thebears/deepstream_yolo
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Added YOLOR native support

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YOLOR-CSP
YOLOR-CSP*
YOLOR-CSP-X
YOLOR-CSP-X*
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unknown
2021-12-12 00:47:32 -03:00
parent 7761ca7a6b
commit e2257a81c0
12 changed files with 336 additions and 6 deletions
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45
nvdsinfer_custom_impl_Yolo/yolo.cpp
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@@ -187,6 +187,51 @@ NvDsInferStatus Yolo::buildYoloNetwork(
printLayerInfo(layerIndex, layerType, inputVol, outputVol, std::to_string(weightPtr));
}
else if (m_ConfigBlocks.at(i).at("type") == "implicit_add" || m_ConfigBlocks.at(i).at("type") == "implicit_mul") {
std::string type;
if (m_ConfigBlocks.at(i).at("type") == "implicit_add") {
type = "add";
}
else if (m_ConfigBlocks.at(i).at("type") == "implicit_mul") {
type = "mul";
}
assert(m_ConfigBlocks.at(i).find("filters") != m_ConfigBlocks.at(i).end());
int filters = std::stoi(m_ConfigBlocks.at(i).at("filters"));
nvinfer1::ILayer* out = implicitLayer(filters, weights, m_TrtWeights, weightPtr, &network);
previous = out->getOutput(0);
assert(previous != nullptr);
channels = getNumChannels(previous);
std::string outputVol = dimsToString(previous->getDimensions());
tensorOutputs.push_back(previous);
std::string layerType = "implicit_" + type;
printLayerInfo(layerIndex, layerType, " -", outputVol, std::to_string(weightPtr));
}
else if (m_ConfigBlocks.at(i).at("type") == "shift_channels" || m_ConfigBlocks.at(i).at("type") == "control_channels") {
std::string type;
if (m_ConfigBlocks.at(i).at("type") == "shift_channels") {
type = "shift";
}
else if (m_ConfigBlocks.at(i).at("type") == "control_channels") {
type = "control";
}
assert(m_ConfigBlocks.at(i).find("from") != m_ConfigBlocks.at(i).end());
int from = stoi(m_ConfigBlocks.at(i).at("from"));
if (from > 0) {
from = from - i + 1;
}
assert((i - 2 >= 0) && (i - 2 < tensorOutputs.size()));
assert((i + from - 1 >= 0) && (i + from - 1 < tensorOutputs.size()));
assert(i + from - 1 < i - 2);
nvinfer1::ILayer* out = channelsLayer(type, previous, tensorOutputs[i + from - 1], &network);
previous = out->getOutput(0);
assert(previous != nullptr);
std::string outputVol = dimsToString(previous->getDimensions());
tensorOutputs.push_back(previous);
std::string layerType = type + "_channels" + ": " + std::to_string(i + from - 1);
printLayerInfo(layerIndex, layerType, " -", outputVol, " -");
}
else if (m_ConfigBlocks.at(i).at("type") == "dropout") {
assert(m_ConfigBlocks.at(i).find("probability") != m_ConfigBlocks.at(i).end());
//float probability = std::stof(m_ConfigBlocks.at(i).at("probability"));