104	14
+1106	3
+1108	6
+1110	5
+1112	2
+1114	8
+1116	3
+1118	3
+1120	7
+1122	10
+1124	6
+1126	8
+1128	1
+1130	4
+1132	3
+1134	2
+1136	5
+1138	5
+1140	8
+1142	3
+1144	7
+1146	3
+1148	11
+1150	1
+1152	5
+1154	1
+1156	5
+1158	1
+1160	5
+1162	3
+1164	6
+1165	1
+1166	1
+1168	4
+1169	1
+1170	3
+1171	1
+1172	2
+1174	5
+1176	3
+1177	1
+1180	8
+1182	2
+1184	4
+1186	2
+1188	3
+1190	2
+1192	5
+1194	6
+1196	1
+1198	2
+1200	2
+1204	10
+1206	2
+1208	9
+1210	1
+1214	6
+1216	3
+1218	4
+1220	9
+1221	2
+1222	1
+1224	5
+1226	4
+1228	8
+1230	1
+1232	1
+1234	3
+1236	5
+1240	3
+1242	1
+1244	3
+1245	1
+1246	4
+1248	6
+1250	2
+1252	7
+1256	3
+1258	2
+1260	2
+1262	3
+1264	4
+1265	1
+1266	1
+1270	1
+1271	1
+1272	2
+1274	3
+1276	3
+1278	1
+1280	3
+1284	1
+1286	1
+1290	1
+1292	3
+1294	1
+1296	7
+1300	2
+1302	4
+1304	3
+1306	2
+1308	2
+1312	1
+1314	1
+1316	3
+1318	2
+1320	1
+1324	8
+1326	1
+1330	1
+1331	1
+1336	2
+1338	1
+1340	3
+1341	1
+1344	1
+1346	2
+1347	1
+1348	3
+1352	1
+1354	2
+1356	1
+1358	1
+1360	3
+1362	1
+1364	4
+1366	1
+1370	1
+1372	3
+1380	2
+1384	2
+1388	2
+1390	2
+1392	2
+1394	1
+1396	1
+1398	1
+1400	2
+1402	1
+1404	1
+1406	1
+1410	1
+1412	5
+1418	1
+1420	1
+1424	1
+1432	2
+1434	2
+1442	3
+1444	5
+1448	1
+1454	1
+1456	1
+1460	3
+1462	4
+1468	1
+1474	1
+1476	1
+1478	2
+1480	1
+1486	2
+1488	1
+1492	1
+1496	1
+1500	3
+1503	1
+1506	1
+1512	2
+1516	1
+1522	1
+1524	2
+1534	4
+1536	1
+1538	1
+1540	2
+1544	2
+1548	1
+1556	1
+1560	1
+1562	1
+1564	2
+1566	1
+1568	1
+1570	1
+1572	1
+1576	1
+1590	1
+1594	1
+1604	1
+1608	1
+1614	1
+1622	1
+1624	2
+1628	1
+1629	1
+1636	1
+1642	1
+1654	2
+1660	1
+1664	1
+1670	1
+1684	4
+1698	1
+1732	3
+1742	1
+1752	1
+1760	1
+1764	1
+1772	2
+1798	1
+1808	1
+1820	1
+1852	1
+1856	1
+1874	1
+1902	1
+1908	1
+1952	1
+2004	1
+2018	1
+2020	1
+2028	1
+2174	1
+2233	1
+2244	1
+2280	1
+2290	1
+2352	1
+2604	1
+4190	1

ppocr/utils/table_utils/matcher.py

+import json
+def distance(box_1, box_2):
+        x1, y1, x2, y2 = box_1
+        x3, y3, x4, y4 = box_2
+        # min_x = (x1 + x2) / 2
+        # min_y = (y1 + y2) / 2
+        # max_x = (x3 + x4) / 2
+        # max_y = (y3 + y4) / 2
+        dis = abs(x3 - x1) + abs(y3 - y1) + abs(x4- x2) + abs(y4 - y2)
+        dis_2 = abs(x3 - x1) + abs(y3 - y1)
+        dis_3 = abs(x4- x2) + abs(y4 - y2)
+        #dis = pow(min_x - max_x, 2) + pow(min_y - max_y, 2) + pow(x3 - x1, 2) + pow(y3 - y1, 2) + pow(x4- x2, 2) + pow(y4 - y2, 2) + abs(x3 - x1) + abs(y3 - y1) + abs(x4- x2) + abs(y4 - y2)
+        return dis + min(dis_2, dis_3)
+
+def compute_iou(rec1, rec2):
+    """
+    computing IoU
+    :param rec1: (y0, x0, y1, x1), which reflects
+            (top, left, bottom, right)
+    :param rec2: (y0, x0, y1, x1)
+    :return: scala value of IoU
+    """
+    # computing area of each rectangles
+    rec1, rec2 = rec1 * 1000, rec2 * 1000
+    S_rec1 = (rec1[2] - rec1[0]) * (rec1[3] - rec1[1])
+    S_rec2 = (rec2[2] - rec2[0]) * (rec2[3] - rec2[1])
+ 
+    # computing the sum_area
+    sum_area = S_rec1 + S_rec2
+ 
+    # find the each edge of intersect rectangle
+    left_line = max(rec1[1], rec2[1])
+    right_line = min(rec1[3], rec2[3])
+    top_line = max(rec1[0], rec2[0])
+    bottom_line = min(rec1[2], rec2[2])
+ 
+    # judge if there is an intersect
+    if left_line >= right_line or top_line >= bottom_line:
+        return 0
+    else:
+        intersect = (right_line - left_line) * (bottom_line - top_line)
+        return (intersect / (sum_area - intersect))*1.0
+ 
+
+
+def matcher_merge(ocr_bboxes, pred_bboxes): # ocr_bboxes: OCR pred_bboxes：端到端
+    all_dis = []
+    ious = []
+    matched = {}
+    for i, gt_box in enumerate(ocr_bboxes):
+        distances = []
+        for j, pred_box in enumerate(pred_bboxes):
+            distances.append((distance(gt_box, pred_box), 1. - compute_iou(gt_box, pred_box))) #获取两两cell之间的L1距离和 1- IOU
+        sorted_distances = distances.copy()
+        # 根据距离和IOU挑选最"近"的cell
+        sorted_distances = sorted(sorted_distances, key = lambda item: (item[1], item[0])) 
+        if distances.index(sorted_distances[0]) not in matched.keys(): 
+            matched[distances.index(sorted_distances[0])] = [i]
+        else:
+            matched[distances.index(sorted_distances[0])].append(i)
+    return matched#, sum(ious) / len(ious)
+def complex_num(pred_bboxes):
+    complex_nums = []
+    for bbox in pred_bboxes:
+        distances = []
+        temp_ious = []
+        for pred_bbox in pred_bboxes:
+            if bbox != pred_bbox:
+                distances.append(distance(bbox, pred_bbox))
+                temp_ious.append(compute_iou(bbox, pred_bbox))
+        complex_nums.append(temp_ious[distances.index(min(distances))])
+    return sum(complex_nums) / len(complex_nums)
+
+def get_rows(pred_bboxes):
+    pre_bbox = pred_bboxes[0]
+    res = []
+    step = 0
+    for i in range(len(pred_bboxes)):
+        bbox = pred_bboxes[i]
+        if bbox[1] - pre_bbox[1] > 2 or bbox[0] - pre_bbox[0] < 0:
+            break
+        else:
+            res.append(bbox)
+            step += 1
+    for i in range(step):
+        pred_bboxes.pop(0)
+    return res, pred_bboxes
+def refine_rows(pred_bboxes): # 微调整行的框，使在一条水平线上
+    ys_1 = []
+    ys_2 = []
+    for box in pred_bboxes:
+        ys_1.append(box[1])
+        ys_2.append(box[3])
+    min_y_1 = sum(ys_1) / len(ys_1)
+    min_y_2 = sum(ys_2) / len(ys_2)
+    re_boxes = []
+    for box in pred_bboxes:
+        box[1] = min_y_1
+        box[3] = min_y_2
+        re_boxes.append(box)
+    return re_boxes
+    
+def matcher_refine_row(gt_bboxes, pred_bboxes):
+    before_refine_pred_bboxes = pred_bboxes.copy()
+    pred_bboxes = []
+    while(len(before_refine_pred_bboxes) != 0):
+        row_bboxes, before_refine_pred_bboxes = get_rows(before_refine_pred_bboxes)
