Check failed: axis_index < num_axes() (4 vs. 4) axis 4 out of range for 4-D Blob with shape

[sara-eb]

Hi, Thank you for sharing the code.
I have compiled 3D-Caffe for pycaffe, and I created the .h files in python. At first since I saw that the input shape based on 3D-Caffe should be in this order NxCxDxHxW

I0721 02:11:07.162717  6153 hdf5_data_layer.cpp:117] Number of HDF5 files: 90
I0721 02:11:07.163275  6153 hdf5.cpp:32] Datatype class: H5T_FLOAT
I0721 02:11:07.326478  6153 hdf5.cpp:35] Datatype class: H5T_INTEGER
I0721 02:11:07.592453  6153 net.cpp:150] Setting up loaddata
I0721 02:11:07.592517  6153 net.cpp:157] Top shape: 1 1 104 256 256 (6815744)
I0721 02:11:07.592532  6153 net.cpp:157] Top shape: 1 1 104 256 256 (6815744)
I0721 02:11:07.592540  6153 net.cpp:165] Memory required for data: 54525952
I0721 02:11:07.592558  6153 layer_factory.hpp:77] Creating layer conv_d0a-b
I0721 02:11:07.592628  6153 net.cpp:106] Creating Layer conv_d0a-b
I0721 02:11:07.592651  6153 net.cpp:454] conv_d0a-b <- data
I0721 02:11:07.592684  6153 net.cpp:411] conv_d0a-b -> d0b
F0721 02:11:07.593014  6153 blob.hpp:140] Check failed: num_axes() <= 4 (5 vs. 4) Cannot use legacy accessors on Blobs with > 4 axes.
*** Check failure stack trace: ***
    @     0x7f3376c885cd  google::LogMessage::Fail()
    @     0x7f3376c8a433  google::LogMessage::SendToLog()
    @     0x7f3376c8815b  google::LogMessage::Flush()
    @     0x7f3376c8ae1e  google::LogMessageFatal::~LogMessageFatal()
    @     0x7f33772170d5  caffe::Blob<>::LegacyShape()
    @     0x7f337721d6a3  caffe::MSRAFiller<>::Fill()
    @     0x7f33772a275e  caffe::BaseConvolutionLayer<>::LayerSetUp()
    @     0x7f3377370a45  caffe::Net<>::Init()
    @     0x7f3377372301  caffe::Net<>::Net()
    @     0x7f337734c7ea  caffe::Solver<>::InitTrainNet()
    @     0x7f337734cd57  caffe::Solver<>::Init()
    @     0x7f337734d0ea  caffe::Solver<>::Solver()
    @     0x7f3377205c93  caffe::Creator_SGDSolver<>()
    @           0x40c48f  train()
    @           0x409214  main
    @     0x7f33756da830  __libc_start_main
    @           0x4099b9  _start
    @              (nil)  (unknown)

Then I changed the code to only have CxHxWxD:

        img = img.reshape(1,img.shape[0],img.shape[1], img.shape[2])
        lbl = img.reshape(1,lbl.shape[0],lbl.shape[1],lbl.shape[2])

shape of h5 files for example for a volume with grayscale images is (1, 256, 256, 104) for both data and label, which is in order CxHxWxD (channel, height,width,depth). Once I want to run it in 3D-Caffe, it is showing this error, which is related to Concat layer,

0721 04:24:50.512578  8927 net.cpp:157] Top shape: 1 512 60 22 (675840)
I0721 04:24:50.512579  8927 net.cpp:165] Memory required for data: 168148992
I0721 04:24:50.512581  8927 layer_factory.hpp:77] Creating layer concat_d2c_u2a-b
I0721 04:24:50.512584  8927 net.cpp:106] Creating Layer concat_d2c_u2a-b
I0721 04:24:50.512588  8927 net.cpp:454] concat_d2c_u2a-b <- scaleu2a
I0721 04:24:50.512589  8927 net.cpp:454] concat_d2c_u2a-b <- scaled2c_relu_d2c_0_split_1
I0721 04:24:50.512593  8927 net.cpp:411] concat_d2c_u2a-b -> u2b
F0721 04:24:50.512604  8927 concat_layer.cpp:42] Check failed: top_shape[j] == bottom[i]->shape(j) (60 vs. 64) All inputs must have the same shape, except at concat_axis.
*** Check failure stack trace: ***
    @     0x7ff92fdc75cd  google::LogMessage::Fail()
    @     0x7ff92fdc9433  google::LogMessage::SendToLog()
    @     0x7ff92fdc715b  google::LogMessage::Flush()
    @     0x7ff92fdc9e1e  google::LogMessageFatal::~LogMessageFatal()
    @     0x7ff9303b6a71  caffe::ConcatLayer<>::Reshape()
    @     0x7ff9304afa54  caffe::Net<>::Init()
    @     0x7ff9304b1301  caffe::Net<>::Net()
    @     0x7ff93048b7ea  caffe::Solver<>::InitTrainNet()
    @     0x7ff93048bd57  caffe::Solver<>::Init()
    @     0x7ff93048c0ea  caffe::Solver<>::Solver()
    @     0x7ff930344c93  caffe::Creator_SGDSolver<>()
    @           0x40c48f  train()
    @           0x409214  main
    @     0x7ff92e819830  __libc_start_main
    @           0x4099b9  _start
    @              (nil)  (unknown)
Aborted (core dumped)

But the problem is that the number of slices is different from patient to patient. Then, then based on what I saw in HeartSeg, I added
transform_param { crop_size_l : 64 crop_size_h : 64 crop_size_w : 64 } to HDF5Data layer, But am still getting an error:

I0```
721 04:29:23.488734 8998 hdf5_data_layer.cpp:117] Number of HDF5 files: 90
I0721 04:29:23.489279 8998 hdf5.cpp:32] Datatype class: H5T_FLOAT
I0721 04:29:23.506300 8998 hdf5.cpp:35] Datatype class: H5T_INTEGER
F0721 04:29:23.520934 8998 blob.hpp:122] Check failed: axis_index < num_axes() (4 vs. 4) axis 4 out of range for 4-D Blob with shape 1 256 256 104 (6815744)
*** Check failure stack trace: ***
@ 0x7fb7ed6565cd google::LogMessage::Fail()
@ 0x7fb7ed658433 google::LogMessage::SendToLog()
@ 0x7fb7ed65615b google::LogMessage::Flush()
@ 0x7fb7ed658e1e google::LogMessageFatal::~LogMessageFatal()
@ 0x7fb7edbea0d8 caffe::Blob<>::CanonicalAxisIndex()
@ 0x7fb7edcd0cf9 caffe::HDF5DataLayer<>::HDF5DataTransform()
@ 0x7fb7edccec49 caffe::HDF5DataLayer<>::LoadHDF5FileData()
@ 0x7fb7edccda81 caffe::HDF5DataLayer<>::LayerSetUp()
@ 0x7fb7edd3ea45 caffe::Net<>::Init()
@ 0x7fb7edd40301 caffe::Net<>::Net()
@ 0x7fb7edd1a7ea caffe::Solver<>::InitTrainNet()
@ 0x7fb7edd1ad57 caffe::Solver<>::Init()
@ 0x7fb7edd1b0ea caffe::Solver<>::Solver()
@ 0x7fb7edbd3c93 caffe::Creator_SGDSolver<>()
@ 0x40c48f train()
@ 0x409214 main
@ 0x7fb7ec0a8830 __libc_start_main
@ 0x4099b9 _start
@ (nil) (unknown)
Aborted (core dumped)

How to solve the issue? what is the reason that problem coming from? 
Should I change the order of channels?