Chiebot-Mirror
/
opencv
8
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Added function to get timings for layers

Browse Source
pull/9294/head
Aleksandr Rybnikov 8 years ago
parent da0a36c323
commit 8b1146deb2
5 changed files with 98 additions and 52 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 34
      modules/dnn/include/opencv2/dnn/dnn.hpp
  2. 77
      modules/dnn/src/dnn.cpp
  3. 19
      modules/java/generator/src/cpp/listconverters.cpp
  4. 7
      modules/java/generator/src/cpp/listconverters.hpp
  5. 13
      samples/dnn/ssd_mobilenet_object_detection.cpp

34
modules/dnn/include/opencv2/dnn/dnn.hpp
Unescape View File

@ -483,15 +483,15 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
* order is the same as in layersIds
*/
CV_WRAP void getLayersShapes(const std::vector<MatShape>& netInputShapes,
std::vector<int>* layersIds,
std::vector<std::vector<MatShape> >* inLayersShapes,
std::vector<std::vector<MatShape> >* outLayersShapes) const;
CV_OUT std::vector<int>& layersIds,
CV_OUT std::vector<std::vector<MatShape> >& inLayersShapes,
CV_OUT std::vector<std::vector<MatShape> >& outLayersShapes) const;
/** @overload */
CV_WRAP void getLayersShapes(const MatShape& netInputShape,
std::vector<int>* layersIds,
std::vector<std::vector<MatShape> >* inLayersShapes,
std::vector<std::vector<MatShape> >* outLayersShapes) const;
CV_OUT std::vector<int>& layersIds,
CV_OUT std::vector<std::vector<MatShape> >& inLayersShapes,
CV_OUT std::vector<std::vector<MatShape> >& outLayersShapes) const;
/** @brief Returns input and output shapes for layer with specified
* id in loaded model; preliminary inferencing isn't necessary.
@ -504,14 +504,14 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
*/
CV_WRAP void getLayerShapes(const MatShape& netInputShape,
const int layerId,
std::vector<MatShape>* inLayerShapes,
std::vector<MatShape>* outLayerShapes) const;
CV_OUT std::vector<MatShape>& inLayerShapes,
CV_OUT std::vector<MatShape>& outLayerShapes) const;
/** @overload */
CV_WRAP void getLayerShapes(const std::vector<MatShape>& netInputShapes,
const int layerId,
std::vector<MatShape>* inLayerShapes,
std::vector<MatShape>* outLayerShapes) const;
CV_OUT std::vector<MatShape>& inLayerShapes,
CV_OUT std::vector<MatShape>& outLayerShapes) const;
/** @brief Computes FLOP for whole loaded model with specified input shapes.
* @param netInputShapes vector of shapes for all net inputs.
@ -566,11 +566,13 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
* @param blobs output parameter to store resulting bytes for intermediate blobs.
*/
CV_WRAP void getMemoryConsumption(const std::vector<MatShape>& netInputShapes,
CV_OUT std::vector<int>& layerIds, CV_OUT std::vector<size_t>& weights,
CV_OUT std::vector<int>& layerIds,
CV_OUT std::vector<size_t>& weights,
CV_OUT std::vector<size_t>& blobs) const;
/** @overload */
CV_WRAP void getMemoryConsumption(const MatShape& netInputShape,
CV_OUT std::vector<int>& layerIds, CV_OUT std::vector<size_t>& weights,
CV_OUT std::vector<int>& layerIds,
CV_OUT std::vector<size_t>& weights,
CV_OUT std::vector<size_t>& blobs) const;
/** @brief Enables or disables layer fusion in the network.
@ -578,6 +580,14 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
*/
CV_WRAP void enableFusion(bool fusion);
/** @brief Returns overall time for inference and timings (in ticks) for layers.
* Indexes in returned vector correspond to layers ids. Some layers can be fused with others,
* in this case zero ticks count will be return for that skipped layers.
* @param timings vector for tick timings for all layers.
* @return overall ticks for model inference.
*/
CV_WRAP int64 getPerfProfile(CV_OUT std::vector<double>& timings);
private:
struct Impl;
Ptr<Impl> impl;

77
modules/dnn/src/dnn.cpp
Unescape View File

@ -47,6 +47,7 @@
#include <iostream>
#include <sstream>
#include <iterator>
#include <numeric>
#include <opencv2/dnn/shape_utils.hpp>
#include <opencv2/imgproc.hpp>
@ -633,7 +634,7 @@ struct Net::Impl
inpl.layerInstance = netInputLayer;
layerNameToId.insert(std::make_pair(inpl.name, inpl.id));
lastLayerId = 1;
lastLayerId = 0;
netWasAllocated = false;
fusion = true;
preferableBackend = DNN_BACKEND_DEFAULT;
@ -656,6 +657,7 @@ struct Net::Impl
bool netWasAllocated;
bool fusion;
std::vector<int64> layersTimings;
void compileHalide()
{
@ -716,6 +718,8 @@ struct Net::Impl
it = layers.find(0);
CV_Assert(it != layers.end());
it->second.skipFlags[DNN_BACKEND_DEFAULT] = true;
layersTimings.clear();
}
void setUpNet(const std::vector<LayerPin>& blobsToKeep_ = std::vector<LayerPin>())
@ -1269,6 +1273,8 @@ struct Net::Impl
allocateLayer(lid, layersShapes);
}
layersTimings.resize(lastLayerId + 1, 0);
fuseLayers(blobsToKeep_);
}
@ -1278,11 +1284,16 @@ struct Net::Impl
Ptr<Layer> layer = ld.layerInstance;
TickMeter tm;
tm.start();
if (preferableBackend == DNN_BACKEND_DEFAULT ||
!layer->supportBackend(preferableBackend))
{
if( !ld.skipFlags[DNN_BACKEND_DEFAULT] )
layer->forward(ld.inputBlobs, ld.outputBlobs, ld.internals);
else
tm.reset();
}
else if (!ld.skipFlags[preferableBackend])
{
@ -1299,6 +1310,9 @@ struct Net::Impl
}
}
tm.stop();
layersTimings[ld.id] = tm.getTimeTicks();
ld.flag = 1;
}
@ -1717,16 +1731,13 @@ std::vector<int> Net::getUnconnectedOutLayers() const
}
void Net::getLayersShapes(const ShapesVec& netInputShapes,
std::vector<int>* layersIds,
std::vector<ShapesVec>* inLayersShapes,
std::vector<ShapesVec>* outLayersShapes) const
std::vector<int>& layersIds,
std::vector<ShapesVec>& inLayersShapes,
std::vector<ShapesVec>& outLayersShapes) const
{
if ((layersIds || inLayersShapes || outLayersShapes) == false)
return;
if (layersIds) layersIds->clear();
if (inLayersShapes) inLayersShapes->clear();
if (outLayersShapes) outLayersShapes->clear();
layersIds.clear();
inLayersShapes.clear();
outLayersShapes.clear();
Impl::LayersShapesMap inOutShapes;
impl->getLayersShapes(netInputShapes, inOutShapes);
@ -1734,19 +1745,16 @@ void Net::getLayersShapes(const ShapesVec& netInputShapes,
for(Impl::LayersShapesMap::const_iterator it = inOutShapes.begin();
it != inOutShapes.end(); it++)
{
if (layersIds)
layersIds->push_back(it->first);
if (inLayersShapes)
inLayersShapes->push_back(it->second.in);
if (outLayersShapes)
outLayersShapes->push_back(it->second.out);
layersIds.push_back(it->first);
inLayersShapes.push_back(it->second.in);
outLayersShapes.push_back(it->second.out);
}
}
void Net::getLayersShapes(const MatShape& netInputShape,
std::vector<int>* layerIds,
std::vector<ShapesVec>* inLayersShapes,
std::vector<ShapesVec>* outLayersShapes) const
std::vector<int>& layerIds,
std::vector<ShapesVec>& inLayersShapes,
std::vector<ShapesVec>& outLayersShapes) const
{
getLayersShapes(ShapesVec(1, netInputShape),
layerIds, inLayersShapes, outLayersShapes);
@ -1754,8 +1762,8 @@ void Net::getLayersShapes(const MatShape& netInputShape,
void Net::getLayerShapes(const MatShape& netInputShape,
const int layerId,
ShapesVec* inLayerShapes,
ShapesVec* outLayerShapes) const
ShapesVec& inLayerShapes,
ShapesVec& outLayerShapes) const
{
getLayerShapes(ShapesVec(1, netInputShape),
layerId, inLayerShapes, outLayerShapes);
@ -1764,15 +1772,13 @@ void Net::getLayerShapes(const MatShape& netInputShape,
void Net::getLayerShapes(const ShapesVec& netInputShapes,
const int layerId,
ShapesVec* inLayerShapes,
ShapesVec* outLayerShapes) const
ShapesVec& inLayerShapes,
ShapesVec& outLayerShapes) const
{
LayerShapes shapes;
impl->getLayerShapes(netInputShapes, layerId, shapes);
if (inLayerShapes)
*inLayerShapes = shapes.in;
if (outLayerShapes)
*outLayerShapes = shapes.out;
inLayerShapes = shapes.in;
outLayerShapes = shapes.out;
}
int64 Net::getFLOPS(const std::vector<MatShape>& netInputShapes) const
@ -1782,7 +1788,7 @@ int64 Net::getFLOPS(const std::vector<MatShape>& netInputShapes) const
int64 flops = 0;
std::vector<int> ids;
std::vector<std::vector<MatShape> > inShapes, outShapes;
getLayersShapes(netInputShapes, &ids, &inShapes, &outShapes);
getLayersShapes(netInputShapes, ids, inShapes, outShapes);
CV_Assert(inShapes.size() == outShapes.size());
CV_Assert(inShapes.size() == ids.size());
@ -1867,8 +1873,8 @@ void Net::getMemoryConsumption(const int layerId,
weights += weightsBlob.total()*weightsBlob.elemSize();
}
std::vector<MatShape> outLayerShapes;
getLayerShapes(netInputShapes, layerId, 0, &outLayerShapes);
ShapesVec inLayerShapes, outLayerShapes;
getLayerShapes(netInputShapes, layerId, inLayerShapes, outLayerShapes);
for(int i = 0; i < outLayerShapes.size(); i++)
{
blobs += total(outLayerShapes[i]) * sizeof(float);
@ -1917,9 +1923,9 @@ void Net::getMemoryConsumption(const std::vector<MatShape>& netInputShapes,
weights.clear();
blobs.clear();
std::vector<std::vector<MatShape> > outLayerShapes;
std::vector<std::vector<MatShape> > inLayerShapes, outLayerShapes;
getLayersShapes(netInputShapes, &layerIds, 0, &outLayerShapes);
getLayersShapes(netInputShapes, layerIds, inLayerShapes, outLayerShapes);
for(int i = 0; i < layerIds.size(); i++)
{
@ -1968,6 +1974,13 @@ void Net::setHalideScheduler(const String& scheduler)
impl->halideConfigFile = scheduler;
}
int64 Net::getPerfProfile(std::vector<double>& timings)
{
timings = std::vector<double>(impl->layersTimings.begin() + 1, impl->layersTimings.end());
int64 total = std::accumulate(timings.begin(), timings.end(), 0);
return total;
}
//////////////////////////////////////////////////////////////////////////
Importer::~Importer() {}

19
modules/java/generator/src/cpp/listconverters.cpp
Unescape View File

@ -56,4 +56,21 @@ void Copy_vector_String_to_List(JNIEnv* env, std::vector<cv::String>& vs, jobjec
env->CallBooleanMethod(list, m_add, element);
env->DeleteLocalRef(element);
}
}
}
#if defined(HAVE_OPENCV_DNN)
void Copy_vector_MatShape_to_List(JNIEnv* env, std::vector<cv::dnn::MatShape>& vs, jobject list)
{
static jclass juArrayList = ARRAYLIST(env);
jmethodID m_clear = LIST_CLEAR(env, juArrayList);
jmethodID m_add = LIST_ADD(env, juArrayList);
env->CallVoidMethod(list, m_clear);
for (std::vector<cv::dnn::MatShape>::iterator it = vs.begin(); it != vs.end(); ++it)
{
jstring element = env->NewStringUTF("");
env->CallBooleanMethod(list, m_add, element);
env->DeleteLocalRef(element);
}
}
#endif

7
modules/java/generator/src/cpp/listconverters.hpp
Unescape View File

@ -16,4 +16,9 @@ std::vector<cv::String> List_to_vector_String(JNIEnv* env, jobject list);
void Copy_vector_String_to_List(JNIEnv* env, std::vector<cv::String>& vs, jobject list);
#endif /* LISTCONVERTERS_HPP */
#if defined(HAVE_OPENCV_DNN)
#include "opencv2/dnn.hpp"
void Copy_vector_MatShape_to_List(JNIEnv* env, std::vector<cv::dnn::MatShape>& vs, jobject list);
#endif
#endif /* LISTCONVERTERS_HPP */

13
samples/dnn/ssd_mobilenet_object_detection.cpp
Unescape View File

@ -101,17 +101,18 @@ int main(int argc, char** argv)
//! [Prepare blob]
//! [Set input blob]
net.setInput(inputBlob, "data"); //set the network input
net.setInput(inputBlob, "data"); //set the network input
//! [Set input blob]
TickMeter tm;
tm.start();
//! [Make forward pass]
Mat detection = net.forward("detection_out"); //compute output
tm.stop();
cout << "Inference time, ms: " << tm.getTimeMilli() << endl;
Mat detection = net.forward("detection_out"); //compute output
//! [Make forward pass]
std::vector<double> layersTimings;
double freq = getTickFrequency() / 1000;
double time = net.getPerfProfile(layersTimings) / freq;
cout << "Inference time, ms: " << time << endl;
Mat detectionMat(detection.size[2], detection.size[3], CV_32F, detection.ptr<float>());
frame = frame(crop);

Write Preview
Loading…
Cancel
Save