+        print(row_bboxes)
+        pred_bboxes.extend(refine_rows(row_bboxes))
+    all_dis = []
+    ious = []
+    matched = {}
+    for i, gt_box in enumerate(gt_bboxes):
+        distances = []
+        #temp_ious = []
+        for j, pred_box in enumerate(pred_bboxes):
+            distances.append(distance(gt_box, pred_box))
+            #temp_ious.append(compute_iou(gt_box, pred_box))
+        #all_dis.append(min(distances))
+        #ious.append(temp_ious[distances.index(min(distances))])
+        if distances.index(min(distances)) not in matched.keys(): 
+            matched[distances.index(min(distances))] = [i]
+        else:
+            matched[distances.index(min(distances))].append(i)
+    return matched#, sum(ious) / len(ious)
+
+
+
+#先挑选出一行，再进行匹配
+def matcher_structure_1(gt_bboxes, pred_bboxes_rows, pred_bboxes):
+    gt_box_index = 0
+    delete_gt_bboxes = gt_bboxes.copy()
+    match_bboxes_ready = []
+    matched = {}
+    while(len(delete_gt_bboxes) != 0):
+        row_bboxes, delete_gt_bboxes = get_rows(delete_gt_bboxes)
+        row_bboxes = sorted(row_bboxes, key = lambda key: key[0])
+        if len(pred_bboxes_rows) > 0:
+            match_bboxes_ready.extend(pred_bboxes_rows.pop(0))
+        print(row_bboxes)
+        for i, gt_box in enumerate(row_bboxes):
+            #print(gt_box)
+            pred_distances = []
+            distances = []  
+            for pred_bbox in pred_bboxes:
+                pred_distances.append(distance(gt_box, pred_bbox))
+            for j, pred_box in enumerate(match_bboxes_ready):
+                distances.append(distance(gt_box, pred_box))
+            index = pred_distances.index(min(distances))
+            #print('index', index)
+            if index not in matched.keys(): 
+                matched[index] = [gt_box_index]
+            else:
+                matched[index].append(gt_box_index)
+            gt_box_index += 1
+    return matched
+
+def matcher_structure(gt_bboxes, pred_bboxes_rows, pred_bboxes):
+    '''
+    gt_bboxes: 排序后
+    pred_bboxes: 
+    '''
+    pre_bbox = gt_bboxes[0]
+    matched = {}
+    match_bboxes_ready = []
+    match_bboxes_ready.extend(pred_bboxes_rows.pop(0))
+    for i, gt_box in enumerate(gt_bboxes):
+        
+        pred_distances = []
+        for pred_bbox in pred_bboxes:
+            pred_distances.append(distance(gt_box, pred_bbox))
+        distances = []
+        gap_pre = gt_box[1] - pre_bbox[1]
+        gap_pre_1 = gt_box[0] - pre_bbox[2]
+        #print(gap_pre, len(pred_bboxes_rows))
+        if (gap_pre_1 < 0 and len(pred_bboxes_rows) > 0):
+            match_bboxes_ready.extend(pred_bboxes_rows.pop(0))
+        if len(pred_bboxes_rows) == 1:
+            match_bboxes_ready.extend(pred_bboxes_rows.pop(0))
+        if len(match_bboxes_ready) == 0 and len(pred_bboxes_rows) > 0:
+            match_bboxes_ready.extend(pred_bboxes_rows.pop(0))
+        if len(match_bboxes_ready) == 0 and len(pred_bboxes_rows) == 0:
+            break
+        #print(match_bboxes_ready)
+        for j, pred_box in enumerate(match_bboxes_ready):
+            distances.append(distance(gt_box, pred_box))
+        index = pred_distances.index(min(distances))
+        #print(gt_box, index)
+        #match_bboxes_ready.pop(distances.index(min(distances)))
+        print(gt_box, match_bboxes_ready[distances.index(min(distances))])
+        if index not in matched.keys(): 
+            matched[index] = [i]
+        else:
+            matched[index].append(i)
+        pre_bbox = gt_box
+    return matched
+
+
+def main():
+    detect_bboxes = json.load(open('./f_detecion_bbox.json'))
+    gt_bboxes = json.load(open('./f_gt_bbox.json'))
+    all_node = 0
+    matched_right = 0
+    key = 'PMC4796501_003_00.png'
+    print(key)
+    gt_bbox = gt_bboxes[key]
+    pred_bbox = detect_bboxes[key]
+    matched = matcher(gt_bbox, pred_bbox)
+    print(matched)
+    
+
+if __name__ == "__main__":
+    main()
+

