emilwallner / coloring-greyscale-images Goto Github PK

env: tensorflow-gpu 1.15.0，keras 2.3.1，cudakit 10.0.130，cudann 7.6.5

when run full version, encountered following problems, try global_variables_initializer, can't resolve:
2020-04-25 20:43:26.316669: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_100.dll
Traceback (most recent call last):
File "D:/work/py/Coloring-greyscale-images/Full-version/full_version.py", line 112, in
model.fit_generator(image_a_b_gen(batch_size), epochs=1, steps_per_epoch=1)
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\site-packages\keras\engine\training.py", line 1732, in fit_generator
initial_epoch=initial_epoch)
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\site-packages\keras\engine\training_generator.py", line 185, in fit_generator
generator_output = next(output_generator)
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\site-packages\keras\utils\data_utils.py", line 742, in get
six.reraise(*sys.exc_info())
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\site-packages\six.py", line 703, in reraise
raise value
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\site-packages\keras\utils\data_utils.py", line 711, in get
inputs = future.get(timeout=30)
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\multiprocessing\pool.py", line 657, in get
raise self._value
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\multiprocessing\pool.py", line 121, in worker
result = (True, func(*args, **kwds))
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\site-packages\keras\utils\data_utils.py", line 650, in next_sample
return six.next(_SHARED_SEQUENCES[uid])
File "D:/work/py/Coloring-greyscale-images/Full-version/full_version.py", line 97, in image_a_b_gen
embed = create_inception_embedding(grayscaled_rgb)
File "D:/work/py/Coloring-greyscale-images/Full-version/full_version.py", line 81, in create_inception_embedding
embed = inception.predict(grayscaled_rgb_resized)
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\site-packages\keras\engine\training.py", line 1462, in predict
callbacks=callbacks)
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\site-packages\keras\engine\training_arrays.py", line 324, in predict_loop
batch_outs = f(ins_batch)
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\site-packages\tensorflow_core\python\keras\backend.py", line 3476, in call
run_metadata=self.run_metadata)
File "D:\ProgramData\Anaconda3\envs\tf1_gpu\lib\site-packages\tensorflow_core\python\client\session.py", line 1472, in call
run_metadata_ptr)
tensorflow.python.framework.errors_impl.FailedPreconditionError: 2 root error(s) found.
(0) Failed precondition: Error while reading resource variable batch_normalization_177/beta from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/batch_normalization_177/beta)
[[{{node batch_normalization_177/cond/ReadVariableOp}}]]
[[predictions/Softmax/_7]]
(1) Failed precondition: Error while reading resource variable batch_normalization_177/beta from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/batch_normalization_177/beta)
[[{{node batch_normalization_177/cond/ReadVariableOp}}]]
0 successful operations.
0 derived errors ignored.

where is the “calc_output_and_feature_size.py”in GAN_version？thank you

Can you help me to fix this problem? I don't know why it occur.

Error :
tensorflow.python.framework.errors_impl.AbortedError: Operation received an exception:Status: 3, message: could not initialize a memory descriptor, in file tensorflow/core/kernels/mkl_concat_op.cc:781

Deatil: :
Using TensorFlow backend.
1.7.0
WARNING:tensorflow:From /root/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/datasets/base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Use the retry module or similar alternatives.
Epoch 1/100
Traceback (most recent call last):
File "/root/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1327, in _do_call
return fn(*args)
File "/root/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1312, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/root/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1420, in _call_tf_sessionrun
status, run_metadata)
File "/root/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py", line 516, in exit
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.AbortedError: Operation received an exception:Status: 3, message: could not initialize a memory descriptor, in file tensorflow/core/kernels/mkl_concat_op.cc:781
[[Node: concatenate_1/concat = _MklConcatV2[N=2, T=DT_FLOAT, Tidx=DT_INT32, _kernel="MklOp", _device="/job:localhost/replica:0/task:0/device:CPU:0"](conv2d_211/Relu, reshape_1/Reshape, concatenate_1/concat/axis, conv2d_211/Relu:1, reshape_1/Reshape:1, DMT/_19)]]

Hey,
I was trying to color the image of women lena which has been used in image processing from the beginning using the full version. All of the result is pretty much bad.
this is the image and ur default images is also there.

outputs

I am not sure what is wrong!
Help me out.

