Chiebot-Mirror
/
opencv
mirror of https://github.com/opencv/opencv.git
8
0
Fork 0
Code Issues Projects Releases Wiki Activity

Removed usage of std::map in DetectionOutput layer

Browse Source
pull/9013/head
Aleksandr Rybnikov 7 years ago
parent 82ec76c123
commit ec321e651f
2 changed files with 20 additions and 15 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Unified View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 23
      modules/dnn/src/layers/detection_output_layer.cpp
  2. 12
      modules/dnn/src/layers/softmax_layer.cpp

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

@ -218,7 +218,7 @@ public:
_shareLocation, &allLocationPredictions); _shareLocation, &allLocationPredictions);
// Retrieve all confidences. // 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, GetConfidenceScores(confidenceData, num, numPriors, _numClasses,
&allConfidenceScores); &allConfidenceScores);
@ -240,7 +240,7 @@ public:
for (int i = 0; i < num; ++i) for (int i = 0; i < num; ++i)
{ {
const LabelBBox& decodeBBoxes = allDecodedBBoxes[i]; const LabelBBox& decodeBBoxes = allDecodedBBoxes[i];
const std::map<int, std::vector<float> >& confidenceScores = const std::vector<std::vector<float> >& confidenceScores =
allConfidenceScores[i]; allConfidenceScores[i];
std::map<int, std::vector<int> > indices; std::map<int, std::vector<int> > indices;
int numDetections = 0; int numDetections = 0;
@ -251,13 +251,13 @@ public:
// Ignore background class. // Ignore background class.
continue; continue;
} }
if (confidenceScores.find(c) == confidenceScores.end()) if (confidenceScores.size() <= c)
{ {
// Something bad happened if there are no predictions for current label. // Something bad happened if there are no predictions for current label.
util::make_error<int>("Could not find confidence predictions for label ", c); 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; int label = _shareLocation ? -1 : c;
if (decodeBBoxes.find(label) == decodeBBoxes.end()) if (decodeBBoxes.find(label) == decodeBBoxes.end())
{ {
@ -279,13 +279,13 @@ public:
{ {
int label = it->first; int label = it->first;
const std::vector<int>& labelIndices = it->second; const std::vector<int>& labelIndices = it->second;
if (confidenceScores.find(label) == confidenceScores.end()) if (confidenceScores.size() <= label)
{ {
// Something bad happened for current label. // Something bad happened for current label.
util::make_error<int>("Could not find location predictions for label ", label); util::make_error<int>("Could not find location predictions for label ", label);
continue; 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) for (size_t j = 0; j < labelIndices.size(); ++j)
{ {
size_t idx = labelIndices[j]; size_t idx = labelIndices[j];
@ -328,20 +328,20 @@ public:
int count = 0; int count = 0;
for (int i = 0; i < num; ++i) for (int i = 0; i < num; ++i)
{ {
const std::map<int, std::vector<float> >& confidenceScores = const std::vector<std::vector<float> >& confidenceScores =
allConfidenceScores[i]; allConfidenceScores[i];
const LabelBBox& decodeBBoxes = allDecodedBBoxes[i]; const LabelBBox& decodeBBoxes = allDecodedBBoxes[i];
for (std::map<int, std::vector<int> >::iterator it = allIndices[i].begin(); for (std::map<int, std::vector<int> >::iterator it = allIndices[i].begin();
it != allIndices[i].end(); ++it) it != allIndices[i].end(); ++it)
{ {
int label = it->first; 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. // Something bad happened if there are no predictions for current label.
util::make_error<int>("Could not find confidence predictions for label ", label); util::make_error<int>("Could not find confidence predictions for label ", label);
continue; continue;
} }
const std::vector<float>& scores = confidenceScores.find(label)->second; const std::vector<float>& scores = confidenceScores[label];
int locLabel = _shareLocation ? -1 : label; int locLabel = _shareLocation ? -1 : label;
if (decodeBBoxes.find(locLabel) == decodeBBoxes.end()) if (decodeBBoxes.find(locLabel) == decodeBBoxes.end())
{ {
@ -641,13 +641,14 @@ public:
// confidence prediction for an image. // confidence prediction for an image.
void GetConfidenceScores(const float* confData, const int num, void GetConfidenceScores(const float* confData, const int num,
const int numPredsPerClass, const int numClasses, 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->clear();
confPreds->resize(num); confPreds->resize(num);
for (int i = 0; i < num; ++i) 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) for (int p = 0; p < numPredsPerClass; ++p)
{ {
int startIdx = p * numClasses; int startIdx = p * numClasses;

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

@ -123,8 +123,9 @@ public:
for (size_t cnDim = 0; cnDim < channels; cnDim++) for (size_t cnDim = 0; cnDim < channels; cnDim++)
{ {
const int offset = srcOffset + cnDim * cnStep;
for (size_t i = 0; i < innerSize; i++) 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];
} }
} }
@ -141,22 +142,25 @@ public:
for (size_t cnDim = 0; cnDim < channels; cnDim++) for (size_t cnDim = 0; cnDim < channels; cnDim++)
{ {
const int offset = srcOffset + cnDim * cnStep;
for (size_t i = 0; i < innerSize; i++) 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 //divide by computed sum
for (size_t cnDim = 0; cnDim < channels; cnDim++) for (size_t cnDim = 0; cnDim < channels; cnDim++)
{ {
const int offset = srcOffset + cnDim * cnStep;
for (size_t i = 0; i < innerSize; i++) for (size_t i = 0; i < innerSize; i++)
dstPtr[srcOffset + cnDim * cnStep + i] /= bufPtr[bufOffset + i]; dstPtr[offset + i] /= bufPtr[bufOffset + i];
} }
if (logSoftMax) if (logSoftMax)
{ {
for (size_t cnDim = 0; cnDim < channels; cnDim++) for (size_t cnDim = 0; cnDim < channels; cnDim++)
{ {
const int offset = srcOffset + cnDim * cnStep;
for (size_t i = 0; i < innerSize; i++) 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]);
} }
} }
} }

Write Preview
Loading…
Cancel
Save