From 9b1532d86c2cf48a63017f3460897d8d14b98b60 Mon Sep 17 00:00:00 2001
From: Scheaven <xuepengqiang>
Date: 星期三, 08 九月 2021 17:45:25 +0800
Subject: [PATCH] coding
---
src/detecter_tools/trt_utils.h | 76 +++++++++++++++++++++++++++++++++++++-
1 files changed, 74 insertions(+), 2 deletions(-)
diff --git a/src/detecter_tools/trt_utils.h b/src/detecter_tools/trt_utils.h
index 189a60b..a166a6f 100644
--- a/src/detecter_tools/trt_utils.h
+++ b/src/detecter_tools/trt_utils.h
@@ -67,6 +67,34 @@
}
}
};
+nvinfer1::ILayer* netAddMaxpool(int layerIdx, std::map<std::string, std::string>& block,
+ nvinfer1::ITensor* input, nvinfer1::INetworkDefinition* network);
+nvinfer1::ILayer* netAddConvLinear(int layerIdx, std::map<std::string, std::string>& block,
+ std::vector<float>& weights,
+ std::vector<nvinfer1::Weights>& trtWeights, int& weightPtr,
+ int& inputChannels, nvinfer1::ITensor* input,
+ nvinfer1::INetworkDefinition* network);
+
+nvinfer1::ILayer* net_conv_bn_mish(int layerIdx,
+ std::map<std::string, std::string>& block,
+ std::vector<float>& weights,
+ std::vector<nvinfer1::Weights>& trtWeights,
+ int& weightPtr,
+ int& inputChannels,
+ nvinfer1::ITensor* input,
+ nvinfer1::INetworkDefinition* network);
+
+nvinfer1::ILayer* netAddConvBNLeaky(int layerIdx, std::map<std::string, std::string>& block,
+ std::vector<float>& weights,
+ std::vector<nvinfer1::Weights>& trtWeights, int& weightPtr,
+ int& inputChannels, nvinfer1::ITensor* input,
+ nvinfer1::INetworkDefinition* network);
+std::string dimsToString(const nvinfer1::Dims d);
+std::vector<float> loadWeights(const std::string weightsFilePath, const std::string& networkType);
+int getNumChannels(nvinfer1::ITensor* t);
+std::string trim(std::string s);
+std::string triml(std::string s, const char* t);
+std::string trimr(std::string s, const char* t);
float clamp(const float val, const float minVal, const float maxVal);
// Common helper functions
cv::Mat blobFromDsImages(const std::vector<DsImage>& inputImages, const int& inputH,
@@ -77,9 +105,53 @@
nvinfer1::ICudaEngine* loadTRTEngine(const std::string planFilePath, PluginFactory* pluginFactory,
Logger& logger);
uint64_t get3DTensorVolume(nvinfer1::Dims inputDims);
-
+std::vector<std::string> loadImageList(const std::string filename, const std::string prefix);
std::vector<BBoxInfo> nmsAllClasses(const float nmsThresh, std::vector<BBoxInfo>& binfo,
const uint32_t numClasses, const std::string &model_type);
-
+void printLayerInfo(std::string layerIndex, std::string layerName, std::string layerInput,
+ std::string layerOutput, std::string weightPtr);
std::vector<BBoxInfo> nonMaximumSuppression(const float nmsThresh, std::vector<BBoxInfo> binfo);
+std::vector<int> split_layer_index(const std::string &s_,const std::string &delimiter_);
+nvinfer1::ILayer * layer_split(const int n_layer_index_,
+ nvinfer1::ITensor *input_,
+ nvinfer1::INetworkDefinition* network);
+nvinfer1::ILayer* netAddUpsample(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);
+std::vector<std::string> loadListFromTextFile(const std::string filename);
+class YoloTinyMaxpoolPaddingFormula : public nvinfer1::IOutputDimensionsFormula
+{
+private:
+ std::set<std::string> m_SamePaddingLayers;
+
+ nvinfer1::DimsHW compute(nvinfer1::DimsHW inputDims, nvinfer1::DimsHW kernelSize,
+ nvinfer1::DimsHW stride, nvinfer1::DimsHW padding,
+ nvinfer1::DimsHW dilation, const char* layerName) const override
+ {
+ // assert(inputDims.d[0] == inputDims.d[1]);
+ assert(kernelSize.d[0] == kernelSize.d[1]);
+ assert(stride.d[0] == stride.d[1]);
+ assert(padding.d[0] == padding.d[1]);
+
+ int output_h, output_w;
+ // Only layer maxpool_12 makes use of same padding
+ if (m_SamePaddingLayers.find(layerName) != m_SamePaddingLayers.end())
+ {
+ output_h = (inputDims.d[0] + 2 * padding.d[0]) / stride.d[0];
+ output_w = (inputDims.d[1] + 2 * padding.d[1]) / stride.d[1];
+ }
+ // Valid Padding
+ else
+ {
+ output_h = (inputDims.d[0] - kernelSize.d[0]) / stride.d[0] + 1;
+ output_w = (inputDims.d[1] - kernelSize.d[1]) / stride.d[1] + 1;
+ }
+ return nvinfer1::DimsHW{output_h, output_w};
+ }
+
+public:
+ void addSamePaddingLayer(std::string input) { m_SamePaddingLayers.insert(input); }
+};
+
#endif
--
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