Multiple images for testing

[gaurav16gupta]

Hi,
How can I pass multiple images as batch while testing?
I made these changes in use_dictnet.py line 44, just to check if I can provide multiple images.

def classify_image(self,img):
img = self._preprocess(img)
xtest = zeros((1,2,32,100))
xtest[0,0,:,:] = img
xtest[0,1,:,:] = img
z = self.model.predict_classes(xtest,verbose=0)[0]
return self.output_word[z][0]

I get the following error:

Traceback (most recent call last):
File "use_dictnet.py", line 62, in
print (cnn_model.classify_image(img))
File "use_dictnet.py", line 49, in classify_image
z = self.model.predict_classes(xtest,verbose=0)[0]
File "/home/gaurav/deeplearning/TEXT/reading-text-in-the-wild/DICT2/keras/models.py", line 747, in predict_classes
proba = self.predict(X, batch_size=batch_size, verbose=verbose)
File "/home/gaurav/deeplearning/TEXT/reading-text-in-the-wild/DICT2/keras/models.py", line 716, in predict
return self._predict_loop(self._predict, X, batch_size, verbose)[0]
File "/home/gaurav/deeplearning/TEXT/reading-text-in-the-wild/DICT2/keras/models.py", line 359, in _predict_loop
batch_outs = f(ins_batch)
File "/home/gaurav/deeplearning/TEXT/reading-text-in-the-wild/DICT2/keras/backend/theano_backend.py", line 473, in call
return self.function(*inputs)
File "/usr/local/lib/python2.7/dist-packages/theano/compile/function_module.py", line 898, in call
storage_map=getattr(self.fn, 'storage_map', None))
File "/usr/local/lib/python2.7/dist-packages/theano/gof/link.py", line 325, in raise_with_op
reraise(exc_type, exc_value, exc_trace)
File "/usr/local/lib/python2.7/dist-packages/theano/compile/function_module.py", line 884, in call
self.fn() if output_subset is None else
ValueError: CorrMM images and kernel must have the same stack size

Apply node that caused the error: CorrMM{half, (1, 1), (1, 1)}(<TensorType(float32, 4D)>, Subtensor{::, ::, ::int64, ::int64}.0)
Toposort index: 15
Inputs types: [TensorType(float32, 4D), TensorType(float32, 4D)]
Inputs shapes: [(1, 2, 32, 100), (64, 1, 5, 5)]
Inputs strides: [(25600, 12800, 400, 4), (100, 100, -20, -4)]
Inputs values: ['not shown', 'not shown']
Outputs clients: [[Elemwise{Composite{(i0 * ((i1 + i2) + Abs((i1 + i2))))}}[(0, 1)](TensorConstant{(1, 1, 1, 1) of 0.5}, CorrMM{half, (1, 1), (1, 1)}.0, InplaceDimShuffle{x,0,x,x}.0)]]

Backtrace when the node is created(use Theano flag traceback.limit=N to make it longer):
File "/home/gaurav/deeplearning/TEXT/reading-text-in-the-wild/DICT2/keras/layers/convolutional.py", line 683, in get_output
X = self.get_input(train)
File "/home/gaurav/deeplearning/TEXT/reading-text-in-the-wild/DICT2/keras/layers/core.py", line 241, in get_input
previous_output = self.previous.get_output(train=train)
File "/home/gaurav/deeplearning/TEXT/reading-text-in-the-wild/DICT2/keras/layers/convolutional.py", line 310, in get_output
X = self.get_input(train)
File "/home/gaurav/deeplearning/TEXT/reading-text-in-the-wild/DICT2/keras/layers/core.py", line 241, in get_input
previous_output = self.previous.get_output(train=train)
File "/home/gaurav/deeplearning/TEXT/reading-text-in-the-wild/DICT2/keras/layers/convolutional.py", line 683, in get_output
X = self.get_input(train)
File "/home/gaurav/deeplearning/TEXT/reading-text-in-the-wild/DICT2/keras/layers/core.py", line 241, in get_input
previous_output = self.previous.get_output(train=train)
File "/home/gaurav/deeplearning/TEXT/reading-text-in-the-wild/DICT2/keras/layers/convolutional.py", line 315, in get_output
filter_shape=self.W_shape)
File "/home/gaurav/deeplearning/TEXT/reading-text-in-the-wild/DICT2/keras/backend/theano_backend.py", line 719, in conv2d
filter_shape=filter_shape)