mjdelta / deeplabv3plus-keras Goto Github PK

Hello, thanks for your code，and I seem to have found a mistake in the part of "ASPP".
the function DepthwiseConv2D( ) ,the "dilation_rate" seems to be 6, 12, 18 , and there are 6, 12, 12 .
I hope you understand my description，my English is not good.

Hi,
Thanks for your work. I get some problems in training process. Could you please release your training code here or give some reference?

i have RGB pictures ,but can not train

model = deeplabv3_plus()
smooth = 1.
model.compile(optimizer=Adam(lr=1e-4), loss=IOU_calc_loss, metrics=[IOU_calc])
history = model.fit(X_train, y_train, batch_size=1, epochs=50, verbose=1, validation_split=0.1, shuffle=False)
what can i do for this?

Train on 81 samples, validate on 9 samples
Epoch 1/50

InvalidArgumentError Traceback (most recent call last)
~\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)
1326 try:
-> 1327 return fn(*args)
1328 except errors.OpError as e:

~\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
1305 feed_dict, fetch_list, target_list,
-> 1306 status, run_metadata)
1307

~\Anaconda3\lib\contextlib.py in exit(self, type, value, traceback)
87 try:
---> 88 next(self.gen)
89 except StopIteration:

~\Anaconda3\lib\site-packages\tensorflow\python\framework\errors_impl.py in raise_exception_on_not_ok_status()
465 compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 466 pywrap_tensorflow.TF_GetCode(status))
467 finally:

InvalidArgumentError: Incompatible shapes: [786432] vs. [5505024]
[[Node: loss_6/bilinear_upsampling_24_loss/mul = Mul[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"](loss_6/bilinear_upsampling_24_loss/Reshape, loss_6/bilinear_upsampling_24_loss/Reshape_1)]]
[[Node: loss_6/mul/_43833 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_79013_loss_6/mul", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]]

During handling of the above exception, another exception occurred:

InvalidArgumentError Traceback (most recent call last)
in ()
----> 1 history = model.fit(X_train, y_train, batch_size=1, epochs=50, verbose=1, validation_split=0.1, shuffle=False)

~\Anaconda3\lib\site-packages\keras\engine\training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)
1655 initial_epoch=initial_epoch,
1656 steps_per_epoch=steps_per_epoch,
-> 1657 validation_steps=validation_steps)
1658
1659 def evaluate(self, x=None, y=None,

~\Anaconda3\lib\site-packages\keras\engine\training.py in _fit_loop(self, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch, steps_per_epoch, validation_steps)
1211 batch_logs['size'] = len(batch_ids)
1212 callbacks.on_batch_begin(batch_index, batch_logs)
-> 1213 outs = f(ins_batch)
1214 if not isinstance(outs, list):
1215 outs = [outs]

~\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py in call(self, inputs)
2355 session = get_session()
2356 updated = session.run(fetches=fetches, feed_dict=feed_dict,
-> 2357 **self.session_kwargs)
2358 return updated[:len(self.outputs)]
2359

~\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata)
893 try:
894 result = self._run(None, fetches, feed_dict, options_ptr,
--> 895 run_metadata_ptr)
896 if run_metadata:
897 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

~\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1122 if final_fetches or final_targets or (handle and feed_dict_tensor):
1123 results = self._do_run(handle, final_targets, final_fetches,
-> 1124 feed_dict_tensor, options, run_metadata)
1125 else:
1126 results = []

~\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1319 if handle is None:
1320 return self._do_call(_run_fn, self._session, feeds, fetches, targets,
-> 1321 options, run_metadata)
1322 else:
1323 return self._do_call(_prun_fn, self._session, handle, feeds, fetches)

~\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)
1338 except KeyError:
1339 pass
-> 1340 raise type(e)(node_def, op, message)
1341
1342 def _extend_graph(self):