ppstructure/predict_system.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import sys
+import subprocess
+
+__dir__ = os.path.dirname(os.path.abspath(__file__))
+sys.path.append(__dir__)
+sys.path.append(os.path.abspath(os.path.join(__dir__, '../..')))
+
+os.environ["FLAGS_allocator_strategy"] = 'auto_growth'
+import cv2
+import copy
+import numpy as np
+import time
+import tools.infer.utility as utility
+from tools.infer.predict_system import TextSystem
+from ppstructure.table.predict_table import TableSystem, to_excel
+from ppstructure.layout.predict_layout import LayoutDetector
+from ppocr.utils.utility import get_image_file_list, check_and_read_gif
+from ppocr.utils.logging import get_logger
+
+logger = get_logger()
+
+
+def parse_args():
+    parser = utility.init_args()
+
+    # params for table structure
+    parser.add_argument("--table_max_len", type=int, default=488)
+    parser.add_argument("--table_max_text_length", type=int, default=100)
+    parser.add_argument("--table_max_elem_length", type=int, default=800)
+    parser.add_argument("--table_max_cell_num", type=int, default=500)
+    parser.add_argument("--table_model_dir", type=str)
+    parser.add_argument("--table_char_type", type=str, default='en')
+    parser.add_argument("--table_char_dict_path", type=str, default="./ppocr/utils/dict/table_structure_dict.txt")
+
+    # params for layout detector
+    parser.add_argument("--layout_model_dir", type=str)
+    return parser.parse_args()
+
+
+class OCRSystem():
+    def __init__(self, args):
+        self.text_system = TextSystem(args)
+        self.table_system = TableSystem(args)
+        self.table_layout = LayoutDetector(args)
+        self.use_angle_cls = args.use_angle_cls
+        self.drop_score = args.drop_score
+
+    def __call__(self, img):
+        ori_im = img.copy()
+        layout_res = self.table_layout(copy.deepcopy(img))
+        for region in layout_res:
+            x1, y1, x2, y2 = region['bbox']
+            roi_img = ori_im[y1:y2, x1:x2,:]
+            if region['label'] == 'table':
+                res = self.table_system(roi_img)
+            else:
+                res = self.text_system(roi_img)
+            region['res'] = res
+        return layout_res
+
+
+def main(args):
+    image_file_list = get_image_file_list(args.image_dir)
+    image_file_list = image_file_list[args.process_id::args.total_process_num]
+    excel_save_folder = 'output/table'
+    os.makedirs(excel_save_folder, exist_ok=True)
+
+    text_sys = OCRSystem(args)
+    img_num = len(image_file_list)
+    for i, image_file in enumerate(image_file_list):
+        logger.info("[{}/{}] {}".format(i, img_num, image_file))
+        img, flag = check_and_read_gif(image_file)
+        imgname = os.path.basename(image_file).split('.')[0]
+        # excel_path = os.path.join(excel_save_folder, + '.xlsx')
+        if not flag:
+            img = cv2.imread(image_file)
+        if img is None:
+            logger.info("error in loading image:{}".format(image_file))
+            continue
+        starttime = time.time()
+        res = text_sys(img)
+
+        for region in res:
+            if region['label'] == 'table':
+                # x1, y1, x2, y2 = region['bbox']
+                excel_path = os.path.join(excel_save_folder, '{}_{}.xlsx'.format(imgname,region['bbox']))
+                to_excel(region['res'],excel_path)
+        logger.info(res)
+        elapse = time.time() - starttime
+        logger.info("Predict time : {:.3f}s".format(elapse))
+
+
+if __name__ == "__main__":
+    args = parse_args()
+    if args.use_mp:
+        p_list = []
+        total_process_num = args.total_process_num
+        for process_id in range(total_process_num):
+            cmd = [sys.executable, "-u"] + sys.argv + [
+                "--process_id={}".format(process_id),
+                "--use_mp={}".format(False)
+            ]
+            p = subprocess.Popen(cmd, stdout=sys.stdout, stderr=sys.stdout)
+            p_list.append(p)
+        for p in p_list:
+            p.wait()
+    else:
+        main(args)

