#ifndef _YOLO_LAYER_H #define _YOLO_LAYER_H #include #include #include "NvInfer.h" namespace Yolo { static constexpr int CHECK_COUNT = 3; static constexpr float IGNORE_THRESH = 0.1f; struct YoloKernel { int width; int height; float anchors[CHECK_COUNT * 2]; }; static constexpr int MAX_OUTPUT_BBOX_COUNT = 1000; static constexpr int CLASS_NUM = 13; static constexpr int INPUT_H = 384; static constexpr int INPUT_W = 640; static constexpr int IMG_H = 360; static constexpr int IMG_W = 640; // static constexpr int INPUT_H = 192; // static constexpr int INPUT_W = 320; // static constexpr int IMG_H = 180; // static constexpr int IMG_W = 320; static constexpr int LOCATIONS = 4; struct alignas(float) Detection { //center_x center_y w h float bbox[LOCATIONS]; float conf; // bbox_conf * cls_conf float class_id; }; } namespace nvinfer1 { class YoloLayerPlugin : public IPluginV2IOExt { public: YoloLayerPlugin(int classCount, int netWidth, int netHeight, int maxOut, const std::vector& vYoloKernel); YoloLayerPlugin(const void* data, size_t length); ~YoloLayerPlugin(); int getNbOutputs() const override { return 1; } Dims getOutputDimensions(int index, const Dims* inputs, int nbInputDims) override; int initialize() override; virtual void terminate() override {}; virtual size_t getWorkspaceSize(int maxBatchSize) const override { return 0; } virtual int enqueue(int batchSize, const void*const * inputs, void** outputs, void* workspace, cudaStream_t stream) override; virtual size_t getSerializationSize() const override; virtual void serialize(void* buffer) const override; bool supportsFormatCombination(int pos, const PluginTensorDesc* inOut, int nbInputs, int nbOutputs) const override { return inOut[pos].format == TensorFormat::kLINEAR && inOut[pos].type == DataType::kFLOAT; } const char* getPluginType() const override; const char* getPluginVersion() const override; void destroy() override; IPluginV2IOExt* clone() const override; void setPluginNamespace(const char* pluginNamespace) override; const char* getPluginNamespace() const override; DataType getOutputDataType(int index, const nvinfer1::DataType* inputTypes, int nbInputs) const override; bool isOutputBroadcastAcrossBatch(int outputIndex, const bool* inputIsBroadcasted, int nbInputs) const override; bool canBroadcastInputAcrossBatch(int inputIndex) const override; void attachToContext( cudnnContext* cudnnContext, cublasContext* cublasContext, IGpuAllocator* gpuAllocator) override; void configurePlugin(const PluginTensorDesc* in, int nbInput, const PluginTensorDesc* out, int nbOutput) override; void detachFromContext() override; private: void forwardGpu(const float *const * inputs, float * output, cudaStream_t stream, int batchSize = 1); int mThreadCount = 256; const char* mPluginNamespace; int mKernelCount; int mClassCount; int mYoloV5NetWidth; int mYoloV5NetHeight; int mMaxOutObject; std::vector mYoloKernel; void** mAnchor; }; class YoloPluginCreator : public IPluginCreator { public: YoloPluginCreator(); ~YoloPluginCreator() override = default; const char* getPluginName() const override; const char* getPluginVersion() const override; const PluginFieldCollection* getFieldNames() override; IPluginV2IOExt* createPlugin(const char* name, const PluginFieldCollection* fc) override; IPluginV2IOExt* deserializePlugin(const char* name, const void* serialData, size_t serialLength) override; void setPluginNamespace(const char* libNamespace) override { mNamespace = libNamespace; } const char* getPluginNamespace() const override { return mNamespace.c_str(); } private: std::string mNamespace; static PluginFieldCollection mFC; static std::vector mPluginAttributes; }; REGISTER_TENSORRT_PLUGIN(YoloPluginCreator); }; #endif