I tried running your colornet_script.py. Like in your example, i tried running it with the same image as training and test data. It runs smoothly, but the output image is grayscale. What might be the cause for that?

ValueError: ('Input data in NumpyArrayIterator should have rank 4. You passed an array with shape', (0,))

X = np.array(X, dtype=float)
ValueError: setting an array element with a sequence on Line 15

Any reason why this would happen

Hi! I'm just curious as to why your model uses a shape 1000 long instead of 1001, as in the paper?

Is there a pre-trained model for this? I want to do transfer learning on my dataset w/o training from scratch.

Calling Model.predict in graph mode is not supported when the Model instance was constructed with eager mode enabled. Please construct your Model instance in graph mode or call Model.predict with eager mode enabled.

Traceback (most recent call last):
File "colorize_base.py", line 308, in
write_log(callback_Full, callback_Full_names, d_loss_fake_full + d_loss_real_full, i)
File "/mnt/Coloring-grey-scale-master/GAN-version/lib/data_utils.py", line 85, in write_log
summary = tf.Summary()
AttributeError: module 'tensorflow' has no attribute 'Summary'

I dont know why. I ran colorize_base.py in Pycharm, it works. But when I run it at a GPU service, this problem came out.
May I ask which version of your tensorflow is?

"generator() takes 5 positional arguments but 6 were given"

I got this error when i run the colorise_base.py in gan version.How colud i resolve this?

I get an attribute error, anyone can help? Thanks.

AttributeError                            Traceback (most recent call last)
<ipython-input-15-218ed4947ab4> in <module>()
      1 # Building the neural network
----> 2 model = Sequential()
      3 model.add(InputLayer(input_shape=(None, None, 1)))
      4 model.add(Conv2D(8, (3, 3), activation='relu', padding='same', strides=2))
      5 model.add(Conv2D(8, (3, 3), activation='relu', padding='same'))

/home/x/.local/lib/python3.7/site-packages/keras/engine/sequential.py in __init__(self, layers, name)
     85 
     86     def __init__(self, layers=None, name=None):
---> 87         super(Sequential, self).__init__(name=name)
     88         self._build_input_shape = None
     89 

/home/x/.local/lib/python3.7/site-packages/keras/legacy/interfaces.py in wrapper(*args, **kwargs)
     89                 warnings.warn('Update your `' + object_name + '` call to the ' +
     90                               'Keras 2 API: ' + signature, stacklevel=2)
---> 91             return func(*args, **kwargs)
     92         wrapper._original_function = func
     93         return wrapper

/home/x/.local/lib/python3.7/site-packages/keras/engine/network.py in __init__(self, *args, **kwargs)
     94         else:
     95             # Subclassed network
---> 96             self._init_subclassed_network(**kwargs)
     97 
     98     def _base_init(self, name=None):

/home/x/.local/lib/python3.7/site-packages/keras/engine/network.py in _init_subclassed_network(self, name)
    292 
    293     def _init_subclassed_network(self, name=None):
--> 294         self._base_init(name=name)
    295         self._is_graph_network = False
    296         self._expects_training_arg = has_arg(self.call, 'training')

/home/x/.local/lib/python3.7/site-packages/keras/engine/network.py in _base_init(self, name)
    107         if not name:
    108             prefix = self.__class__.__name__.lower()
--> 109             name = prefix + '_' + str(K.get_uid(prefix))
    110         self.name = name
    111 

/home/x/.local/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py in get_uid(prefix)
     72     """
     73     global _GRAPH_UID_DICTS
---> 74     graph = tf.get_default_graph()
     75     if graph not in _GRAPH_UID_DICTS:
     76         _GRAPH_UID_DICTS[graph] = defaultdict(int)

AttributeError: module 'tensorflow' has no attribute 'get_default_graph'

It says "cannot pickle generator objects"