synckey / tensorflow_lstm_ctc_ocr

CTC + Tensorflow Example for ASR

LSTM + CTC + Tensorflow Example

This is a demo using lstm and ctc to recognize a picture of a series numbers with blanks all at once. The code is compatible with Python3.

For example: given the piture below the model would give result 73791096754314441539.

Installation

# on mac
pip install pillow
pip install opencv-python
brew install cmake
brew tap homebrew/science
brew install opencv
sh ./prepare_train_data.sh

# on ubuntu
pip intall pillow
pip install opencv-python
pip install tensorflow-gpu

The prepare_train_data.sh script would download the SUN database and extract the pitures to bgs dir. Then you can run python gen.py to generate test and train dir.

When the train and test data set are ready you can start the train process by nohup python lstm_and_ctc_ocr_train.py .

Requirements

• Python 2.7+ / Python 3.5+
• Tensorflow 1.0+

License

This project is licensed under the terms of the MIT license.

See README for more information.

tensorflow_lstm_ctc_ocr's Issues

Clarification about input and output.

Here we have some shape OUTPUT_SHAPE = (64, 256) what it represent?
https://github.com/synckey/tensorflow_lstm_ctc_ocr/blob/master/common.py#L45
Seems also used here, but what is 32 and 8 ?
https://github.com/synckey/tensorflow_lstm_ctc_ocr/blob/master/model.py#L66

Why pooling here is not 2x2 ?
https://github.com/synckey/tensorflow_lstm_ctc_ocr/blob/master/model.py#L56

So what should be input of model, output of convolutional part - input of RNN part and what is output of full model?

./detect error

when i run detect.py i get this
sparse_tensor = SparseTensorValue(indices=array([], shape=(0, 2), dtype=int64), values=array([], dtype=int64), dense_shape=array([640, 0]))
decoded_indexes = [[]]
('len(original_list)', 640, 'len(detected_list)', 1, " test and detect length desn't match")
None

someone can help me?

Add readme to tell the user how to use it

Add readme to tell the user how to get it run.

error in running detect.py

Hi @synckey

I have an error will running the detect file , looks like error related about initializing variable in the model

Restore from models\ocr.model-103000
Traceback (most recent call last):
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1139, in _do_call
    return fn(*args)
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1121, in _run_fn
    status, run_metadata)
  File "C:\Users\ososanny\Anaconda3\lib\contextlib.py", line 88, in __exit__
    next(self.gen)
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 466, in raise_exception_on_not_ok_status
    pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [5,5,48,64] rhs shape= [48]
         [[Node: save/Assign_2 = Assign[T=DT_FLOAT, _class=["loc:@Variable_2"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/cpu:0"](Variable_2, save/RestoreV2_2)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "detect.py", line 63, in <module>
    print(detect(test_inputs, test_targets, test_seq_len))
  File "detect.py", line 29, in detect
    saver.restore(sess, model_path)
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 1548, in restore
    {self.saver_def.filename_tensor_name: save_path})
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 789, in run
    run_metadata_ptr)
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 997, in _run
    feed_dict_string, options, run_metadata)
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1132, in _do_run
    target_list, options, run_metadata)
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1152, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [5,5,48,64] rhs shape= [48]
         [[Node: save/Assign_2 = Assign[T=DT_FLOAT, _class=["loc:@Variable_2"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/cpu:0"](Variable_2, save/RestoreV2_2)]]

Caused by op 'save/Assign_2', defined at:
  File "detect.py", line 63, in <module>
    print(detect(test_inputs, test_targets, test_seq_len))
  File "detect.py", line 23, in detect
    saver = tf.train.Saver()
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 1139, in __init__
    self.build()
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 1170, in build
    restore_sequentially=self._restore_sequentially)
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 691, in build
    restore_sequentially, reshape)
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 419, in _AddRestoreOps
    assign_ops.append(saveable.restore(tensors, shapes))
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 155, in restore
    self.op.get_shape().is_fully_defined())
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\ops\state_ops.py", line 271, in assign
    validate_shape=validate_shape)
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_state_ops.py", line 45, in assign
    use_locking=use_locking, name=name)
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 767, in apply_op
    op_def=op_def)
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 2506, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "C:\Users\ososanny\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 1269, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [5,5,48,64] rhs shape= [48]
         [[Node: save/Assign_2 = Assign[T=DT_FLOAT, _class=["loc:@Variable_2"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/cpu:0"](Variable_2, save/RestoreV2_2)]]

Any Help

代码训练一直不收敛

请问作者有测试过加了空格的代码吗？我训练过后loss一直22左右降不下去，而且测试正确率为零，不知道是什么原因，麻烦解答一下，谢谢！

Remove the background of the number

Unlike the plates, bank cards are not surrounded by white background.

