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I got a lot of warnings for scikit-image > 0.14
/usr/local/lib/python3.5/dist-packages/skimage/transform/_warps.py:110: UserWarning: Anti-aliasing will be enabled by default in skimage 0.15 to avoid aliasing artifacts when down-sampling images.
warn("Anti-aliasing will be enabled by default in skimage 0.15 to "
better with
pip install scikit-image==0.13.1 (e.g. update requirements.txt)
an example for secret_settings.py (local computer) could be helpful e.g.
mongo_url='127.0.0.1:27017' #: The url of your mongodb with credentials.
db_name='test' #: The database name you are using in the mongodb.
mongo --host 127.0.0.1:27017
crashed with:
1/25 [>.............................] - ETA: 8:27 - loss: 0.6897 - acc: 0.7500/usr/local/lib/python3.5/dist-packages/keras/callbacks.py:97: UserWarning: Method on_batch_begin() is slow compared to the batch update (1.891898). Check your callbacks.
% delta_t_median)
2/25 [=>............................] - ETA: 4:07 - loss: 0.7122 - acc: 0.6250ERROR - UnsharpDetector - Failed after 0:00:24!
Traceback (most recent calls WITHOUT Sacred internals):
multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
File "/usr/lib/python3.5/multiprocessing/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/usr/local/lib/python3.5/dist-packages/keras/utils/data_utils.py", line 390, in get_index
return _SHARED_SEQUENCES[uid][i]
File "UnsharpDetector/TrainingDataGenerator.py", line 44, in getitem
batch_x, batch_y = self.__data_generation(filename_selection)
File "UnsharpDetector/TrainingDataGenerator.py", line 87, in __data_generation
return np.array(batch_x), np.array(batch_y)
ValueError: could not broadcast input array from shape (256,256,3) into shape (256,256)
"""
The above exception was the direct cause of the following exception:
Traceback (most recent calls WITHOUT Sacred internals):
File "/usr/local/lib/python3.5/dist-packages/keras/utils/data_utils.py", line 564, in get
inputs = self.queue.get(block=True).get()
File "/usr/lib/python3.5/multiprocessing/pool.py", line 608, in get
raise self._value
ValueError: could not broadcast input array from shape (256,256,3) into shape (256,256)
The above exception was the direct cause of the following exception:
Traceback (most recent calls WITHOUT Sacred internals):
File "train.py", line 180, in run
train(gui_callback)
File "train.py", line 170, in train
workers=8, max_queue_size=30)
File "/usr/local/lib/python3.5/dist-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/keras/engine/training.py", line 2212, in fit_generator
generator_output = next(output_generator)
File "/usr/local/lib/python3.5/dist-packages/keras/utils/data_utils.py", line 570, in get
six.raise_from(StopIteration(e), e)
File "", line 2, in raise_from
StopIteration: could not broadcast input array from shape (256,256,3) into shape (256,256)
Any suggestions ?
The text was updated successfully, but these errors were encountered:
I got a lot of warnings for scikit-image > 0.14
/usr/local/lib/python3.5/dist-packages/skimage/transform/_warps.py:110: UserWarning: Anti-aliasing will be enabled by default in skimage 0.15 to avoid aliasing artifacts when down-sampling images.
warn("Anti-aliasing will be enabled by default in skimage 0.15 to "
better with
pip install scikit-image==0.13.1 (e.g. update requirements.txt)
an example for secret_settings.py (local computer) could be helpful e.g.
mongo_url='127.0.0.1:27017' #: The url of your mongodb with credentials.
db_name='test' #: The database name you are using in the mongodb.
mongo --host 127.0.0.1:27017
crashed with:
1/25 [>.............................] - ETA: 8:27 - loss: 0.6897 - acc: 0.7500/usr/local/lib/python3.5/dist-packages/keras/callbacks.py:97: UserWarning: Method on_batch_begin() is slow compared to the batch update (1.891898). Check your callbacks.
% delta_t_median)
2/25 [=>............................] - ETA: 4:07 - loss: 0.7122 - acc: 0.6250ERROR - UnsharpDetector - Failed after 0:00:24!
Traceback (most recent calls WITHOUT Sacred internals):
multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
File "/usr/lib/python3.5/multiprocessing/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/usr/local/lib/python3.5/dist-packages/keras/utils/data_utils.py", line 390, in get_index
return _SHARED_SEQUENCES[uid][i]
File "UnsharpDetector/TrainingDataGenerator.py", line 44, in getitem
batch_x, batch_y = self.__data_generation(filename_selection)
File "UnsharpDetector/TrainingDataGenerator.py", line 87, in __data_generation
return np.array(batch_x), np.array(batch_y)
ValueError: could not broadcast input array from shape (256,256,3) into shape (256,256)
"""
The above exception was the direct cause of the following exception:
Traceback (most recent calls WITHOUT Sacred internals):
File "/usr/local/lib/python3.5/dist-packages/keras/utils/data_utils.py", line 564, in get
inputs = self.queue.get(block=True).get()
File "/usr/lib/python3.5/multiprocessing/pool.py", line 608, in get
raise self._value
ValueError: could not broadcast input array from shape (256,256,3) into shape (256,256)
The above exception was the direct cause of the following exception:
Traceback (most recent calls WITHOUT Sacred internals):
File "train.py", line 180, in run
train(gui_callback)
File "train.py", line 170, in train
workers=8, max_queue_size=30)
File "/usr/local/lib/python3.5/dist-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/keras/engine/training.py", line 2212, in fit_generator
generator_output = next(output_generator)
File "/usr/local/lib/python3.5/dist-packages/keras/utils/data_utils.py", line 570, in get
six.raise_from(StopIteration(e), e)
File "", line 2, in raise_from
StopIteration: could not broadcast input array from shape (256,256,3) into shape (256,256)
Any suggestions ?
The text was updated successfully, but these errors were encountered: