Add root_folder to ImageDataLayer

3 files changed, 57 insertions, 22 deletions

diff --git a/src/caffe/layers/data_layer.cpp b/src/caffe/layers/data_layer.cpp
index 95c54279..95604e5a 100644
--- a/src/caffe/layers/data_layer.cpp
+++ b/src/caffe/layers/data_layer.cpp
@@ -8,7 +8,9 @@
 #include "caffe/dataset_factory.hpp"
 #include "caffe/layer.hpp"
 #include "caffe/proto/caffe.pb.h"
+#ifdef TIMING
 #include "caffe/util/benchmark.hpp"
+#endif
 #include "caffe/util/io.hpp"
 #include "caffe/util/math_functions.hpp"
 #include "caffe/util/rng.hpp"
@@ -82,8 +84,13 @@ void DataLayer<Dtype>::DataLayerSetUp(const vector<Blob<Dtype>*>& bottom,
 // This function is used to create a thread that prefetches the data.
 template <typename Dtype>
 void DataLayer<Dtype>::InternalThreadEntry() {
+  #ifdef TIMING
   Timer batch_timer;
   batch_timer.Start();
+  float read_time = 0;
+  float trans_time = 0;
+  Timer timer;
+  #endif
   CHECK(this->prefetch_data_.count());
   CHECK(this->transformed_data_.count());
   Dtype* top_data = this->prefetch_data_.mutable_cpu_data();
@@ -93,9 +100,6 @@ void DataLayer<Dtype>::InternalThreadEntry() {
     top_label = this->prefetch_label_.mutable_cpu_data();
   }
   const int batch_size = this->layer_param_.data_param().batch_size();
-  float read_time = 0;
-  float trans_time = 0;
-  Timer timer;
   for (int item_id = 0; item_id < batch_size; ++item_id) {
     timer.Start();
     // get a blob
@@ -105,31 +109,36 @@ void DataLayer<Dtype>::InternalThreadEntry() {
     if (datum.encoded()) {
        cv_img = DecodeDatumToCVMat(datum);
     }
+    #ifdef TIMING
     read_time += timer.MilliSeconds();
     timer.Start();
+    #endif
 
     // Apply data transformations (mirror, scale, crop...)
     int offset = this->prefetch_data_.offset(item_id);
     this->transformed_data_.set_cpu_data(top_data + offset);
     if (datum.encoded()) {
-      this->data_transformer_.Transform(cv_img, &(this->transformed_data_));  
+      this->data_transformer_.Transform(cv_img, &(this->transformed_data_));
     } else {
       this->data_transformer_.Transform(datum, &(this->transformed_data_));
     }
-    
     if (this->output_labels_) {
       top_label[item_id] = datum.label();
     }
+    #ifdef TIMING
     trans_time += timer.MilliSeconds();
+    #endif
     // go to the next iter
     ++iter_;
     if (iter_ == dataset_->end()) {
       iter_ = dataset_->begin();
     }
   }
-  DLOG(INFO) << "Prefetch batch: " << batch_timer.MilliSeconds() << "ms.";
-  DLOG(INFO) << "Read time: " << read_time << "ms.";
-  DLOG(INFO) << "Transform time: " << trans_time << "ms.";
+  #ifdef TIMING
+  LOG(INFO) << "Prefetch batch: " << batch_timer.MilliSeconds() << "ms.";
+  LOG(INFO) << "Read time: " << read_time << "ms.";
+  LOG(INFO) << "Transform time: " << trans_time << "ms.";
+  #endif
 }
 
 INSTANTIATE_CLASS(DataLayer);
diff --git a/src/caffe/layers/image_data_layer.cpp b/src/caffe/layers/image_data_layer.cpp
index 67493117..0abcd888 100644
--- a/src/caffe/layers/image_data_layer.cpp
+++ b/src/caffe/layers/image_data_layer.cpp
@@ -6,7 +6,9 @@
 
 #include "caffe/data_layers.hpp"
 #include "caffe/layer.hpp"
+#ifdef TIMING
 #include "caffe/util/benchmark.hpp"
+#endif
 #include "caffe/util/io.hpp"
 #include "caffe/util/math_functions.hpp"
 #include "caffe/util/rng.hpp"
@@ -24,6 +26,7 @@ void ImageDataLayer<Dtype>::DataLayerSetUp(const vector<Blob<Dtype>*>& bottom,
   const int new_height = this->layer_param_.image_data_param().new_height();
   const int new_width  = this->layer_param_.image_data_param().new_width();
   const bool is_color  = this->layer_param_.image_data_param().is_color();
+  string root_folder = this->layer_param_.image_data_param().root_folder();
 
   CHECK((new_height == 0 && new_width == 0) ||
       (new_height > 0 && new_width > 0)) << "Current implementation requires "
@@ -57,7 +60,7 @@ void ImageDataLayer<Dtype>::DataLayerSetUp(const vector<Blob<Dtype>*>& bottom,
     lines_id_ = skip;
   }
   // Read an image, and use it to initialize the top blob.
-  cv::Mat cv_img = ReadImageToCVMat(lines_[lines_id_].first,
+  cv::Mat cv_img = ReadImageToCVMat(root_folder + lines_[lines_id_].first,
                                     new_height, new_width, is_color);
   const int channels = cv_img.channels();
   const int height = cv_img.rows;
@@ -92,8 +95,13 @@ void ImageDataLayer<Dtype>::ShuffleImages() {
 // This function is used to create a thread that prefetches the data.
 template <typename Dtype>
 void ImageDataLayer<Dtype>::InternalThreadEntry() {
+  #ifdef TIMING
   Timer batch_timer;
   batch_timer.Start();
+  float read_time = 0;
+  float trans_time = 0;
+  Timer timer;
+  #endif
   CHECK(this->prefetch_data_.count());
   CHECK(this->transformed_data_.count());
   Dtype* top_data = this->prefetch_data_.mutable_cpu_data();
@@ -103,28 +111,32 @@ void ImageDataLayer<Dtype>::InternalThreadEntry() {
   const int new_height = image_data_param.new_height();
   const int new_width = image_data_param.new_width();
   const bool is_color = image_data_param.is_color();
+  string root_folder = image_data_param.root_folder();
 
   // datum scales
   const int lines_size = lines_.size();
-  float read_time = 0;
-  float trans_time = 0;
-  Timer timer;
   for (int item_id = 0; item_id < batch_size; ++item_id) {
     // get a blob
+    #ifdef TIMING
     timer.Start();
+    #endif
     CHECK_GT(lines_size, lines_id_);
-    cv::Mat cv_img = ReadImageToCVMat(lines_[lines_id_].first,
+    cv::Mat cv_img = ReadImageToCVMat(root_folder + lines_[lines_id_].first,
                                     new_height, new_width, is_color);
     if (!cv_img.data) {
       continue;
     }
+    #ifdef TIMING
     read_time += timer.MilliSeconds();
     timer.Start();
+    #endif
     // Apply transformations (mirror, crop...) to the image
     int offset = this->prefetch_data_.offset(item_id);
     this->transformed_data_.set_cpu_data(top_data + offset);
     this->data_transformer_.Transform(cv_img, &(this->transformed_data_));
+    #ifdef TIMING
     trans_time += timer.MilliSeconds();
+    #endif
 
     top_label[item_id] = lines_[lines_id_].second;
     // go to the next iter
@@ -138,9 +150,11 @@ void ImageDataLayer<Dtype>::InternalThreadEntry() {
       }
     }
   }
-  DLOG(INFO) << "Prefetch batch: " << batch_timer.MilliSeconds() << "ms.";
-  DLOG(INFO) << "Read time: " << read_time << "ms.";
-  DLOG(INFO) << "Transform time: " << trans_time << "ms.";
+  #ifdef TIMING
+  LOG(INFO) << "Prefetch batch: " << batch_timer.MilliSeconds() << "ms.";
+  LOG(INFO) << "Read time: " << read_time << "ms.";
+  LOG(INFO) << "Transform time: " << trans_time << "ms.";
+  #endif
 }
 
