yolo_standard_libray/tensorrtx-master/rcnn/RpnNmsPlugin.h
2025-03-07 11:35:40 +08:00

198 lines
6.0 KiB
C++
Executable File

#pragma once
#include <NvInfer.h>
#include <vector>
#include <cassert>
#include "macros.h"
using namespace nvinfer1;
#define PLUGIN_NAME "RpnNms"
#define PLUGIN_VERSION "1"
#define PLUGIN_NAMESPACE ""
namespace nvinfer1 {
int rpnNms(int batchSize,
const void *const *inputs, void *TRT_CONST_ENQUEUE*outputs,
size_t pre_nms_topk, int post_nms_topk, float nms_thresh,
void *workspace, size_t workspace_size, cudaStream_t stream);
/*
input1: scores{C, 1} C->pre_nms_topk
input2: boxes{C, 4} C->pre_nms_topk format:XYXY
output1: boxes{C, 4} C->post_nms_topk format:XYXY
Description: implement rpn nms
*/
class RpnNmsPlugin : public IPluginV2Ext {
float _nms_thresh;
int _post_nms_topk;
size_t _pre_nms_topk = 1;
mutable int size = -1;
protected:
void deserialize(void const* data, size_t length) {
const char* d = static_cast<const char*>(data);
read(d, _nms_thresh);
read(d, _post_nms_topk);
read(d, _pre_nms_topk);
}
size_t getSerializationSize() const TRT_NOEXCEPT override {
return sizeof(_nms_thresh) + sizeof(_post_nms_topk)
+ sizeof(_pre_nms_topk);
}
void serialize(void *buffer) const TRT_NOEXCEPT override {
char* d = static_cast<char*>(buffer);
write(d, _nms_thresh);
write(d, _post_nms_topk);
write(d, _pre_nms_topk);
}
public:
RpnNmsPlugin(float nms_thresh, int post_nms_topk)
: _nms_thresh(nms_thresh), _post_nms_topk(post_nms_topk) {
assert(nms_thresh > 0);
assert(post_nms_topk > 0);
}
RpnNmsPlugin(float nms_thresh, int post_nms_topk, size_t pre_nms_topk)
: _nms_thresh(nms_thresh), _post_nms_topk(post_nms_topk), _pre_nms_topk(pre_nms_topk) {
assert(nms_thresh > 0);
assert(post_nms_topk > 0);
assert(pre_nms_topk > 0);
}
RpnNmsPlugin(void const* data, size_t length) {
this->deserialize(data, length);
}
const char *getPluginType() const TRT_NOEXCEPT override {
return PLUGIN_NAME;
}
const char *getPluginVersion() const TRT_NOEXCEPT override {
return PLUGIN_VERSION;
}
int getNbOutputs() const TRT_NOEXCEPT override {
return 1;
}
Dims getOutputDimensions(int index,
const Dims *inputs, int nbInputDims) TRT_NOEXCEPT override {
assert(nbInputDims == 2);
assert(index < this->getNbOutputs());
return Dims2(_post_nms_topk, 4);
}
bool supportsFormat(DataType type, PluginFormat format) const TRT_NOEXCEPT override {
return type == DataType::kFLOAT && format == PluginFormat::kLINEAR;
}
int initialize() TRT_NOEXCEPT override { return 0; }
void terminate() TRT_NOEXCEPT override {}
size_t getWorkspaceSize(int maxBatchSize) const TRT_NOEXCEPT override {
if (size < 0) {
size = rpnNms(maxBatchSize, nullptr, nullptr, _pre_nms_topk,
_post_nms_topk, _nms_thresh,
nullptr, 0, nullptr);
}
return size;
}
int enqueue(int batchSize,
const void *const *inputs, void *TRT_CONST_ENQUEUE*outputs,
void *workspace, cudaStream_t stream) TRT_NOEXCEPT override {
return rpnNms(batchSize, inputs, outputs, _pre_nms_topk,
_post_nms_topk, _nms_thresh,
workspace, getWorkspaceSize(batchSize), stream);
}
void destroy() TRT_NOEXCEPT override {
delete this;
}
const char *getPluginNamespace() const TRT_NOEXCEPT override {
return PLUGIN_NAMESPACE;
}
void setPluginNamespace(const char *N) TRT_NOEXCEPT override {
}
// IPluginV2Ext Methods
DataType getOutputDataType(int index, const DataType* inputTypes, int nbInputs) const TRT_NOEXCEPT override {
assert(index < 1);
return DataType::kFLOAT;
}
bool isOutputBroadcastAcrossBatch(int outputIndex, const bool* inputIsBroadcasted,
int nbInputs) const TRT_NOEXCEPT override {
return false;
}
bool canBroadcastInputAcrossBatch(int inputIndex) const TRT_NOEXCEPT override { return false; }
void configurePlugin(const Dims* inputDims, int nbInputs, const Dims* outputDims, int nbOutputs,
const DataType* inputTypes, const DataType* outputTypes, const bool* inputIsBroadcast,
const bool* outputIsBroadcast, PluginFormat floatFormat, int maxBatchSize) TRT_NOEXCEPT override {
assert(*inputTypes == nvinfer1::DataType::kFLOAT &&
floatFormat == nvinfer1::PluginFormat::kLINEAR);
assert(nbInputs == 2);
assert(inputDims[0].d[0] == inputDims[1].d[0]);
_pre_nms_topk = inputDims[0].d[0];
}
IPluginV2Ext *clone() const TRT_NOEXCEPT override {
return new RpnNmsPlugin(_nms_thresh, _post_nms_topk, _pre_nms_topk);
}
private:
template<typename T> void write(char*& buffer, const T& val) const {
*reinterpret_cast<T*>(buffer) = val;
buffer += sizeof(T);
}
template<typename T> void read(const char*& buffer, T& val) {
val = *reinterpret_cast<const T*>(buffer);
buffer += sizeof(T);
}
};
class RpnNmsPluginCreator : public IPluginCreator {
public:
RpnNmsPluginCreator() {}
const char *getPluginNamespace() const TRT_NOEXCEPT override {
return PLUGIN_NAMESPACE;
}
const char *getPluginName() const TRT_NOEXCEPT override {
return PLUGIN_NAME;
}
const char *getPluginVersion() const TRT_NOEXCEPT override {
return PLUGIN_VERSION;
}
IPluginV2 *deserializePlugin(const char *name, const void *serialData, size_t serialLength) TRT_NOEXCEPT override {
return new RpnNmsPlugin(serialData, serialLength);
}
void setPluginNamespace(const char *N) TRT_NOEXCEPT override {}
const PluginFieldCollection *getFieldNames() TRT_NOEXCEPT override { return nullptr; }
IPluginV2 *createPlugin(const char *name, const PluginFieldCollection *fc) TRT_NOEXCEPT override { return nullptr; }
};
REGISTER_TENSORRT_PLUGIN(RpnNmsPluginCreator);
} // namespace nvinfer1
#undef PLUGIN_NAME
#undef PLUGIN_VERSION
#undef PLUGIN_NAMESPACE