thebears/deepstream_yolo
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

New features

Browse Source 
- Added support for INT8 calibration
- Added support for non square models
- Updated mAP comparison between models
This commit is contained in:
Marcos Luciano
2021-06-18 00:30:10 -03:00
parent 312e9a448d
commit cbd9675dc2
74 changed files with 3287 additions and 700 deletions
Download Patch File Download Diff File Expand all files Collapse all files

76
native/nvdsinfer_custom_impl_Yolo/layers/upsample_layer.cpp
View File

@@ -8,79 +8,17 @@
nvinfer1::ILayer* upsampleLayer(
int layerIdx,
std::map<std::string, std::string>& block,
std::vector<float>& weights,
std::vector<nvinfer1::Weights>& trtWeights,
int& inputChannels,
nvinfer1::ITensor* input,
nvinfer1::INetworkDefinition* network)
{
assert(block.at("type") == "upsample");
nvinfer1::Dims inpDims = input->getDimensions();
assert(inpDims.nbDims == 3);
assert(inpDims.d[1] == inpDims.d[2]);
int h = inpDims.d[1];
int w = inpDims.d[2];
int stride = std::stoi(block.at("stride"));
nvinfer1::Dims preDims{3,
{1, stride * h, w},
{nvinfer1::DimensionType::kCHANNEL, nvinfer1::DimensionType::kSPATIAL,
nvinfer1::DimensionType::kSPATIAL}};
int size = stride * h * w;
nvinfer1::Weights preMul{nvinfer1::DataType::kFLOAT, nullptr, size};
float* preWt = new float[size];
for (int i = 0, idx = 0; i < h; ++i)
{
for (int s = 0; s < stride; ++s)
{
for (int j = 0; j < w; ++j, ++idx)
{
preWt[idx] = (i == j) ? 1.0 : 0.0;
}
}
}
preMul.values = preWt;
trtWeights.push_back(preMul);
nvinfer1::IConstantLayer* preM = network->addConstant(preDims, preMul);
assert(preM != nullptr);
std::string preLayerName = "preMul_" + std::to_string(layerIdx);
preM->setName(preLayerName.c_str());
nvinfer1::Dims postDims{3,
{1, h, stride * w},
{nvinfer1::DimensionType::kCHANNEL, nvinfer1::DimensionType::kSPATIAL,
nvinfer1::DimensionType::kSPATIAL}};
size = stride * h * w;
nvinfer1::Weights postMul{nvinfer1::DataType::kFLOAT, nullptr, size};
float* postWt = new float[size];
for (int i = 0, idx = 0; i < h; ++i)
{
for (int j = 0; j < stride * w; ++j, ++idx)
{
postWt[idx] = (j / stride == i) ? 1.0 : 0.0;
}
}
postMul.values = postWt;
trtWeights.push_back(postMul);
nvinfer1::IConstantLayer* post_m = network->addConstant(postDims, postMul);
assert(post_m != nullptr);
std::string postLayerName = "postMul_" + std::to_string(layerIdx);
post_m->setName(postLayerName.c_str());
nvinfer1::IMatrixMultiplyLayer* mm1
= network->addMatrixMultiply(*preM->getOutput(0), nvinfer1::MatrixOperation::kNONE, *input,
nvinfer1::MatrixOperation::kNONE);
assert(mm1 != nullptr);
std::string mm1LayerName = "mm1_" + std::to_string(layerIdx);
mm1->setName(mm1LayerName.c_str());
nvinfer1::IMatrixMultiplyLayer* mm2
= network->addMatrixMultiply(*mm1->getOutput(0), nvinfer1::MatrixOperation::kNONE,
*post_m->getOutput(0), nvinfer1::MatrixOperation::kNONE);
assert(mm2 != nullptr);
std::string mm2LayerName = "mm2_" + std::to_string(layerIdx);
mm2->setName(mm2LayerName.c_str());
return mm2;
nvinfer1::IResizeLayer* resize_layer = network->addResize(*input);
resize_layer->setResizeMode(nvinfer1::ResizeMode::kNEAREST);
float scale[3] = {1, stride, stride};
resize_layer->setScales(scale, 3);
std::string layer_name = "upsample_" + std::to_string(layerIdx);
resize_layer->setName(layer_name.c_str());
return resize_layer;
}

3
native/nvdsinfer_custom_impl_Yolo/layers/upsample_layer.h
View File

@@ -15,9 +15,6 @@
nvinfer1::ILayer* upsampleLayer(
int layerIdx,
std::map<std::string, std::string>& block,
std::vector<float>& weights,
std::vector<nvinfer1::Weights>& trtWeights,
int& inputChannels,
nvinfer1::ITensor* input,
nvinfer1::INetworkDefinition* network);