Transfer learning example

In [ ]:

    

# 1.- Put the images in some place. One dir for each category
#  bazel build -c opt --copt=-mavx tensorflow/examples/image_retraining:retrain
# 2.- Execute:
# bazel-bin/tensorflow/examples/image_retraining/retrain 
    --image_dir /home/jorge/proyectos/deep_learning/tensorflow/transfer_learning_example/flower_photos  
    --output_graph /home/jorge/proyectos/deep_learning/tensorflow/transfer_learning_example/output_graph.pb 
    --output_labels /home/jorge/proyectos/deep_learning/tensorflow/transfer_learning_example/output_labels.txt 
    --bottleneck_dir /home/jorge/proyectos/deep_learning/tensorflow/transfer_learning_example/bottleneck

    
Other options


    

In [1]:

    

import numpy as np
import tensorflow as tf

path= '/home/jorge/proyectos/deep_learning/tensorflow/transfer_learning_example/'

imagePath = path + 'flower_photos/tulips/14866400927_3a59899df3_m.jpg'
modelFullPath = path + 'output_graph.pb'
labelsFullPath = path + 'output_labels.txt'


    

In [2]:

    

def create_graph():
    """Creates a graph from saved GraphDef file and returns a saver."""
    # Creates graph from saved graph_def.pb.
    with tf.gfile.FastGFile(modelFullPath, 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        _ = tf.import_graph_def(graph_def, name='')
        
def run_inference_on_image():
    answer = None

    if not tf.gfile.Exists(imagePath):
        tf.logging.fatal('File does not exist %s', imagePath)
        return answer

    image_data = tf.gfile.FastGFile(imagePath, 'rb').read()

    # Creates graph from saved GraphDef.
    create_graph()

    with tf.Session() as sess:

        softmax_tensor = sess.graph.get_tensor_by_name('final_result:0')
        predictions = sess.run(softmax_tensor,
                               {'DecodeJpeg/contents:0': image_data})
        predictions = np.squeeze(predictions)

        top_k = predictions.argsort()[-5:][::-1]  # Getting top 5 predictions
        f = open(labelsFullPath, 'rb')
        lines = f.readlines()
        labels = [str(w).replace("\n", "") for w in lines]
        for node_id in top_k:
            human_string = labels[node_id]
            score = predictions[node_id]
            print('%s (score = %.5f)' % (human_string, score))

        answer = labels[top_k[0]]
        return answer


    

In [3]:

    

run_inference_on_image()


    

    





InternalErrorTraceback (most recent call last)
<ipython-input-3-c3814544f0d6> in <module>()
----> 1 run_inference_on_image()

<ipython-input-2-928ec94ef1e4> in run_inference_on_image()
     23         softmax_tensor = sess.graph.get_tensor_by_name('final_result:0')
     24         predictions = sess.run(softmax_tensor,
---> 25                                {'DecodeJpeg/contents:0': image_data})
     26         predictions = np.squeeze(predictions)
     27 

/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in run(self, fetches, feed_dict, options, run_metadata)
    380     try:
    381       result = self._run(None, fetches, feed_dict, options_ptr,
--> 382                          run_metadata_ptr)
    383       if run_metadata:
    384         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _run(self, handle, fetches, feed_dict, options, run_metadata)
    653     movers = self._update_with_movers(feed_dict_string, feed_map)
    654     results = self._do_run(handle, target_list, unique_fetches,
--> 655                            feed_dict_string, options, run_metadata)
    656 
    657     # User may have fetched the same tensor multiple times, but we

/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
    721     if handle is None:
    722       return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
--> 723                            target_list, options, run_metadata)
    724     else:
    725       return self._do_call(_prun_fn, self._session, handle, feed_dict,

/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _do_call(self, fn, *args)
    741         except KeyError:
    742           pass
--> 743       raise type(e)(node_def, op, message)
    744 
    745   def _extend_graph(self):

InternalError: Dst tensor is not initialized.
	 [[Node: mixed_9/tower/mixed/conv_1/batchnorm/beta = Const[dtype=DT_FLOAT, value=Tensor<type: float shape: [384] values: -1.73975 -1.3261451 -1.4997137...>, _device="/job:localhost/replica:0/task:0/gpu:0"]()]]
Caused by op u'mixed_9/tower/mixed/conv_1/batchnorm/beta', defined at:
  File "/usr/lib/python2.7/runpy.py", line 162, in _run_module_as_main
    "__main__", fname, loader, pkg_name)
  File "/usr/lib/python2.7/runpy.py", line 72, in _run_code
    exec code in run_globals
  File "/usr/local/lib/python2.7/dist-packages/ipykernel/__main__.py", line 3, in <module>
    app.launch_new_instance()
  File "/usr/local/lib/python2.7/dist-packages/traitlets/config/application.py", line 596, in launch_instance
    app.start()
  File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelapp.py", line 442, in start
    ioloop.IOLoop.instance().start()
  File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/ioloop.py", line 162, in start
    super(ZMQIOLoop, self).start()
  File "/usr/local/lib/python2.7/dist-packages/tornado/ioloop.py", line 883, in start
    handler_func(fd_obj, events)
  File "/usr/local/lib/python2.7/dist-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 276, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
    handler(stream, idents, msg)
  File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 391, in execute_request
    user_expressions, allow_stdin)
  File "/usr/local/lib/python2.7/dist-packages/ipykernel/ipkernel.py", line 199, in do_execute
    shell.run_cell(code, store_history=store_history, silent=silent)
  File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2723, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2831, in run_ast_nodes
    if self.run_code(code, result):
  File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-3-c3814544f0d6>", line 1, in <module>
    run_inference_on_image()
  File "<ipython-input-2-928ec94ef1e4>", line 19, in run_inference_on_image
    create_graph()
  File "<ipython-input-2-928ec94ef1e4>", line 7, in create_graph
    _ = tf.import_graph_def(graph_def, name='')
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/importer.py", line 274, in import_graph_def
    op_def=op_def)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2297, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1231, in __init__
    self._traceback = _extract_stack()

In [ ]:

    




    

In [ ]:

    




    

In [ ]: