how to do the prediction iteratively using C++ interface?

[jeremy chang]

Hi, i am the beginner of caffe

Recently i have been learning how to use a pretrained caffe model to do some prediction in my own  project

and now i am trying to do a iteratively prediction while each loop there will be a new data(input) to be predicted

i use memory data layer as my data input layer

before entering the loop, i make some declaration 

////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

               caffe::Datum datum;

datum.set_channels(1);

datum.set_height(1);

datum.set_width(30);

vector<caffe::Datum> dvector;

boost::shared_ptr<MemoryDataLayer<float> > memory_data_layer;

memory_data_layer = boost::static_pointer_cast<MemoryDataLayer<float>>(net.layer_by_name("datas"));

////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

and in each loop, assume there is a new input data "vector<float> mydata" to be predicted

Here is what i do in each loop

///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

              1.  copy data from "mydata" to "datum"

              2.   dvector.clear();

    dvector.push_back(datum);

              3.   memory_data_layer->AddDatumVector(dvector);

              4.   const vector<Blob<float>*> & results = net.Forward();

    float *output = results[0]->mutable_cpu_data();

              5.   get output result from "output[1]"

////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

but the output result will turn out to be the same every loop even though the input data is different

am I skip any necessary steps?

thanks!