InvalidArgumentError: Incompatible shapes: [786432] vs. [5505024]
[[Node: loss_6/bilinear_upsampling_24_loss/mul = Mul[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"](loss_6/bilinear_upsampling_24_loss/Reshape, loss_6/bilinear_upsampling_24_loss/Reshape_1)]]
[[Node: loss_6/mul/_43833 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_79013_loss_6/mul", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]]

Caused by op 'loss_6/bilinear_upsampling_24_loss/mul', defined at:
File "C:\Users\User\Anaconda3\lib\runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "C:\Users\User\Anaconda3\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "C:\Users\User\Anaconda3\lib\site-packages\ipykernel_launcher.py", line 16, in
app.launch_new_instance()
File "C:\Users\User\Anaconda3\lib\site-packages\traitlets\config\application.py", line 658, in launch_instance
app.start()
File "C:\Users\User\Anaconda3\lib\site-packages\ipykernel\kernelapp.py", line 477, in start
ioloop.IOLoop.instance().start()
File "C:\Users\User\Anaconda3\lib\site-packages\zmq\eventloop\ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "C:\Users\User\Anaconda3\lib\site-packages\tornado\ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "C:\Users\User\Anaconda3\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "C:\Users\User\Anaconda3\lib\site-packages\zmq\eventloop\zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "C:\Users\User\Anaconda3\lib\site-packages\zmq\eventloop\zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "C:\Users\User\Anaconda3\lib\site-packages\zmq\eventloop\zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "C:\Users\User\Anaconda3\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "C:\Users\User\Anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "C:\Users\User\Anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 235, in dispatch_shell
handler(stream, idents, msg)
File "C:\Users\User\Anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "C:\Users\User\Anaconda3\lib\site-packages\ipykernel\ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "C:\Users\User\Anaconda3\lib\site-packages\ipykernel\zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "C:\Users\User\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2698, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "C:\Users\User\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2808, in run_ast_nodes
if self.run_code(code, result):
File "C:\Users\User\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2862, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 2, in
model.compile(optimizer=Adam(lr=1e-4), loss=IOU_calc_loss, metrics=[IOU_calc])
File "C:\Users\User\Anaconda3\lib\site-packages\keras\engine\training.py", line 860, in compile
sample_weight, mask)
File "C:\Users\User\Anaconda3\lib\site-packages\keras\engine\training.py", line 459, in weighted
score_array = fn(y_true, y_pred)
File "", line 11, in IOU_calc_loss
return -IOU_calc(y_true, y_pred)
File "", line 5, in IOU_calc
intersection = K.sum(y_true_f * y_pred_f) # 求和
File "C:\Users\User\Anaconda3\lib\site-packages\tensorflow\python\ops\math_ops.py", line 865, in binary_op_wrapper
return func(x, y, name=name)
File "C:\Users\User\Anaconda3\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1088, in _mul_dispatch
return gen_math_ops._mul(x, y, name=name)
File "C:\Users\User\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 1449, in _mul
result = _op_def_lib.apply_op("Mul", x=x, y=y, name=name)
File "C:\Users\User\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 767, in apply_op
op_def=op_def)
File "C:\Users\User\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 2630, in create_op
original_op=self._default_original_op, op_def=op_def)
File "C:\Users\User\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 1204, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

InvalidArgumentError (see above for traceback): Incompatible shapes: [786432] vs. [5505024]
[[Node: loss_6/bilinear_upsampling_24_loss/mul = Mul[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"](loss_6/bilinear_upsampling_24_loss/Reshape, loss_6/bilinear_upsampling_24_loss/Reshape_1)]]
[[Node: loss_6/mul/_43833 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_79013_loss_6/mul", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]]

I'm trying to load the saved model . The model saves ok but when I try to load it with the code:

    custom_objects={"BilinearUpsampling":BilinearUpsampling}
    keras.models.load_model(model_file, custom_objects=custom_objects)

It throws an error TypeError: ('Keyword argument not understood:', 'size')

TypeError                                 Traceback (most recent call last)
<ipython-input-2-919f7be2ba45> in <module>()
----> 1 predict()