ppstructure/table/__init__.py

+# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

ppstructure/table/eval_table.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import os
+import sys
+__dir__ = os.path.dirname(os.path.abspath(__file__))
+sys.path.append(__dir__)
+sys.path.append(os.path.abspath(os.path.join(__dir__, '..')))
+
+import cv2
+import json
+from tqdm import tqdm
+from ppstructure.table.table_metric import TEDS
+from ppstructure.table.predict_table import TableSystem, utility
+
+
+def main(gt_path, img_root, args):
+    teds = TEDS(n_jobs=16)
+
+    text_sys = TableSystem(args)
+    jsons_gt = json.load(open(gt_path))  # gt
+    pred_htmls = []
+    gt_htmls = []
+    for img_name in tqdm(jsons_gt):
+        if img_name != 'PMC1064865_002_00.png':
+            continue
+        # 读取信息
+        img = cv2.imread(os.path.join(img_root,img_name))
+        pred_html = text_sys(img)
+        pred_htmls.append(pred_html)
+
+        gt_structures, gt_bboxes, gt_contents, contents_with_block = jsons_gt[img_name]
+        gt_html, gt = get_gt_html(gt_structures, contents_with_block)  # 获取HTMLgt
+        gt_htmls.append(gt_html)
+    scores = teds.batch_evaluate_html(gt_htmls, pred_htmls)  # 计算teds
+    print('teds:', sum(scores) / len(scores))
+
+
+def get_gt_html(gt_structures, contents_with_block):
+    end_html = []
+    td_index = 0
+    for tag in gt_structures:
+        if '</td>' in tag:
+            if contents_with_block[td_index] != []:
+                end_html.extend(contents_with_block[td_index])
+            end_html.append(tag)
+            td_index += 1
+        else:
+            end_html.append(tag)
+    return ''.join(end_html), end_html
+
+
+if __name__ == '__main__':
+    args = utility.parse_args()
+    gt_path = 'table/match_code/f_gt_bbox.json'
+    img_root = 'table/imgs'
+    main(gt_path,img_root, args)

ppstructure/table/predict_structure.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import os
+import sys
+
+__dir__ = os.path.dirname(os.path.abspath(__file__))
+sys.path.append(__dir__)
+sys.path.append(os.path.abspath(os.path.join(__dir__, '../..')))
+
+os.environ["FLAGS_allocator_strategy"] = 'auto_growth'
+
+import cv2
+import numpy as np
+import math
+import time
+import traceback
+import paddle
+
+import tools.infer.utility as utility
+from ppocr.data import create_operators, transform
+from ppocr.postprocess import build_post_process
+from ppocr.utils.logging import get_logger
+from ppocr.utils.utility import get_image_file_list, check_and_read_gif
+
+logger = get_logger()
+
+
+class TableStructurer(object):
+    def __init__(self, args):
+        pre_process_list = [{
+            'ResizeTableImage': {
+                'max_len': args.table_max_len
+            }
+        }, {
+            'NormalizeImage': {
+                'std': [0.229, 0.224, 0.225],
+                'mean': [0.485, 0.456, 0.406],
+                'scale': '1./255.',
+                'order': 'hwc'
+            }
+        }, {
+            'PaddingTableImage': None
+        }, {
+            'ToCHWImage': None
+        }, {
+            'KeepKeys': {
+                'keep_keys': ['image']
+            }
+        }]
+        postprocess_params = {
+            'name': 'TableLabelDecode',
+            "character_type": args.table_char_type,
+            "character_dict_path": args.table_char_dict_path,
+            "max_text_length": args.table_max_text_length,
+            "max_elem_length": args.table_max_elem_length,
+            "max_cell_num": args.table_max_cell_num
+        }
+
+        self.preprocess_op = create_operators(pre_process_list)
+        self.postprocess_op = build_post_process(postprocess_params)
+        self.predictor, self.input_tensor, self.output_tensors = \
+            utility.create_predictor(args, 'table', logger)
+
+    def __call__(self, img):
+        ori_im = img.copy()
+        data = {'image': img}
+        data = transform(data, self.preprocess_op)
+        img = data[0]
+        if img is None:
+            return None, 0
+        img = np.expand_dims(img, axis=0)
+        img = img.copy()
+        starttime = time.time()
+
+        self.input_tensor.copy_from_cpu(img)
+        self.predictor.run()
+        outputs = []
+        for output_tensor in self.output_tensors:
+            output = output_tensor.copy_to_cpu()
+            outputs.append(output)
+
+        preds = {}
+        preds['structure_probs'] = outputs[1]
+        preds['loc_preds'] = outputs[0]
+
+        post_result = self.postprocess_op(preds)
+
+        structure_str_list = post_result['structure_str_list']
+        res_loc = post_result['res_loc']
+        imgh, imgw = ori_im.shape[0:2]
+        res_loc_final = []
+        for rno in range(len(res_loc[0])):
+            x0, y0, x1, y1 = res_loc[0][rno]
+            left = max(int(imgw * x0), 0)
+            top = max(int(imgh * y0), 0)
+            right = min(int(imgw * x1), imgw - 1)
+            bottom = min(int(imgh * y1), imgh - 1)
+            res_loc_final.append([left, top, right, bottom])
+
+        structure_str_list = structure_str_list[0][:-1]
+        structure_str_list = ['<html>', '<body>', '<table>'] + structure_str_list + ['</table>', '</body>', '</html>']
+
+        elapse = time.time() - starttime
+        return (structure_str_list, res_loc_final), elapse
+
+
+def main(args):
+    image_file_list = get_image_file_list(args.image_dir)
+    table_structurer = TableStructurer(args)
+    count = 0
+    total_time = 0
+    for image_file in image_file_list:
+        img, flag = check_and_read_gif(image_file)
+        if not flag:
+            img = cv2.imread(image_file)
+        if img is None:
+            logger.info("error in loading image:{}".format(image_file))
+            continue
+        structure_res, elapse = table_structurer(img)
+
+        logger.info("result: {}".format(structure_res))
+
+        if count > 0:
+            total_time += elapse
+        count += 1
+        logger.info("Predict time of {}: {}".format(image_file, elapse))
+
+
+if __name__ == "__main__":
+    main(utility.parse_args())

