Dear sir,

I just start learning about Neural Network and I found Tensorflow is easy to use.

I learn tensorflow by running example from this tutorial https://github.com/nlintz/TensorFlow-Tutorials and reading this book deeplearningbook.org.

My goal is use Neural network to recognize each letters and number (eg: a,b...x,y,z, A..Z..0...9) . So It means 62 class.

I can segment each letter from the picture by QT.

Now,I confusing about how to OCR by using tensorflow. Cause there are a lot of project about "Handwriting recognition" but a few about "OCR for printed documents". And I a newbie so I really don't know how or where to begin.

Would you mind helping me.

1/ Can I use the same those MNIST classifiers (http://yann.lecun.com/exdb/mnist/) for recognizing English alphabet/letters ? Cause MNIST classifiers recognize digit (0 - 9) so I really don't know It could handle 62 class or not ?

2/ Do you have any documents or papers about "OCR for printed documents". I really lack of knowledge.

3/ I found your project tensorflow-OCR . Would you mind if I learn from your code.

4/ I got errors when i run : ./train_ocr_layer.py

(tensorflow)khoa@khoa:~/tensorflow/tensorflow-ocr$ ./train_ocr_layer.py 
ls: cannot access /tmp/tensorboard_logs/: No such file or directory
Traceback (most recent call last):
  File "./train_ocr_layer.py", line 4, in <module>
    import layer
  File "/home/khoa/tensorflow/tensorflow-ocr/layer/__init__.py", line 1, in <module>
    from net import *
  File "/home/khoa/tensorflow/tensorflow-ocr/layer/net.py", line 8, in <module>
    set_tensorboard_run(auto_increment=True)
  File "/home/khoa/tensorflow/tensorflow-ocr/layer/tensorboard_util.py", line 18, in set_tensorboard_run
    run_nr = get_last_tensorboard_run_nr()
  File "/home/khoa/tensorflow/tensorflow-ocr/layer/tensorboard_util.py", line 8, in get_last_tensorboard_run_nr
    logs=subprocess.check_output(["ls", tensorboard_logs]).split("\n")
  File "/usr/lib/python2.7/subprocess.py", line 573, in check_output
    raise CalledProcessError(retcode, cmd, output=output)
subprocess.CalledProcessError: Command '['ls', '/tmp/tensorboard_logs/']' returned non-zero exit status 2

Thank you and regards, Khoa

lack layer.py

localhost:tensorflow-ocr didi$ ./train_ocr_layer.py Traceback (most recent call last): File "./train_ocr_layer.py", line 3, in import layer ImportError: No module named layer localhost:tensorflow-ocr didi$ pip install layer Collecting layer Could not find a version that satisfies the requirement layer (from versions: ) No matching distribution found for layer

@pannous ,when i train the tensorflow-ocr, I can't find the training data the system input. and when i type the ./train_ocr_layer, there are throwing an error: Exception: BAD FONT: /usr/share/texlive/texmf-dist/fonts/truetype/public/dejavu/DejaVuSansMono-Oblique.ttf.

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I can't find any document or tutorial, and have no clue on how to start with it. Do you guys have any material or wiki page to explain this project?

Thanks very much!

I installed tensorflow 0.11 and PIL 1.17 under ubuntu 16.04, but when i execute the command: python train_ocr_layer.py the result of accuracy and test accuray are below: I don't know the reason,would help me?@pannous

When i try to run mouse_prediction.py i get the following error message:

\AppData\Local\Programs\Python\Python37\lib\site-packages\h5py\_hl\files.py", line 173, in make_fid fid = h5f.open(name, flags, fapl=fapl) File "h5py\_objects.pyx", line 54, in h5py._objects.with_phil.wrapper File "h5py\_objects.pyx", line 55, in h5py._objects.with_phil.wrapper File "h5py\h5f.pyx", line 88, in h5py.h5f.open OSError: Unable to open file (file signature not found)

