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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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This commit is contained in:
Alexander Alekhin
2020-05-28 23:35:11 +00:00
parent d3aaf2d3a3 e58e545584
commit c3e8a82c9c
25 changed files with 837 additions and 73 deletions
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samples/dnn/object_detection.cpp
+47 -9
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@@ -45,7 +45,7 @@ std::vector<std::string> classes;
inline void preprocess(const Mat& frame, Net& net, Size inpSize, float scale,
const Scalar& mean, bool swapRB);
void postprocess(Mat& frame, const std::vector<Mat>& out, Net& net);
void postprocess(Mat& frame, const std::vector<Mat>& out, Net& net, int backend);
void drawPred(int classId, float conf, int left, int top, int right, int bottom, Mat& frame);
@@ -148,7 +148,8 @@ int main(int argc, char** argv)
// Load a model.
Net net = readNet(modelPath, configPath, parser.get<String>("framework"));
net.setPreferableBackend(parser.get<int>("backend"));
int backend = parser.get<int>("backend");
net.setPreferableBackend(backend);
net.setPreferableTarget(parser.get<int>("target"));
std::vector<String> outNames = net.getUnconnectedOutLayersNames();
@@ -245,7 +246,7 @@ int main(int argc, char** argv)
std::vector<Mat> outs = predictionsQueue.get();
Mat frame = processedFramesQueue.get();
postprocess(frame, outs, net);
postprocess(frame, outs, net, backend);
if (predictionsQueue.counter > 1)
{
@@ -285,7 +286,7 @@ int main(int argc, char** argv)
std::vector<Mat> outs;
net.forward(outs, outNames);
postprocess(frame, outs, net);
postprocess(frame, outs, net, backend);
// Put efficiency information.
std::vector<double> layersTimes;
@@ -319,7 +320,7 @@ inline void preprocess(const Mat& frame, Net& net, Size inpSize, float scale,
}
}
void postprocess(Mat& frame, const std::vector<Mat>& outs, Net& net)
void postprocess(Mat& frame, const std::vector<Mat>& outs, Net& net, int backend)
{
static std::vector<int> outLayers = net.getUnconnectedOutLayers();
static std::string outLayerType = net.getLayer(outLayers[0])->type;
@@ -396,11 +397,48 @@ void postprocess(Mat& frame, const std::vector<Mat>& outs, Net& net)
else
CV_Error(Error::StsNotImplemented, "Unknown output layer type: " + outLayerType);
std::vector<int> indices;
NMSBoxes(boxes, confidences, confThreshold, nmsThreshold, indices);
for (size_t i = 0; i < indices.size(); ++i)
// NMS is used inside Region layer only on DNN_BACKEND_OPENCV for another backends we need NMS in sample
// or NMS is required if number of outputs > 1
if (outLayers.size() > 1 || (outLayerType == "Region" && backend != DNN_BACKEND_OPENCV))
{
std::map<int, std::vector<size_t> > class2indices;
for (size_t i = 0; i < classIds.size(); i++)
{
if (confidences[i] >= confThreshold)
{
class2indices[classIds[i]].push_back(i);
}
}
std::vector<Rect> nmsBoxes;
std::vector<float> nmsConfidences;
std::vector<int> nmsClassIds;
for (std::map<int, std::vector<size_t> >::iterator it = class2indices.begin(); it != class2indices.end(); ++it)
{
std::vector<Rect> localBoxes;
std::vector<float> localConfidences;
std::vector<size_t> classIndices = it->second;
for (size_t i = 0; i < classIndices.size(); i++)
{
localBoxes.push_back(boxes[classIndices[i]]);
localConfidences.push_back(confidences[classIndices[i]]);
}
std::vector<int> nmsIndices;
NMSBoxes(localBoxes, localConfidences, confThreshold, nmsThreshold, nmsIndices);
for (size_t i = 0; i < nmsIndices.size(); i++)
{
size_t idx = nmsIndices[i];
nmsBoxes.push_back(localBoxes[idx]);
nmsConfidences.push_back(localConfidences[idx]);
nmsClassIds.push_back(it->first);
}
}
boxes = nmsBoxes;
classIds = nmsClassIds;
confidences = nmsConfidences;
}
for (size_t idx = 0; idx < boxes.size(); ++idx)
{
int idx = indices[i];
Rect box = boxes[idx];
drawPred(classIds[idx], confidences[idx], box.x, box.y,
box.x + box.width, box.y + box.height, frame);