ALPR - Paid Support

Can anybody help me with modifications required for 6-8 chars PL plates? It is urgent; please touch me.

the different between crnn+ctc and lstm ctc

hi, i want to konw the pytorch code ctpn+crnn+ctc is same to you tensorflow_lstm_ctc_ocr code? i want do chinese recongition , can you tell me you code will do well in chinese? thanks.

InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [5,5,1,48] rhs shape= []

python3 detect.py

38
loading test
(256, 64)
2018-06-19 08:52:31.041195: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1322, in _do_call
return fn(*args)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1307, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1409, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [5,5,1,48] rhs shape= []
[[Node: save/Assign = Assign[T=DT_FLOAT, _class=["loc:@variable"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](Variable, save/RestoreV2)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "detect.py", line 59, in
print(detect(test_inputs, test_targets, test_seq_len))
File "detect.py", line 24, in detect
saver.restore(sess,model_file)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1802, in restore
{self.saver_def.filename_tensor_name: save_path})
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 900, in run
run_metadata_ptr)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1135, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1316, in _do_run
run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1335, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [5,5,1,48] rhs shape= []
[[Node: save/Assign = Assign[T=DT_FLOAT, _class=["loc:@variable"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](Variable, save/RestoreV2)]]

Caused by op 'save/Assign', defined at:
File "detect.py", line 59, in
print(detect(test_inputs, test_targets, test_seq_len))
File "detect.py", line 20, in detect
saver = tf.train.Saver()
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1338, in init
self.build()
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1347, in build
self._build(self._filename, build_save=True, build_restore=True)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1384, in _build
build_save=build_save, build_restore=build_restore)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 835, in _build_internal
restore_sequentially, reshape)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 494, in _AddRestoreOps
assign_ops.append(saveable.restore(saveable_tensors, shapes))
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 185, in restore
self.op.get_shape().is_fully_defined())
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/state_ops.py", line 283, in assign
validate_shape=validate_shape)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_state_ops.py", line 60, in assign
use_locking=use_locking, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 3392, in create_op
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1718, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [5,5,1,48] rhs shape= []
[[Node: save/Assign = Assign[T=DT_FLOAT, _class=["loc:@variable"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](Variable, save/RestoreV2)]]

程序使用

您好，请问您这个代码是使用gen.py来生成验证码，然后在使用lstm_and_ctc_ocr_train.py来训练吗？ 我运行gen.py 出错。
libdc1394 error: Failed to initialize libdc1394
12
Traceback (most recent call last):
File "gen.py", line 293, in
for img_idx, (im, c, p) in enumerate(im_gen):
File "gen.py", line 283, in generate_ims
yield generate_im(random.choice(char_ims), num_bg_images)
File "gen.py", line 243, in generate_im
bg = generate_bg(num_bg_images)
File "gen.py", line 228, in generate_bg
fname = "bgs/{:08d}.jpg".format(random.randint(0, num_bg_images - 1))
File "/usr/lib/python2.7/random.py", line 240, in randint
return self.randrange(a, b+1)
File "/usr/lib/python2.7/random.py", line 216, in randrange
raise ValueError, "empty range for randrange() (%d,%d, %d)" % (istart, istop, width)
ValueError: empty range for randrange() (0,-2, -2)
这个bgs目录如何使用呢？ 可不可以在readme.md中加入一些使用须知....谢谢您。

IndexError: string index out of range

in lstm_and_ctc_ocr_train.py . at 99 Step always below error. Any idea ?