ppstructure/table/predict_table.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import sys
+import subprocess
+
+__dir__ = os.path.dirname(os.path.abspath(__file__))
+sys.path.append(__dir__)
+sys.path.append(os.path.abspath(os.path.join(__dir__, '../..')))
+
+os.environ["FLAGS_allocator_strategy"] = 'auto_growth'
+import cv2
+import copy
+import numpy as np
+import time
+import tools.infer.utility as utility
+import tools.infer.predict_rec as predict_rec
+import tools.infer.predict_det as predict_det
+import ppstructure.table.predict_structure as predict_strture
+from ppocr.utils.utility import get_image_file_list, check_and_read_gif
+from ppocr.utils.logging import get_logger
+from ppocr.utils.table_utils.matcher import distance, compute_iou
+
+logger = get_logger()
+
+
+def expand(pix, det_box, shape):
+    x0, y0, x1, y1 = det_box
+    #     print(shape)
+    h, w, c = shape
+    tmp_x0 = x0 - pix
+    tmp_x1 = x1 + pix
+    tmp_y0 = y0 - pix
+    tmp_y1 = y1 + pix
+    x0_ = tmp_x0 if tmp_x0 >= 0 else 0
+    x1_ = tmp_x1 if tmp_x1 <= w else w
+    y0_ = tmp_y0 if tmp_y0 >= 0 else 0
+    y1_ = tmp_y1 if tmp_y1 <= h else h
+    return x0_, y0_, x1_, y1_
+
+
+class TableSystem(object):
+    def __init__(self, args):
+        self.text_detector = predict_det.TextDetector(args)
+        self.text_recognizer = predict_rec.TextRecognizer(args)
+        self.table_structurer = predict_strture.TableStructurer(args)
+        self.use_angle_cls = args.use_angle_cls
+        self.drop_score = args.drop_score
+
+    def __call__(self, img):
+        ori_im = img.copy()
+        structure_res, elapse = self.table_structurer(copy.deepcopy(img))
+        dt_boxes, elapse = self.text_detector(copy.deepcopy(img))
+        dt_boxes = sorted_boxes(dt_boxes)
+
+        r_boxes = []
+        for box in dt_boxes:
+            x_min = box[:, 0].min() - 1
+            x_max = box[:, 0].max() + 1
+            y_min = box[:, 1].min() - 1
+            y_max = box[:, 1].max() + 1
+            box = [x_min, y_min, x_max, y_max]
+            r_boxes.append(box)
+        dt_boxes = np.array(r_boxes)
+
+        # logger.info("dt_boxes num : {}, elapse : {}".format(
+        #     len(dt_boxes), elapse))
+        if dt_boxes is None:
+            return None, None
+        img_crop_list = []
+
+        for i in range(len(dt_boxes)):
+            det_box = dt_boxes[i]
+            x0, y0, x1, y1 = expand(2, det_box, ori_im.shape)
+            text_rect = ori_im[int(y0):int(y1), int(x0):int(x1), :]
+            img_crop_list.append(text_rect)
+        rec_res, elapse = self.text_recognizer(img_crop_list)
+        # logger.info("rec_res num  : {}, elapse : {}".format(
+        #     len(rec_res), elapse))
+
+        pred_html, pred = self.rebuild_table(structure_res, dt_boxes, rec_res)
+        return pred_html
+
+    def rebuild_table(self, structure_res, dt_boxes, rec_res):
+        pred_structures, pred_bboxes = structure_res
+        matched_index = self.match_result(dt_boxes, pred_bboxes)
+        pred_html, pred = self.get_pred_html(pred_structures, matched_index, rec_res)
+        return pred_html, pred
+
+    def match_result(self, dt_boxes, pred_bboxes):
+        matched = {}
+        for i, gt_box in enumerate(dt_boxes):
+            # gt_box = [np.min(gt_box[:, 0]), np.min(gt_box[:, 1]), np.max(gt_box[:, 0]), np.max(gt_box[:, 1])]
+            distances = []
+            for j, pred_box in enumerate(pred_bboxes):
+                distances.append(
+                    (distance(gt_box, pred_box), 1. - compute_iou(gt_box, pred_box)))  # 获取两两cell之间的L1距离和 1- IOU
+            sorted_distances = distances.copy()
+            # 根据距离和IOU挑选最"近"的cell
+            sorted_distances = sorted(sorted_distances, key=lambda item: (item[1], item[0]))
+            if distances.index(sorted_distances[0]) not in matched.keys():
+                matched[distances.index(sorted_distances[0])] = [i]
+            else:
+                matched[distances.index(sorted_distances[0])].append(i)
+        return matched
+
