Feed my own image data on caffe [duplicate] - matlab

Question

I have the train and label data as data.mat. (I have 200 training data with 6000 features and labels are (-1, +1) that have saved in data.mat).
I am trying to convert my data in hdf5 and run Caffe using:
load data.mat
hdf5write('my_data.h5', '/new_train_x', single( reshape(new_train_x,[200, 6000, 1, 1]) ) );
hdf5write('my_data.h5', '/label_train', single( reshape(label_train,[200, 1, 1, 1]) ), 'WriteMode', 'append' );
And my layer.prototxt (just data layer) is:
layer {
type: "HDF5Data"
name: "data"
top: "new_train_x" # note: same name as in HDF5
top: "label_train" #
hdf5_data_param {
source: "/path/to/list/file.txt"
batch_size: 20
}
include { phase: TRAIN }
}
but, i have an error:
( Check failed: hdf_blobs_[i]->shape(0) == num (200 vs. 6000))
I1222 17:02:48.915861 3941 layer_factory.hpp:76] Creating layer data
I1222 17:02:48.915871 3941 net.cpp:110] Creating Layer data
I1222 17:02:48.915877 3941 net.cpp:433] data -> new_train_x
I1222 17:02:48.915890 3941 net.cpp:433] data -> label_train
I1222 17:02:48.915900 3941 hdf5_data_layer.cpp:81] Loading list of HDF5 filenames from: file.txt
I1222 17:02:48.915923 3941 hdf5_data_layer.cpp:95] Number of HDF5 files: 1
F1222 17:02:48.993865 3941 hdf5_data_layer.cpp:55] Check failed: hdf_blobs_[i]->shape(0) == num (200 vs. 6000)
*** Check failure stack trace: ***
# 0x7fd2e6608ddd google::LogMessage::Fail()
# 0x7fd2e660ac90 google::LogMessage::SendToLog()
# 0x7fd2e66089a2 google::LogMessage::Flush()
# 0x7fd2e660b6ae google::LogMessageFatal::~LogMessageFatal()
# 0x7fd2e69f9eda caffe::HDF5DataLayer<>::LoadHDF5FileData()
# 0x7fd2e69f901f caffe::HDF5DataLayer<>::LayerSetUp()
# 0x7fd2e6a48030 caffe::Net<>::Init()
# 0x7fd2e6a49278 caffe::Net<>::Net()
# 0x7fd2e6a9157a caffe::Solver<>::InitTrainNet()
# 0x7fd2e6a928b1 caffe::Solver<>::Init()
# 0x7fd2e6a92c19 caffe::Solver<>::Solver()
# 0x41222d caffe::GetSolver<>()
# 0x408ed9 train()
# 0x406741 main
# 0x7fd2e533ca40 (unknown)
# 0x406f69 _start
Aborted (core dumped)
Many thanks!!!! Any advice would be appreciated!

Answer 1

The problem
It seems like there is indeed a conflict with the order of elements in arrays: matlab arranges the elements from the first dimension to the last (like fortran), while caffe and hdf5 stores the arrays from last dimension to first:
Suppose we have X of shape nxcxhxw then the "second element of X" is X[2,1,1,1] in matlab but X[0,0,0,1] in C (1-based vs 0-based indexing doesn't make life easier at all).
Therefore, when you save an array of size=[200, 6000, 1, 1] in Matlab, what hdf5 and caffe are actually seeing is as array of shape=[6000,200].
Using the h5ls command line tool can help you spot the problem.
In matlab you saved
>> hdf5write('my_data.h5', '/new_train_x',
single( reshape(new_train_x,[200, 6000, 1, 1]) );
>> hdf5write('my_data.h5', '/label_train',
single( reshape(label_train,[200, 1, 1, 1]) ),
'WriteMode', 'append' );
Now you can inspect the resulting my_data.h5 using h5ls (in Linux terminal):
user#host:~/$ h5ls ./my_data.h5
label_train Dataset {200}
new_train_x Dataset {6000, 200}
As you can see, the arrays are written "backwards".
Solution
Taking this conflict into account when exporting data from Matlab, you should permute:
load data.mat
hdf5write('my_data.h5', '/new_train_x',
single( permute(reshape(new_train_x,[200, 6000, 1, 1]),[4:-1:1] ) );
hdf5write('my_data.h5', '/label_train',
single( permute(reshape(label_train,[200, 1, 1, 1]), [4:-1:1] ) ),
'WriteMode', 'append' );
Inspect the resulting my_data.h5 using h5ls now results with:
user#host:~/$ h5ls ./my_data.h5
label_train Dataset {200, 1, 1, 1}
new_train_x Dataset {200, 6000, 1, 1}
Which is what you expected in the first place.