<ipython-input-1-657409a5c4ee> in predict(model_path, validation_file, labels, output_dir)
     23             output_dir=config["prediction_dir"]):
     24     tmp = BilinearUpsampling()
---> 25     model = load_old_model(model_path)
     26     validation_file_opened = tables.open_file(validation_file)
     27     n_samples = validation_file_opened.root.data.shape[0]

~/workspace/segmentation/2DSegNet/DeepLab/keras-deeplab-v3-plus/deeplabv3_plus_train.py in load_old_model(model_file)
    240         pass
    241     try:
--> 242         return load_model(model_file, custom_objects=custom_objects)
    243     except ValueError as error:
    244         if "InstanceNormalization" in str(error):

/usr/local/lib/python3.5/dist-packages/keras/models.py in load_model(filepath, custom_objects, compile)
    268             raise ValueError('No model found in config file.')
    269         model_config = json.loads(model_config.decode('utf-8'))
--> 270         model = model_from_config(model_config, custom_objects=custom_objects)
    271 
    272         # set weights

/usr/local/lib/python3.5/dist-packages/keras/models.py in model_from_config(config, custom_objects)
    345                         'Maybe you meant to use '
    346                         '`Sequential.from_config(config)`?')
--> 347     return layer_module.deserialize(config, custom_objects=custom_objects)
    348 
    349 

/usr/local/lib/python3.5/dist-packages/keras/layers/__init__.py in deserialize(config, custom_objects)
     53                                     module_objects=globs,
     54                                     custom_objects=custom_objects,
---> 55                                     printable_module_name='layer')

/usr/local/lib/python3.5/dist-packages/keras/utils/generic_utils.py in deserialize_keras_object(identifier, module_objects, custom_objects, printable_module_name)
    142                 return cls.from_config(config['config'],
    143                                        custom_objects=dict(list(_GLOBAL_CUSTOM_OBJECTS.items()) +
--> 144                                                            list(custom_objects.items())))
    145             with CustomObjectScope(custom_objects):
    146                 return cls.from_config(config['config'])

/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py in from_config(cls, config, custom_objects)
   2523         # First, we create all layers and enqueue nodes to be processed
   2524         for layer_data in config['layers']:
-> 2525             process_layer(layer_data)
   2526         # Then we process nodes in order of layer depth.
   2527         # Nodes that cannot yet be processed (if the inbound node

/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py in process_layer(layer_data)
   2509 
   2510             layer = deserialize_layer(layer_data,
-> 2511                                       custom_objects=custom_objects)
   2512             created_layers[layer_name] = layer
   2513 

/usr/local/lib/python3.5/dist-packages/keras/layers/__init__.py in deserialize(config, custom_objects)
     53                                     module_objects=globs,
     54                                     custom_objects=custom_objects,
---> 55                                     printable_module_name='layer')

/usr/local/lib/python3.5/dist-packages/keras/utils/generic_utils.py in deserialize_keras_object(identifier, module_objects, custom_objects, printable_module_name)
    144                                                            list(custom_objects.items())))
    145             with CustomObjectScope(custom_objects):
--> 146                 return cls.from_config(config['config'])
    147         else:
    148             # Then `cls` may be a function returning a class.

/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py in from_config(cls, config)
   1269             A layer instance.
   1270         """
-> 1271         return cls(**config)
   1272 
   1273     def count_params(self):

~/workspace/segmentation/2DSegNet/DeepLab/keras-deeplab-v3-plus/deeplabv3_plus_model.py in __init__(self, upsampling, data_format, **kwargs)
     12         self.upsampling = conv_utils.normalize_tuple(upsampling, 2, 'size')
     13         self.input_spec = InputSpec(ndim=4)
---> 14         super(BilinearUpsampling, self).__init__(**kwargs)
     15 
     16     def compute_output_shape(self, input_shape):

/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py in __init__(self, **kwargs)
    291         for kwarg in kwargs:
    292             if kwarg not in allowed_kwargs:
--> 293                 raise TypeError('Keyword argument not understood:', kwarg)
    294         name = kwargs.get('name')
    295         if not name:

TypeError: ('Keyword argument not understood:', 'size')