Step: 99 , batch seconds: 0.320336818695
get data time 0.00392603874207
sparse_tensor = (array([[ 0, 0],
[ 0, 1],
[ 0, 2],
...,
[223, 13],
[223, 14],
[223, 15]]), array([6, 3, 7, ..., 7, 4, 1], dtype=int32), array([224, 20]))
decoded_indexes = [[0, 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, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479], [480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499], [500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519], [520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535], [536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551], [552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567], [568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583], [584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603], [604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623], [624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643], [644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663], [664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679], [680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695], [696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715], [716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735], [736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751], [752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767], [768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783], [784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799], [800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819], [820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839], [840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855], [856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871], [872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887], [888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907], [908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923], [924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943], [944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959], [960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979], [980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999], [1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019], [1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039], [1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055], [1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075], [1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091], [1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111], [1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131], [1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147], [1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167], [1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187], [1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203], [1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223], [1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239], [1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259], [1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275], [1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291], [1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311], [1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 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3605, 3606, 3607], [3608, 3609, 3610, 3611, 3612, 3613, 3614, 3615, 3616, 3617, 3618, 3619, 3620, 3621, 3622, 3623], [3624, 3625, 3626, 3627, 3628, 3629, 3630, 3631, 3632, 3633, 3634, 3635, 3636, 3637, 3638, 3639, 3640, 3641, 3642, 3643], [3644, 3645, 3646, 3647, 3648, 3649, 3650, 3651, 3652, 3653, 3654, 3655, 3656, 3657, 3658, 3659, 3660, 3661, 3662, 3663], [3664, 3665, 3666, 3667, 3668, 3669, 3670, 3671, 3672, 3673, 3674, 3675, 3676, 3677, 3678, 3679], [3680, 3681, 3682, 3683, 3684, 3685, 3686, 3687, 3688, 3689, 3690, 3691, 3692, 3693, 3694, 3695], [3696, 3697, 3698, 3699, 3700, 3701, 3702, 3703, 3704, 3705, 3706, 3707, 3708, 3709, 3710, 3711, 3712, 3713, 3714, 3715], [3716, 3717, 3718, 3719, 3720, 3721, 3722, 3723, 3724, 3725, 3726, 3727, 3728, 3729, 3730, 3731], [3732, 3733, 3734, 3735, 3736, 3737, 3738, 3739, 3740, 3741, 3742, 3743, 3744, 3745, 3746, 3747, 3748, 3749, 3750, 3751], [3752, 3753, 3754, 3755, 3756, 3757, 3758, 3759, 3760, 3761, 3762, 3763, 3764, 3765, 3766, 3767], [3768, 3769, 3770, 3771, 3772, 3773, 3774, 3775, 3776, 3777, 3778, 3779, 3780, 3781, 3782, 3783], [3784, 3785, 3786, 3787, 3788, 3789, 3790, 3791, 3792, 3793, 3794, 3795, 3796, 3797, 3798, 3799, 3800, 3801, 3802, 3803], [3804, 3805, 3806, 3807, 3808, 3809, 3810, 3811, 3812, 3813, 3814, 3815, 3816, 3817, 3818, 3819, 3820, 3821, 3822, 3823], [3824, 3825, 3826, 3827, 3828, 3829, 3830, 3831, 3832, 3833, 3834, 3835, 3836, 3837, 3838, 3839, 3840, 3841, 3842, 3843], [3844, 3845, 3846, 3847, 3848, 3849, 3850, 3851, 3852, 3853, 3854, 3855, 3856, 3857, 3858, 3859, 3860, 3861, 3862, 3863], [3864, 3865, 3866, 3867, 3868, 3869, 3870, 3871, 3872, 3873, 3874, 3875, 3876, 3877, 3878, 3879, 3880, 3881, 3882, 3883], [3884, 3885, 3886, 3887, 3888, 3889, 3890, 3891, 3892, 3893, 3894, 3895, 3896, 3897, 3898, 3899, 3900, 3901, 3902, 3903], [3904, 3905, 3906, 3907, 3908, 3909, 3910, 3911, 3912, 3913, 3914, 3915, 3916, 3917, 3918, 3919], [3920, 3921, 3922, 3923, 3924, 3925, 3926, 3927, 3928, 3929, 3930, 3931, 3932, 3933, 3934, 3935], [3936, 3937, 3938, 3939, 3940, 3941, 3942, 3943, 3944, 3945, 3946, 3947, 3948, 3949, 3950, 3951], [3952, 3953, 3954, 3955, 3956, 3957, 3958, 3959, 3960, 3961, 3962, 3963, 3964, 3965, 3966, 3967], [3968, 3969, 3970, 3971, 3972, 3973, 3974, 3975, 3976, 3977, 3978, 3979, 3980, 3981, 3982, 3983], [3984, 3985, 3986, 3987, 3988, 3989, 3990, 3991, 3992, 3993, 3994, 3995, 3996, 3997, 3998, 3999], [4000, 4001, 4002, 4003, 4004, 4005, 4006, 4007, 4008, 4009, 4010, 4011, 4012, 4013, 4014, 4015]]
Traceback (most recent call last):
File "/Users/alpullu/Downloads/tensorflow_lstm_ctc_ocr/lstm_and_ctc_ocr_train.py", line 132, in
train()
File "/Users/alpullu/Downloads/tensorflow_lstm_ctc_ocr/lstm_and_ctc_ocr_train.py", line 112, in train
c, steps = do_batch()
File "/Users/alpullu/Downloads/tensorflow_lstm_ctc_ocr/lstm_and_ctc_ocr_train.py", line 90, in do_batch
do_report()
File "/Users/alpullu/Downloads/tensorflow_lstm_ctc_ocr/lstm_and_ctc_ocr_train.py", line 83, in do_report
report_accuracy(dd, test_targets)
File "/Users/alpullu/Downloads/tensorflow_lstm_ctc_ocr/lstm_and_ctc_ocr_train.py", line 35, in report_accuracy
original_list = decode_sparse_tensor(test_targets)
File "/Users/alpullu/Downloads/tensorflow_lstm_ctc_ocr/utils.py", line 128, in decode_sparse_tensor
result.append(decode_a_seq(index, sparse_tensor))
File "/Users/alpullu/Downloads/tensorflow_lstm_ctc_ocr/utils.py", line 101, in decode_a_seq
str = common.DIGITS[spars_tensor[1][m]]
IndexError: string index out of range

Process finished with exit code 1

why num_classes =len(CHARS) + 1 + 1

num_classes = len(CHARS) + 1 + 1 # 10 digits + blank + ctc blank

i read other code ，they set num_classes = len(CHARS) + 1

How do i run detect.py on a random licence plate image

I am trying to build an ALPR for Moroccan licence plates using this code but i can't seem to figure out how to test it on a single image. what is the command parsed in order to apply detect.pt on a random licence plate image?

"detect.py"文件混用空格和Tab缩进

可能导致在不同的环境运行效果不同

i use the brach 20160728_immigrate_to_ocr raise error

Invalid argument: Saw a non-null label (index >= num_classes - 1) following a null label, batch: 0 num_classes: 12 labels: 2,10,5,1

Why in the test part will appear (test and detect length doesn't match) error

hi, @synckey , I run your great program, but I will raise an error like this:

test and detect length desn't match

I was confused.

The actually code is in the lstm_and_ctc_ocr_train.py function report_accuracy()。

TypeError: Expected labels to be a SparseTensor

Hmm, this is quite a peculiar issue. I can't seem to wrap my head around why it's throwing this error:

Traceback (most recent call last):
  File "lstm_and_ctc_ocr_train.py", line 132, in <module>
    train()
  File "lstm_and_ctc_ocr_train.py", line 62, in train
    loss = tf.nn.ctc_loss(targets,logits, seq_len)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/ctc_ops.py", line 133, in ctc_loss
    raise TypeError("Expected labels to be a SparseTensor")
TypeError: Expected labels to be a SparseTensor

Seems to boil down to this line of code:
targets = tf.sparse_placeholder(tf.int32)
Though I can't quite place my finger on what went wrong.

Anyone else?

Fail to train on GPU

Hello,
I use gen.py with white background, not with sun database, to create the data of Chinese character.

And, I have two problems when training on GPU.

First,
The problem of OOM before save the checkpoint.
The size of memory of GPU is 16G.
I change the size of batches (on common.py) to 765, and set the size of test data to 765.
And when training on step 999 (report_step=1000), and then occur the issue of OOM.
There's the error message:

Step: 992 , batch seconds: 1.7767887115478516
Step: 993 , batch seconds: 1.6799790859222412
Step: 994 , batch seconds: 1.777162790298462
Step: 995 , batch seconds: 1.7640042304992676
Step: 996 , batch seconds: 1.6605353355407715
Step: 997 , batch seconds: 1.6975252628326416
Step: 998 , batch seconds: 1.6763508319854736
Step: 999 , batch seconds: 1.955089807510376
2019-06-23 15:12:19.462267: W tensorflow/core/common_runtime/bfc_allocator.cc:273] Allocator (GPU_0_bfc) ran out of memorytrying to allocate 15.32GiB. Current allocation summary follows.
2019-06-23 15:12:19.462428: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (256): Total Chunks: 29, Chunks in use: 29. 7.2KiB allocated for chunks. 7.2KiB in use in bin. 1.8KiB client-requested in use in bin.
2019-06-23 15:12:19.462451: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (512): Total Chunks: 4, Chunks inuse: 4. 2.0KiB allocated for chunks. 2.0KiB in use in bin. 2.0KiB client-requested in use in bin.
2019-06-23 15:12:19.462469: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (1024): Total Chunks: 5, Chunks inuse: 5. 5.2KiB allocated for chunks. 5.2KiB in use in bin. 5.0KiB client-requested in use in bin.
2019-06-23 15:12:19.462488: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (2048): Total Chunks: 7, Chunks inuse: 7. 14.0KiB allocated for chunks. 14.0KiB in use in bin. 14.0KiB client-requested in use in bin.
2019-06-23 15:12:19.462507: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (4096): Total Chunks: 3, Chunks inuse: 3. 14.2KiB allocated for chunks. 14.2KiB in use in bin. 14.1KiB client-requested in use in bin.
2019-06-23 15:12:19.462523: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (8192): Total Chunks: 0, Chunks inuse: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-06-23 15:12:19.462539: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (16384): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-06-23 15:12:19.462554: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (32768): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-06-23 15:12:19.462574: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (65536): Total Chunks: 4, Chunks in use: 4. 329.0KiB allocated for chunks. 329.0KiB in use in bin. 328.0KiB client-requested in use in bin.
2019-06-23 15:12:19.462590: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (131072): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-06-23 15:12:19.462607: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (262144): Total Chunks: 8, Chunks in use: 8. 2.28MiB allocated for chunks. 2.28MiB in use in bin. 2.26MiB client-requested in use in bin.
2019-06-23 15:12:19.462624: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (524288): Total Chunks: 8, Chunks in use: 7. 5.41MiB allocated for chunks. 4.67MiB in use in bin. 4.34MiB client-requested in use in bin.
2019-06-23 15:12:19.462640: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (1048576): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-06-23 15:12:19.462656: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (2097152): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-06-23 15:12:19.462671: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (4194304): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-06-23 15:12:19.462689: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (8388608): Total Chunks: 3, Chunks in use: 2. 33.02MiB allocated for chunks. 23.89MiB in use in bin. 20.50MiB client-requested in use in bin.
2019-06-23 15:12:19.462708: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (16777216): Total Chunks: 1, Chunks in use: 1. 16.00MiB allocated for chunks. 16.00MiB in use in bin. 10.25MiB client-requested in use in bin.
2019-06-23 15:12:19.462726: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (33554432): Total Chunks: 1, Chunks in use: 0. 53.75MiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-06-23 15:12:19.462745: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (67108864): Total Chunks: 4, Chunks in use: 4. 339.63MiB allocated for chunks. 339.63MiB in use in bin. 287.62MiB client-requested in use in bin.
2019-06-23 15:12:19.462762: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (134217728): Total Chunks: 1, Chunks in use: 0. 190.16MiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-06-23 15:12:19.462779: I tensorflow/core/common_runtime/bfc_allocator.cc:627] Bin (268435456): Total Chunks: 5, Chunks in use: 0. 13.96GiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-06-23 15:12:19.462796: I tensorflow/core/common_runtime/bfc_allocator.cc:643] Bin for 15.32GiB was 256.00MiB, Chunk State:
2019-06-23 15:12:19.462819: I tensorflow/core/common_runtime/bfc_allocator.cc:649] Size: 416.38MiB | Requested Size: 2.0KiB | in_use: 0, prev: Size: 95.62MiB | Requested Size: 95.62MiB | in_use: 1
2019-06-23 15:12:19.462836: I tensorflow/core/common_runtime/bfc_allocator.cc:649] Size: 1.00GiB | Requested Size: 765.00MiB | in_use: 0
2019-06-23 15:12:19.462851: I tensorflow/core/common_runtime/bfc_allocator.cc:649] Size: 2.00GiB | Requested Size: 382.50MiB | in_use: 0
2019-06-23 15:12:19.462865: I tensorflow/core/common_runtime/bfc_allocator.cc:649] Size: 4.00GiB | Requested Size: 2.98GiB | in_use: 0
2019-06-23 15:12:19.462879: I tensorflow/core/common_runtime/bfc_allocator.cc:649] Size: 6.56GiB | Requested Size: 2.24GiB | in_use: 0
2019-06-23 15:12:19.462894: I tensorflow/core/common_runtime/bfc_allocator.cc:670] Free at 0x7f00f6000000 of size 7039814656
2019-06-23 15:12:19.462906: I tensorflow/core/common_runtime/bfc_allocator.cc:670] Free at 0x7f03afe00000 of size 4294967296
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2019-06-23 15:12:19.462945: I tensorflow/core/common_runtime/bfc_allocator.cc:661] Chunk at 0x7f05b8000000 of size 100270080
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2019-06-23 15:12:19.463867: I tensorflow/core/common_runtime/bfc_allocator.cc:661] Chunk at 0x7f07dceb9e00 of size 512
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2019-06-23 15:12:19.463905: I tensorflow/core/common_runtime/bfc_allocator.cc:676] Summary of in-use Chunks by size:
2019-06-23 15:12:19.463920: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 29 Chunks of size 256 totalling 7.2KiB
2019-06-23 15:12:19.463933: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 4 Chunks of size 512 totalling 2.0KiB
2019-06-23 15:12:19.463946: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 4 Chunks of size 1024 totalling 4.0KiB
2019-06-23 15:12:19.463958: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 1 Chunks of size 1280 totalling 1.2KiB
2019-06-23 15:12:19.463970: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 7 Chunks of size 2048 totalling 14.0KiB
2019-06-23 15:12:19.463983: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 3 Chunks of size 4864 totalling 14.2KiB
2019-06-23 15:12:19.463997: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 4 Chunks of size 84224 totalling 329.0KiB
2019-06-23 15:12:19.464010: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 3 Chunks of size 264192 totalling 774.0KiB
2019-06-23 15:12:19.464024: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 1 Chunks of size 285696 totalling 279.0KiB
2019-06-23 15:12:19.464038: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 3 Chunks of size 307200 totalling 900.0KiB
2019-06-23 15:12:19.464051: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 1 Chunks of size 391680 totalling 382.5KiB
2019-06-23 15:12:19.464065: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 3 Chunks of size 524288 totalling 1.50MiB
2019-06-23 15:12:19.464077: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 3 Chunks of size 819200 totalling 2.34MiB
2019-06-23 15:12:19.464091: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 1 Chunks of size 862208 totalling 842.0KiB
2019-06-23 15:12:19.464104: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 1 Chunks of size 10748416 totalling 10.25MiB
2019-06-23 15:12:19.464117: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 1 Chunks of size 14307328 totalling 13.64MiB
2019-06-23 15:12:19.464131: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 1 Chunks of size 16777216 totalling 16.00MiB
2019-06-23 15:12:19.464144: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 2 Chunks of size 67108864 totalling 128.00MiB
2019-06-23 15:12:19.464157: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 1 Chunks of size 100270080 totalling 95.62MiB
2019-06-23 15:12:19.464171: I tensorflow/core/common_runtime/bfc_allocator.cc:679] 1 Chunks of size 121640192 totalling 116.00MiB
2019-06-23 15:12:19.464185: I tensorflow/core/common_runtime/bfc_allocator.cc:683] Sum Total of in-use chunks: 386.83MiB
2019-06-23 15:12:19.464202: I tensorflow/core/common_runtime/bfc_allocator.cc:685] Stats:
Limit: 15664352461
InUse: 405625856
MaxInUse: 9210262016
NumAllocs: 16693437
MaxAllocSize: 4294967296

2019-06-23 15:12:19.464233: W tensorflow/core/common_runtime/bfc_allocator.cc:277] __________________________________________________________________________________________***_**
2019-06-23 15:12:19.464261: W tensorflow/core/framework/op_kernel.cc:1192] Resource exhausted: OOM when allocating tensor with shape[195840,20993]
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1323, in _do_call
return fn(*args)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1302, in _run_fn
status, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/errors_impl.py", line 473, in exit
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[195840,20993]
[[Node: MatMul_1 = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](Reshape_2, W/read)]]
[[Node: Mean_1/_121 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_310_Mean_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "lstm_and_ctc_ocr_train.py", line 134, in
train()
File "lstm_and_ctc_ocr_train.py", line 115, in train
c, steps = do_batch()
File "lstm_and_ctc_ocr_train.py", line 91, in do_batch
do_report()
File "lstm_and_ctc_ocr_train.py", line 83, in do_report
dd, log_probs, accuracy = session.run([decoded[0], log_prob, acc], test_feed)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 889, in run
run_metadata_ptr)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1120, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1317, in _do_run
options, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1336, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[195840,20993]
[[Node: MatMul_1 = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](Reshape_2, W/read)]]
[[Node: Mean_1/_121 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_310_Mean_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]

Caused by op 'MatMul_1', defined at:
File "lstm_and_ctc_ocr_train.py", line 134, in
train()
File "lstm_and_ctc_ocr_train.py", line 61, in train
logits, inputs, targets, seq_len, W, b = model.get_train_model()
File "/workspace/lustre/tensorflow_lstm_ctc_ocr-master/model.py", line 125, in get_train_model
logits = tf.matmul(outputs, W) + b
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/math_ops.py", line 1891, in matmul
a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_math_ops.py", line 2437, in _mat_mul
name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 2956, in create_op
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1470, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[195840,20993]
[[Node: MatMul_1 = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](Reshape_2, W/read)]]
[[Node: Mean_1/_121 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_310_Mean_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]

Second, then I try with the smaller data same as the author (train: 100*64, test: 100), and the batches=100, report_step=100, then another problem appear:
The process will freeze when step=100=report_step.

Does anyone knows that what happened, and how to fix this?
Or in problem two, I just need to be patient?

Thank you.

decode_a_seq方法出现IndexError异常

这个问题在 #4 后面的回复里有人提到过，不过没有解决。

...
File ".../tensorflow_lstm_ctc_ocr-master/utils.py", line 101, in decode_a_seq
str = common.DIGITS[spars_tensor[1][m]]
IndexError: string index out of range

错误的确存在，101行附件的代码：

def decode_a_seq(indexes, spars_tensor):
    decoded = []
    for m in indexes:
        str = common.DIGITS[spars_tensor[1][m]]
        decoded.append(str)

spars_tensor变量的维度是[200, 20]，传进来的indexes取值远远超过20（观察到的最大index值会到3551），这里估计是有问题的。

简单修改以后可以运行（粗暴的try...expect绕过错误），但结果不太好（也许和这个问题有关系？），使用带底色的训练/验证图，100000迭代结束后最终准确度只有27%。

Test Accuracy: 0.27
Step: 100000 , batch seconds: 2.0177502632141113
Epoch 10000/10000, steps = 100000, train_cost = 1.383, train_ler = 0.000, val_cost = 1.170, val_ler = 0.009, time = 2.491s, learning_rate = 0.00012157658056821674

你好，为什么一开始所有值都一样，然后跑着跑着detected_list就变成空了，这是为什么呢？

训练100步左右，模型的的detected_list变成了空，刚开始是128左右，然后越来越短，最后变成空，然后后边也就一直打印original_list与detected_list不匹配的，这个应该怎么解决呢？

error in running detect.py

@synckey When I trained the model, I wanted to detect the model.But I run detect.py,I have encountered the following error.
I want to know how to solve it. Thank you!

Traceback (most recent call last):
File "E:/download/tensorflow_lstm_ctc_ocr-master/detect.py", line 55, in
test_inputs, test_targets, test_seq_len = utils.get_data_set('small_test')
File "E:\download\tensorflow_lstm_ctc_ocr-master\utils.py", line 79, in get_data_set
inputs, codes = common.unzip(list(common.read_data_for_lstm_ctc(dirname, start_index, end_index)))
File "E:\download\tensorflow_lstm_ctc_ocr-master\common.py", line 145, in unzip
xs, ys = zip(*b)
ValueError: not enough values to unpack (expected 2, got 0)

Is there any benefit using convlutional layers to segment honrizontal picture into chunks and extract feature vectors from pixels before going into lstm_ctc model?

Variable image size?

Does this model support variable input image size or only variable width?
Seems like it can be done via convolutional layers + global average pooling/spartial pyramid pooling, will it work in such setting?

Error when I am running train.py, any ideas ?

Traceback (most recent call last):
File "/train.py", line 133, in
train()
File "/train.py", line 109, in train
(batch + 1) * common.BATCH_SIZE)
File "\utils.py", line 79, in get_data_set
inputs, codes = common.unzip(list(common.read_data_for_lstm_ctc(dirname, start_index, end_index)))
File "\common.py", line 113, in read_data_for_lstm_ctc
if not data_set in dirname:
TypeError: 'in ' requires string as left operand, not dict