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Keras ValueError Input Form

I have a problem and a question at the same time. I want to make an image classifier with Keras using Theano as Backend and Sequential.

>>> keras.__version__
'2.0.1'  
>>> theano.__version__
'0.9.0'

My input form: INPUT_SHAPE = (3, 28, 28) #depth, size, size

Let's go to my problem. If I run my script on Windows 7 32 Bit it gives me below error:

ValueError: ('The specified size contains a dimension with value <= 0', (-1024, 512))

If I run it with an input form: INPUT_SHAPE = (28, 28, 3) #size, size, depth


It gives me this error below:

ValueError: Error when checking model input: expected conv2d_1_input to have shape (None, 48, 48, 3) but got array with shape (1000, 3, 48, 48)

If I run the code on Elementary OS 64 bit, it works without issue ( INPUT_SHAPE = (3, 28, 28)

).

My keras.json file for windows:

{
  "backend": "theano",
  "epsilon": 1e-07,
  "floatx": "float32",
  "image_dim_ordering": "tf"
}

So my question is, is there such a big difference between different operating systems or where is my mistake? Just to remind, I used exactly the same code for both systems.

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3 answers


If your problem is still not resolved, try using: from keras import backend as K K.set_image_dim_ordering('th')

This would be fine if you want to use theano backend and must use the first channel config to order image sizes.



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The problem you are having is with the expected ordering of sizes.

  • Tensorflow order (tf): There are expected to be shapes (size_lines, size_columns, channel )
  • Theano ordering (th): Shapes are expected ( channel , size_lines, size_columns)


If you change the order line in your keras.json file to "image_dim_ordering": "th" it should work. (I would bet that in your Elementary OS keras.json).

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To switch to another server, you can change the configuration file located in the folder

  • Linux: $HOME/.keras/keras.json

  • Windows: %USER_PROFILE%/.keras/keras.json

This is the file keras.json

for the backend theano

:

{
    "floatx": "float32",
    "epsilon": 1e-07,
    "backend": "theano",
    "image_data_format": "channels_first"
}

This is the file keras.json

for the tensorflow

backend:

{
    "floatx": "float32",
    "epsilon": 1e-07,
    "backend": "tensorflow",
    "image_data_format": "channels_last"
}

This is what the documentation https://keras.io/backend/ says about the property image_data_format

:

image_data_format

: string

, either "channels_last"

, or "channels_first"

. It specifies which format the Keras data format will be used for. ( keras.backend.image_data_format()

returns it.)

For two-dimensional data (eg, an image), "channels_last"

assumes (rows, cols, channels)

while "channels_first" assumes (channels, rows, cols)

.

For 3D data, "channels_last"

assumes (conv_dim1, conv_dim2, conv_dim3, channels)

but "channels_first"

takes (channels, conv_dim1, conv_dim2, conv_dim3)

.

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