What did I do : python train_ocr_layer.py After I got ckpt file, I try to transfer it into pb file with code:

import tensorflow as tf
from tensorflow.python.framework import graph_util

def freeze_graph(input_checkpoint, output_graph):
    '''
    :param input_checkpoint:
    :param output_graph: PB模型保存路径
    :return:
    '''
    model_folder = './checkpoints/'
    checkpoint = tf.train.get_checkpoint_state(model_folder) #检查目录下ckpt文件状态是否可用
    input_checkpoint = checkpoint.model_checkpoint_path #得ckpt文件路径

    # 指定输出的节点名称,该节点名称必须是原模型中存在的节点
    output_node_names = "group_deps"
    saver = tf.train.import_meta_graph(input_checkpoint + '.meta', clear_devices=True)
    graph = tf.get_default_graph()  # 获得默认的图
    input_graph_def = graph.as_graph_def()  # 返回一个序列化的图代表当前的图

    with tf.Session() as sess:
        saver.restore(sess, input_checkpoint)  # 恢复图并得到数据
        output_graph_def = graph_util.convert_variables_to_constants(  # 模型持久化，将变量值固定
            sess=sess,
            input_graph_def=input_graph_def,  # 等于:sess.graph_def
            output_node_names=output_node_names.split(","))  # 如果有多个输出节点，以逗号隔开

        with tf.gfile.GFile(output_graph, "wb") as f:  # 保存模型
            f.write(output_graph_def.SerializeToString())  # 序列化输出
        print("%d ops in the final graph." % len(output_graph_def.node))  # 得到当前图有几个操作节点

        for op in graph.get_operations():
             print(op.name, op.values())

if __name__ == '__main__':

    input_checkpoint = './checkpoints/denseConv0.ckpt'
    output_graph = './checkpoints/frozen_graph.pb'
    freeze_graph(input_checkpoint, output_graph)

After I got pb file, I just can`t open it with tensorborad or transfer it into ONNX. I got this error message:

Traceback (most recent call last):
  File "/home/cenhong/.local/lib/python3.6/site-packages/tensorflow/python/framework/importer.py", line 418, in import_graph_def
    graph._c_graph, serialized, options)  # pylint: disable=protected-access
tensorflow.python.framework.errors_impl.InvalidArgumentError: Input 0 of node import/model/batchnorm/AssignMovingAvg was passed float from import/model/batchnorm//moving_mean:0 incompatible with expected float_ref.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/cenhong/.local/bin/tfpb_tensorboard", line 11, in <module>
    load_entry_point('doml', 'console_scripts', 'tfpb_tensorboard')()
  File "/home/cenhong/do-ml/scripts/tfpb_tensorboard.py", line 33, in main
    tfpb_tensorboard(args.input_path, args.log_path, 6006 if args.port is None else args.port)
  File "/home/cenhong/do-ml/scripts/tfpb_tensorboard.py", line 18, in tfpb_tensorboard
    g_in = tf.import_graph_def(graph_def)
  File "/home/cenhong/.local/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
    return func(*args, **kwargs)
  File "/home/cenhong/.local/lib/python3.6/site-packages/tensorflow/python/framework/importer.py", line 422, in import_graph_def
    raise ValueError(str(e))
ValueError: Input 0 of node import/model/batchnorm/AssignMovingAvg was passed float from import/model/batchnorm//moving_mean:0 incompatible with expected float_ref.

Does anyone know how to solve this? Thanks.

Traceback (most recent call last): File "train_letters.py", line 61, in net.train(data=data, dropout=.6, display_step=10, test_step=1000) # run resume File "/usr/local/lib/python3.5/dist-packages/layer/net.py", line 438, in train tf.add_check_numerics_ops() File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/numerics.py", line 90, in add_check_numerics_ops raise ValueError("tf.add_check_numerics_ops() is not compatible " ValueError:tf.add_check_numerics_ops() is not compatible with TensorFlow control flow operations such as tf.cond() or tf.while_loop().