Traceback (most recent call last):


 "/usr/lib/python3.5/threading.py", line 914, in _bootstrap_inner

self.run()


 "/usr/lib/python3.5/threading.py", line 862, in run

self._target(*self._args, **self._kwargs)


 "/usr/local/lib/python3.5/dist-packages/keras/engine/training.py", line 612, in data_generator_task

generator_output = next(self._generator)


 "/media/y/2T/wangxingli/TT100K/ssd_keras/data_generator/object_detection_2d_data_generator.py", line 1136, in generate

"must be homogenous in size along all axes.")
data_generator.object_detection_2d_data_generator.DegenerateBatchError: You produced an empty batch. This might be because the images in the batch vary in their size and/or number of channels. Note that after all transformations (if any were given) have been applied to all images in the batch, all images must be homogenous in size along all axes.

Traceback (most recent call last):


 "D:\tools\XX-Net-3.7.9\code\default\python27\1.0\lib\threading.py", line 801, in __bootstrap_inner

self.run()


 "D:\tools\XX-Net-3.7.9\code\default\python27\1.0\lib\threading.py", line 754, in run

self.__target(*self.__args, **self.__kwargs)


 "D:\tools\XX-Net-3.7.9\code\default\gae_proxy\local\google_ip.py", line 652, in scan_ip_worker

xlog.exception("google_ip.runJob fail:%r", e)
AttributeError: 'NoneType' object has no attribute 'exception'
