mirror/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2025-08-03 20:56:30 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

Merge pull request #9013 from arrybn:ssd_last_layers_optim

Browse Source
This commit is contained in:
Vadim Pisarevsky 2017-06-28 10:38:55 +00:00
commit c5faa9aefa
2 changed files with 20 additions and 15 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

23
modules/dnn/src/layers/detection_output_layer.cpp
View File

@ -219,7 +219,7 @@ public:
_shareLocation, &allLocationPredictions);
// Retrieve all confidences.
std::vector<std::map<int, std::vector<float> > > allConfidenceScores;
std::vector<std::vector<std::vector<float> > > allConfidenceScores;
GetConfidenceScores(confidenceData, num, numPriors, _numClasses,
&allConfidenceScores);
@ -241,7 +241,7 @@ public:
for (int i = 0; i < num; ++i)
{
const LabelBBox& decodeBBoxes = allDecodedBBoxes[i];
const std::map<int, std::vector<float> >& confidenceScores =
const std::vector<std::vector<float> >& confidenceScores =
allConfidenceScores[i];
std::map<int, std::vector<int> > indices;
int numDetections = 0;
@ -252,13 +252,13 @@ public:
// Ignore background class.
continue;
}
if (confidenceScores.find(c) == confidenceScores.end())
if (confidenceScores.size() <= c)
{
// Something bad happened if there are no predictions for current label.
util::make_error<int>("Could not find confidence predictions for label ", c);
}
const std::vector<float>& scores = confidenceScores.find(c)->second;
const std::vector<float>& scores = confidenceScores[c];
int label = _shareLocation ? -1 : c;
if (decodeBBoxes.find(label) == decodeBBoxes.end())
{
@ -280,13 +280,13 @@ public:
{
int label = it->first;
const std::vector<int>& labelIndices = it->second;
if (confidenceScores.find(label) == confidenceScores.end())
if (confidenceScores.size() <= label)
{
// Something bad happened for current label.
util::make_error<int>("Could not find location predictions for label ", label);
continue;
}
const std::vector<float>& scores = confidenceScores.find(label)->second;
const std::vector<float>& scores = confidenceScores[label];
for (size_t j = 0; j < labelIndices.size(); ++j)
{
size_t idx = labelIndices[j];
@ -329,20 +329,20 @@ public:
int count = 0;
for (int i = 0; i < num; ++i)
{
const std::map<int, std::vector<float> >& confidenceScores =
const std::vector<std::vector<float> >& confidenceScores =
allConfidenceScores[i];
const LabelBBox& decodeBBoxes = allDecodedBBoxes[i];
for (std::map<int, std::vector<int> >::iterator it = allIndices[i].begin();
it != allIndices[i].end(); ++it)
{
int label = it->first;
if (confidenceScores.find(label) == confidenceScores.end())
if (confidenceScores.size() <= label)
{
// Something bad happened if there are no predictions for current label.
util::make_error<int>("Could not find confidence predictions for label ", label);
continue;
}
const std::vector<float>& scores = confidenceScores.find(label)->second;
const std::vector<float>& scores = confidenceScores[label];
int locLabel = _shareLocation ? -1 : label;
if (decodeBBoxes.find(locLabel) == decodeBBoxes.end())
{
@ -642,13 +642,14 @@ public:
// confidence prediction for an image.
void GetConfidenceScores(const float* confData, const int num,
const int numPredsPerClass, const int numClasses,
std::vector<std::map<int, std::vector<float> > >* confPreds)
std::vector<std::vector<std::vector<float> > >* confPreds)
{
confPreds->clear();
confPreds->resize(num);
for (int i = 0; i < num; ++i)
{
std::map<int, std::vector<float> >& labelScores = (*confPreds)[i];
std::vector<std::vector<float> >& labelScores = (*confPreds)[i];
labelScores.resize(numClasses);
for (int p = 0; p < numPredsPerClass; ++p)
{
int startIdx = p * numClasses;

12
modules/dnn/src/layers/softmax_layer.cpp
View File

@ -124,8 +124,9 @@ public:
for (size_t cnDim = 0; cnDim < channels; cnDim++)
{
const int offset = srcOffset + cnDim * cnStep;
for (size_t i = 0; i < innerSize; i++)
dstPtr[srcOffset + cnDim * cnStep + i] = srcPtr[srcOffset + cnDim * cnStep + i] - bufPtr[bufOffset + i];
dstPtr[offset + i] = srcPtr[offset + i] - bufPtr[bufOffset + i];
}
}
@ -142,22 +143,25 @@ public:
for (size_t cnDim = 0; cnDim < channels; cnDim++)
{
const int offset = srcOffset + cnDim * cnStep;
for (size_t i = 0; i < innerSize; i++)
bufPtr[bufOffset + i] += dstPtr[srcOffset + cnDim * cnStep + i];
bufPtr[bufOffset + i] += dstPtr[offset + i];
}
//divide by computed sum
for (size_t cnDim = 0; cnDim < channels; cnDim++)
{
const int offset = srcOffset + cnDim * cnStep;
for (size_t i = 0; i < innerSize; i++)
dstPtr[srcOffset + cnDim * cnStep + i] /= bufPtr[bufOffset + i];
dstPtr[offset + i] /= bufPtr[bufOffset + i];
}
if (logSoftMax)
{
for (size_t cnDim = 0; cnDim < channels; cnDim++)
{
const int offset = srcOffset + cnDim * cnStep;
for (size_t i = 0; i < innerSize; i++)
dstPtr[srcOffset + cnDim * cnStep + i] = log(dstPtr[srcOffset + cnDim * cnStep + i]);
dstPtr[offset + i] = log(dstPtr[offset + i]);
}
}
}