Adapting different testing image shapes?

[terrytykuo]

I got an error below:

Traceback (most recent call last):
File "main.py", line 63, in
m = Model(input=[x, x_maps], output=sam_resnet([x, x_maps]))
File "/Users/Terry/Documents/Memorix/sam-master/models.py", line 140, in sam_resnet
concateneted = merge([att_convlstm, priors1], mode='concat', concat_axis=1)
File "/Users/Terry/anaconda3/envs/python27/lib/python2.7/site-packages/keras/engine/topology.py", line 1528, in merge
name=name)
File "/Users/Terry/anaconda3/envs/python27/lib/python2.7/site-packages/keras/engine/topology.py", line 1186, in init
node_indices, tensor_indices)
File "/Users/Terry/anaconda3/envs/python27/lib/python2.7/site-packages/keras/engine/topology.py", line 1253, in _arguments_validation
'Layer shapes: %s' % (input_shapes))
Exception: "concat" mode can only merge layers with matching output shapes except for the concat axis. Layer shapes: [(None, 512, 113, 180), (None, 16, 30, 40)]

Is it because of my testing images are 1440x900? If so, How do I configure the input shape of the model?

--
Update I tested pics with

[plebreton]

The issue is you did not set your ~/.keras/keras.json file properly.

You need to have "image_dim_ordering" set to "th".

Note, that there is also another parameter "image_data_format" which comes with more recent version of Keras. You may have changed the wrong one by going quickly into the configuration of the platform ;)