implementato addMatVectorMultiLabel

- cambiati i test di addMatVector per provare addMatVectorMultiLabel.
Vanno riportati come erano prima

include/caffe/data_layers.hpp

@@ -280,6 +280,8 @@ class MemoryDataLayer : public BaseDataLayer<Dtype> {
 #ifdef USE_OPENCV
   virtual void AddMatVector(const vector<cv::Mat>& mat_vector,
       const vector<int>& labels);
+  virtual void AddMatVectorMultilabel(const vector<cv::Mat>& mat_vector,
+      const vector< vector < int > >& labels);
 #endif  // USE_OPENCV
 
   // Reset should accept const pointers, but can't, because the memory
@@ -296,7 +298,7 @@ class MemoryDataLayer : public BaseDataLayer<Dtype> {
   virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
       const vector<Blob<Dtype>*>& top);
 
-  int batch_size_, channels_, height_, width_, size_;
+  int batch_size_, channels_, height_, width_, data_size_, label_size_;
   Dtype* data_;
   Dtype* labels_;
   int n_;

src/caffe/layers/memory_data_layer.cpp

@@ -15,8 +15,9 @@ void MemoryDataLayer<Dtype>::DataLayerSetUp(const vector<Blob<Dtype>*>& bottom,
   channels_ = this->layer_param_.memory_data_param().channels();
   height_ = this->layer_param_.memory_data_param().height();
   width_ = this->layer_param_.memory_data_param().width();
-  size_ = channels_ * height_ * width_;
-  CHECK_GT(batch_size_ * size_, 0) <<
+  data_size_ = channels_ * height_ * width_;
+  label_size_ = 1;
+  CHECK_GT(batch_size_ * data_size_, 0) <<
       "batch_size, channels, height, and width must be specified and"
       " positive in memory_data_param";
   vector<int> label_shape(1, batch_size_);
@@ -77,6 +78,41 @@ void MemoryDataLayer<Dtype>::AddMatVector(const vector<cv::Mat>& mat_vector,
   Reset(top_data, top_label, num);
   has_new_data_ = true;
 }
+
+template <typename Dtype>
+void MemoryDataLayer<Dtype>::AddMatVectorMultilabel(const vector<cv::Mat>& mat_vector,
+    const vector< vector < int > >& labels) {
+  size_t num = mat_vector.size();
+  CHECK(!has_new_data_) <<
+      "Can't add mat until current data has been consumed.";
+  CHECK_GT(num, 0) << "There is no mat to add";
+  CHECK_EQ(num % batch_size_, 0) <<
+      "The added data must be a multiple of the batch size.";
+  CHECK_EQ(num, labels.size()) <<
+      "Added mat and labels must have the same size";
+  label_size_ = labels[0].size();
+  for(int i = 1; i < num; ++i) {
+    CHECK_EQ(labels[i].size(), label_size_) <<
+          "All labels must have the same dimension";
+  }
+  added_data_.Reshape(num, channels_, height_, width_);
+  added_label_.Reshape(num, label_size_, 1, 1);
+  // Apply data transformations (mirror, scale, crop...)
+  this->data_transformer_->Transform(mat_vector, &added_data_);
+  // Copy Labels
+  Dtype* top_label = added_label_.mutable_cpu_data();
+  int index_label;
+  for (int item_id = 0; item_id < num; ++item_id) {
+    for (int label_id = 0; label_id < label_size_; ++label_id) {
+      index_label = (item_id * label_size_) + label_id;
+      top_label[index_label] = labels[item_id][label_id];
+    }
+  }
+  // num_images == batch_size_
+  Dtype* top_data = added_data_.mutable_cpu_data();
+  Reset(top_data, top_label, num);
+  has_new_data_ = true;
+}
 #endif  // USE_OPENCV
 
 template <typename Dtype>
@@ -101,16 +137,16 @@ void MemoryDataLayer<Dtype>::set_batch_size(int new_size) {
       "Can't change batch_size until current data has been consumed.";
   batch_size_ = new_size;
   added_data_.Reshape(batch_size_, channels_, height_, width_);
-  added_label_.Reshape(batch_size_, 1, 1, 1);
+  added_label_.Reshape(batch_size_, label_size_, 1, 1);
 }
 
 template <typename Dtype>
 void MemoryDataLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
       const vector<Blob<Dtype>*>& top) {
   CHECK(data_) << "MemoryDataLayer needs to be initalized by calling Reset";
   top[0]->Reshape(batch_size_, channels_, height_, width_);
-  top[1]->Reshape(batch_size_, 1, 1, 1);
-  top[0]->set_cpu_data(data_ + pos_ * size_);
+  top[1]->Reshape(batch_size_, label_size_, 1, 1);
+  top[0]->set_cpu_data(data_ + pos_ * data_size_);
   top[1]->set_cpu_data(labels_ + pos_);
   pos_ = (pos_ + batch_size_) % n_;
   if (pos_ == 0)

src/caffe/test/test_memory_data_layer.cpp

@@ -190,7 +190,10 @@ TYPED_TEST(MemoryDataLayerTest, AddMatVectorDefaultTransform) {
     label_vector[i] = i;
     cv::randu(mat_vector[i], cv::Scalar::all(0), cv::Scalar::all(255));
   }
-  layer.AddMatVector(mat_vector, label_vector);
+  vector < vector < int > > multilabel_vector;
+  for(int i = 0; i< mat_vector.size(); ++i)
+    multilabel_vector.push_back(label_vector);
+  layer.AddMatVectorMultilabel(mat_vector, multilabel_vector);
 
   int data_index;
   const size_t count = this->channels_ * this->height_ * this->width_;
@@ -235,7 +238,10 @@ TYPED_TEST(MemoryDataLayerTest, TestSetBatchSize) {
     label_vector[i] = i;
     cv::randu(mat_vector[i], cv::Scalar::all(0), cv::Scalar::all(255));
   }
-  layer.AddMatVector(mat_vector, label_vector);
+  vector < vector < int > > multilabel_vector;
+  for(int i = 0; i< mat_vector.size(); ++i)
+      multilabel_vector.push_back(label_vector);
+  layer.AddMatVectorMultilabel(mat_vector, multilabel_vector);
   // then consume the data
   int data_index;
   const size_t count = this->channels_ * this->height_ * this->width_;
@@ -270,7 +276,10 @@ TYPED_TEST(MemoryDataLayerTest, TestSetBatchSize) {
     label_vector[i] = i;
     cv::randu(mat_vector[i], cv::Scalar::all(0), cv::Scalar::all(255));
   }
-  layer.AddMatVector(mat_vector, label_vector);
+  multilabel_vector.clear();
+  for(int i = 0; i< mat_vector.size(); ++i)
+      multilabel_vector.push_back(label_vector);
+  layer.AddMatVectorMultilabel(mat_vector, multilabel_vector);
 
   // finally consume new data and check if everything is fine
   for (int iter = 0; iter < num_iter; ++iter) {