+    def get_pred_html(self, pred_structures, matched_index, ocr_contents):
+        end_html = []
+        td_index = 0
+        for tag in pred_structures:
+            if '</td>' in tag:
+                if td_index in matched_index.keys():
+                    b_with = False
+                    if '<b>' in ocr_contents[matched_index[td_index][0]] and len(matched_index[td_index]) > 1:
+                        b_with = True
+                        end_html.extend('<b>')
+                    for i, td_index_index in enumerate(matched_index[td_index]):
+                        content = ocr_contents[td_index_index][0]
+                        if len(matched_index[td_index]) > 1:
+                            if len(content) == 0:
+                                continue
+                            if content[0] == ' ':
+                                content = content[1:]
+                            if '<b>' in content:
+                                content = content[3:]
+                            if '</b>' in content:
+                                content = content[:-4]
+                            if len(content) == 0:
+                                continue
+                            if i != len(matched_index[td_index]) - 1 and ' ' != content[-1]:
+                                content += ' '
+                        end_html.extend(content)
+                    if b_with:
+                        end_html.extend('</b>')
+
+                end_html.append(tag)
+                td_index += 1
+            else:
+                end_html.append(tag)
+        return ''.join(end_html), end_html
+
+
+def sorted_boxes(dt_boxes):
+    """
+    Sort text boxes in order from top to bottom, left to right
+    args:
+        dt_boxes(array):detected text boxes with shape [4, 2]
+    return:
+        sorted boxes(array) with shape [4, 2]
+    """
+    num_boxes = dt_boxes.shape[0]
+    sorted_boxes = sorted(dt_boxes, key=lambda x: (x[0][1], x[0][0]))
+    _boxes = list(sorted_boxes)
+
+    for i in range(num_boxes - 1):
+        if abs(_boxes[i + 1][0][1] - _boxes[i][0][1]) < 10 and \
+                (_boxes[i + 1][0][0] < _boxes[i][0][0]):
+            tmp = _boxes[i]
+            _boxes[i] = _boxes[i + 1]
+            _boxes[i + 1] = tmp
+    return _boxes
+
+def to_excel(html_table, excel_path):
+    from tablepyxl import tablepyxl
+    tablepyxl.document_to_xl(html_table, excel_path)
+
+
+def main(args):
+    image_file_list = get_image_file_list(args.image_dir)
+    image_file_list = image_file_list[args.process_id::args.total_process_num]
+    excel_save_folder = 'output/table'
+    os.makedirs(excel_save_folder, exist_ok=True)
+
+    text_sys = TableSystem(args)
+    img_num = len(image_file_list)
+    for i, image_file in enumerate(image_file_list):
+        logger.info("[{}/{}] {}".format(i, img_num, image_file))
+        img, flag = check_and_read_gif(image_file)
+        excel_path = os.path.join(excel_save_folder, os.path.basename(image_file).split('.')[0] + '.xlsx')
+        if not flag:
+            img = cv2.imread(image_file)
+        if img is None:
+            logger.info("error in loading image:{}".format(image_file))
+            continue
+        starttime = time.time()
+        pred_html = text_sys(img)
+
+        to_excel(pred_html, excel_path)
+        logger.info('excel saved to {}'.format(excel_path))
+        logger.info(pred_html)
+        elapse = time.time() - starttime
+        logger.info("Predict time : {:.3f}s".format(elapse))
+
+
+if __name__ == "__main__":
+    args = utility.parse_args()
+    if args.use_mp:
+        p_list = []
+        total_process_num = args.total_process_num
+        for process_id in range(total_process_num):
+            cmd = [sys.executable, "-u"] + sys.argv + [
+                "--process_id={}".format(process_id),
+                "--use_mp={}".format(False)
+            ]
+            p = subprocess.Popen(cmd, stdout=sys.stdout, stderr=sys.stdout)
+            p_list.append(p)
+        for p in p_list:
+            p.wait()
+    else:
+        main(args)

