ssd_keras
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Value error. Please suggest what must be done now ?
/usr/local/lib/python2.7/site-packages/tensorflow/python/ops/gradients_impl.py:91: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory.
"Converting sparse IndexedSlices to a dense Tensor of unknown shape. "
Exception in thread Thread-4:
Traceback (most recent call last):
File "/usr/local/Cellar/python/2.7.12_2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/threading.py", line 801, in __bootstrap_inner
self.run()
File "/usr/local/Cellar/python/2.7.12_2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/threading.py", line 754, in run
self.__target(*self.__args, **self.__kwargs)
File "/usr/local/lib/python2.7/site-packages/keras/engine/training.py", line 429, in data_generator_task
generator_output = next(self._generator)
File "
Epoch 1/30
ValueError Traceback (most recent call last)
/usr/local/lib/python2.7/site-packages/keras/engine/training.pyc in fit_generator(self, generator, samples_per_epoch, nb_epoch, verbose, callbacks, validation_data, nb_val_samples, class_weight, max_q_size, nb_worker, pickle_safe, initial_epoch) 1530 '(x, y, sample_weight) ' 1531 'or (x, y). Found: ' + -> 1532 str(generator_output)) 1533 if len(generator_output) == 2: 1534 x, y = generator_output
ValueError: output of generator should be a tuple (x, y, sample_weight) or (x, y). Found: None
@rykov8 Could you list the correct format of input files?
IOError: [Errno 2] No such file or directory: u'../../frames/frame01059.png' You don't have this file on your machine, so the generator fails to produce a sample. Change all the paths in your code to match files you have.
IOError: [Errno 2] No such file or directory: u'../../frames/frame01059.png' You don't have this file on your machine, so the generator fails to produce a sample. Change all the paths in your code to match files you have.
If you are using training data and validation data as a separate file, you must create, "validation_data" as a pickle, "val_path" and add to "gen" instance. I think you must have a prefix path only for the training data.