 INSTANTIATE_CLASS(ImageDataLayer);
diff --git a/src/caffe/layers/window_data_layer.cpp b/src/caffe/layers/window_data_layer.cpp
index 47e0fb2a..8e656155 100644
--- a/src/caffe/layers/window_data_layer.cpp
+++ b/src/caffe/layers/window_data_layer.cpp
@@ -13,7 +13,9 @@
 #include "caffe/common.hpp"
 #include "caffe/data_layers.hpp"
 #include "caffe/layer.hpp"
+#ifdef TIMING
 #include "caffe/util/benchmark.hpp"
+#endif
 #include "caffe/util/io.hpp"
 #include "caffe/util/math_functions.hpp"
 #include "caffe/util/rng.hpp"
@@ -193,8 +195,13 @@ template <typename Dtype>
 void WindowDataLayer<Dtype>::InternalThreadEntry() {
   // At each iteration, sample N windows where N*p are foreground (object)
   // windows and N*(1-p) are background (non-object) windows
+  #ifdef TIMING
   Timer batch_timer;
   batch_timer.Start();
+  float read_time = 0;
+  float trans_time = 0;
+  Timer timer;
+  #endif
   Dtype* top_data = this->prefetch_data_.mutable_cpu_data();
   Dtype* top_label = this->prefetch_label_.mutable_cpu_data();
   const Dtype scale = this->layer_param_.window_data_param().scale();
@@ -221,14 +228,13 @@ void WindowDataLayer<Dtype>::InternalThreadEntry() {
   const int num_samples[2] = { batch_size - num_fg, num_fg };
 
   int item_id = 0;
-  float read_time = 0;
-  float trans_time = 0;
-  Timer timer;
   // sample from bg set then fg set
   for (int is_fg = 0; is_fg < 2; ++is_fg) {
     for (int dummy = 0; dummy < num_samples[is_fg]; ++dummy) {
       // sample a window
+      #ifdef TIMING
       timer.Start();
+      #endif
       const unsigned int rand_index = PrefetchRand();
       vector<float> window = (is_fg) ?
           fg_windows_[rand_index % fg_windows_.size()] :
@@ -245,8 +251,10 @@ void WindowDataLayer<Dtype>::InternalThreadEntry() {
         LOG(ERROR) << "Could not open or find file " << image.first;
         return;
       }
+      #ifdef TIMING
       read_time += timer.MilliSeconds();
       timer.Start();
+      #endif
       const int channels = cv_img.channels();
 
       // crop window out of image and warp it
@@ -364,7 +372,9 @@ void WindowDataLayer<Dtype>::InternalThreadEntry() {
           }
         }
       }
+      #ifdef TIMING
       trans_time += timer.MilliSeconds();
+      #endif
       // get window label
       top_label[item_id] = window[WindowDataLayer<Dtype>::LABEL];
 
@@ -404,9 +414,11 @@ void WindowDataLayer<Dtype>::InternalThreadEntry() {
       item_id++;
     }
   }
-  DLOG(INFO) << "Prefetch batch: " << batch_timer.MilliSeconds() << "ms.";
-  DLOG(INFO) << "Read time: " << read_time << "ms.";
-  DLOG(INFO) << "Transform time: " << trans_time << "ms.";
+  #ifdef TIMING
+  LOG(INFO) << "Prefetch batch: " << batch_timer.MilliSeconds() << "ms.";
+  LOG(INFO) << "Read time: " << read_time << "ms.";
+  LOG(INFO) << "Transform time: " << trans_time << "ms.";
+  #endif
 }
 
 INSTANTIATE_CLASS(WindowDataLayer);