ppstructure/table/table_metric/__init__.py

+# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+__all__ = ['TEDS']
+from .table_metric import TEDS
\ No newline at end of file

ppstructure/table/table_metric/parallel.py

+from tqdm import tqdm
+from concurrent.futures import ProcessPoolExecutor, as_completed
+
+
+def parallel_process(array, function, n_jobs=16, use_kwargs=False, front_num=0):
+    """
+        A parallel version of the map function with a progress bar.
+        Args:
+            array (array-like): An array to iterate over.
+            function (function): A python function to apply to the elements of array
+            n_jobs (int, default=16): The number of cores to use
+            use_kwargs (boolean, default=False): Whether to consider the elements of array as dictionaries of
+                keyword arguments to function
+            front_num (int, default=3): The number of iterations to run serially before kicking off the parallel job.
+                Useful for catching bugs
+        Returns:
+            [function(array[0]), function(array[1]), ...]
+    """
+    # We run the first few iterations serially to catch bugs
+    if front_num > 0:
+        front = [function(**a) if use_kwargs else function(a)
+                 for a in array[:front_num]]
+    else:
+        front = []
+    # If we set n_jobs to 1, just run a list comprehension. This is useful for benchmarking and debugging.
+    if n_jobs == 1:
+        return front + [function(**a) if use_kwargs else function(a) for a in tqdm(array[front_num:])]
+    # Assemble the workers
+    with ProcessPoolExecutor(max_workers=n_jobs) as pool:
+        # Pass the elements of array into function
+        if use_kwargs:
+            futures = [pool.submit(function, **a) for a in array[front_num:]]
+        else:
+            futures = [pool.submit(function, a) for a in array[front_num:]]
+        kwargs = {
+            'total': len(futures),
+            'unit': 'it',
+            'unit_scale': True,
+            'leave': True
+        }
+        # Print out the progress as tasks complete
+        for f in tqdm(as_completed(futures), **kwargs):
+            pass
+    out = []
+    # Get the results from the futures.
+    for i, future in tqdm(enumerate(futures)):
+        try:
+            out.append(future.result())
+        except Exception as e:
+            out.append(e)
+    return front + out

tools/infer/utility.py

@@ -125,6 +125,8 @@ def create_predictor(args, mode, logger):
         model_dir = args.cls_model_dir
     elif mode == 'rec':
         model_dir = args.rec_model_dir
+    elif mode == 'table':
+        model_dir = args.table_model_dir
     else:
         model_dir = args.e2e_model_dir
 
@@ -244,7 +246,8 @@ def create_predictor(args, mode, logger):
 
     config.delete_pass("conv_transpose_eltwiseadd_bn_fuse_pass")
     config.switch_use_feed_fetch_ops(False)
-
+    if mode == 'table':
+        config.switch_ir_optim(False)
     # create predictor
     predictor = inference.create_predictor(config)
     input_names = predictor.get_input_names()