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-rw-r--r--src/caffe/data_transformer.cpp12
-rw-r--r--src/caffe/layers/data_layer.cpp25
-rw-r--r--src/caffe/layers/image_data_layer.cpp30
-rw-r--r--src/caffe/layers/window_data_layer.cpp24
-rw-r--r--src/caffe/net.cpp10
-rw-r--r--src/caffe/proto/caffe.proto1
-rw-r--r--src/caffe/util/io.cpp5
7 files changed, 74 insertions, 33 deletions
diff --git a/src/caffe/data_transformer.cpp b/src/caffe/data_transformer.cpp
index 8f145994..023396ce 100644
--- a/src/caffe/data_transformer.cpp
+++ b/src/caffe/data_transformer.cpp
@@ -193,8 +193,7 @@ void DataTransformer<Dtype>::Transform(const cv::Mat& cv_img,
CHECK_LE(width, img_width);
CHECK_GE(num, 1);
- CHECK(cv_img.depth() == CV_8U || cv_img.depth() == CV_8S) <<
- "Image data type must be unsigned or signed byte";
+ CHECK(cv_img.depth() == CV_8U) << "Image data type must be unsigned byte";
const int crop_size = param_.crop_size();
const Dtype scale = param_.scale();
@@ -238,22 +237,19 @@ void DataTransformer<Dtype>::Transform(const cv::Mat& cv_img,
h_off = (img_height - crop_size) / 2;
w_off = (img_width - crop_size) / 2;
}
- cv::Rect roi(h_off, w_off, crop_size, crop_size);
+ cv::Rect roi(w_off, h_off, crop_size, crop_size);
cv_cropped_img = cv_img(roi);
} else {
CHECK_EQ(img_height, height);
CHECK_EQ(img_width, width);
}
-
- // if (do_mirror) {
- // cv::flip(cv_cropped_img, cv_cropped_img, 1);
- // }
+
CHECK(cv_cropped_img.data);
Dtype* transformed_data = transformed_blob->mutable_cpu_data();
int top_index;
for (int h = 0; h < height; ++h) {
- const char* ptr = cv_cropped_img.ptr<char>(h);
+ const uchar* ptr = cv_cropped_img.ptr<uchar>(h);
int img_index = 0;
for (int w = 0; w < width; ++w) {
for (int c = 0; c < img_channels; ++c) {
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);
diff --git a/src/caffe/net.cpp b/src/caffe/net.cpp
index 5b7152e6..c0e56920 100644
--- a/src/caffe/net.cpp
+++ b/src/caffe/net.cpp
@@ -9,7 +9,9 @@
#include "caffe/layer.hpp"
#include "caffe/net.hpp"
#include "caffe/proto/caffe.pb.h"
+#ifdef TIMING
#include "caffe/util/benchmark.hpp"
+#endif
#include "caffe/util/insert_splits.hpp"
#include "caffe/util/io.hpp"
#include "caffe/util/math_functions.hpp"
@@ -500,8 +502,10 @@ void Net<Dtype>::GetLearningRateAndWeightDecay() {
template <typename Dtype>
Dtype Net<Dtype>::ForwardFromTo(int start, int end) {
+ #ifdef TIMING
Timer timer;
timer.Start();
+ #endif
CHECK_GE(start, 0);
CHECK_LT(end, layers_.size());
Dtype loss = 0;
@@ -512,7 +516,9 @@ Dtype Net<Dtype>::ForwardFromTo(int start, int end) {
loss += layer_loss;
if (debug_info_) { ForwardDebugInfo(i); }
}
+ #ifdef TIMING
LOG(INFO) << "Forward time: " << timer.MilliSeconds() << "ms.";
+ #endif
return loss;
}
@@ -569,8 +575,10 @@ string Net<Dtype>::Forward(const string& input_blob_protos, Dtype* loss) {
template <typename Dtype>
void Net<Dtype>::BackwardFromTo(int start, int end) {
+ #ifdef TIMING
Timer timer;
timer.Start();
+ #endif
CHECK_GE(end, 0);
CHECK_LT(start, layers_.size());
for (int i = start; i >= end; --i) {
@@ -580,7 +588,9 @@ void Net<Dtype>::BackwardFromTo(int start, int end) {
if (debug_info_) { BackwardDebugInfo(i); }
}
}
+ #ifdef TIMING
LOG(INFO) << "Backward time: " << timer.MilliSeconds() << "ms.";
+ #endif
}
template <typename Dtype>
diff --git a/src/caffe/proto/caffe.proto b/src/caffe/proto/caffe.proto
index 53db6f76..b602d0e4 100644
--- a/src/caffe/proto/caffe.proto
+++ b/src/caffe/proto/caffe.proto
@@ -540,6 +540,7 @@ message ImageDataParameter {
// DEPRECATED. See TransformationParameter. Specify if we want to randomly mirror
// data.
optional bool mirror = 6 [default = false];
+ optional string root_folder = 12 [default = ""];
}
// Message that stores parameters InfogainLossLayer
diff --git a/src/caffe/util/io.cpp b/src/caffe/util/io.cpp
index 06b9deb0..b136bc8a 100644
--- a/src/caffe/util/io.cpp
+++ b/src/caffe/util/io.cpp
@@ -150,8 +150,7 @@ bool DecodeDatum(const int height, const int width, const bool is_color,
}
void CVMatToDatum(const cv::Mat& cv_img, Datum* datum) {
- CHECK(cv_img.depth() == CV_8U || cv_img.depth() == CV_8S) <<
- "Image data type must be unsigned or signed byte";
+ CHECK(cv_img.depth() == CV_8U) << "Image data type must be unsigned byte";
datum->set_channels(cv_img.channels());
datum->set_height(cv_img.rows);
datum->set_width(cv_img.cols);
@@ -164,7 +163,7 @@ void CVMatToDatum(const cv::Mat& cv_img, Datum* datum) {
int datum_size = datum_channels * datum_height * datum_width;
std::string buffer(datum_size, ' ');
for (int h = 0; h < datum_height; ++h) {
- const char* ptr = cv_img.ptr<char>(h);
+ const uchar* ptr = cv_img.ptr<uchar>(h);
int img_index = 0;
for (int w = 0; w < datum_width; ++w) {
for (int c = 0; c < datum_channels; ++c) {
generated by cgit v1.2.3 (git 2.25.1) at 2024-06-28 06:08:58 +0000