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BatchedNmsPlugin.h
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BatchedNmsPlugin.h
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#pragma once
#include <NvInfer.h>
#include <vector>
#include <cassert>
#include "macros.h"
using namespace nvinfer1;
#define PLUGIN_NAME "BatchedNms"
#define PLUGIN_VERSION "1"
#define PLUGIN_NAMESPACE ""
namespace nvinfer1 {
int batchedNms(int nms_method, int batchSize,
const void *const *inputs, void *TRT_CONST_ENQUEUE*outputs,
size_t count, int detections_per_im, float nms_thresh,
void *workspace, size_t workspace_size, cudaStream_t stream);
/*
input1: scores{C, 1} C->topk
input2: boxes{C, 4} C->topk format:XYXY
input3: classes{C, 1} C->topk
output1: scores{C, 1} C->detections_per_img
output2: boxes{C, 4} C->detections_per_img format:XYXY
output3: classes{C, 1} C->detections_per_img
Description: implement batched nms
*/
class BatchedNmsPlugin : public IPluginV2Ext {
int _nms_method;
float _nms_thresh;
int _detections_per_im;
size_t _count = 1;
protected:
void deserialize(void const* data, size_t length) {
const char* d = static_cast<const char*>(data);
read(d, _nms_method);
read(d, _nms_thresh);
read(d, _detections_per_im);
read(d, _count);
}
size_t getSerializationSize() const override {
return sizeof(_nms_method) + sizeof(_nms_thresh) + sizeof(_detections_per_im)
+ sizeof(_count);
}
void serialize(void *buffer) const TRT_NOEXCEPT override {
char* d = static_cast<char*>(buffer);
write(d, _nms_method);
write(d, _nms_thresh);
write(d, _detections_per_im);
write(d, _count);
}
public:
BatchedNmsPlugin(int nms_method, float nms_thresh, int detections_per_im)
: _nms_method(nms_method), _nms_thresh(nms_thresh), _detections_per_im(detections_per_im) {
assert(nms_method >= 0);
assert(nms_thresh > 0);
assert(detections_per_im > 0);
}
BatchedNmsPlugin(int nms_method, float nms_thresh, int detections_per_im, size_t count)
: _nms_method(nms_method), _nms_thresh(nms_thresh), _detections_per_im(detections_per_im), _count(count) {
assert(nms_method >= 0);
assert(nms_thresh > 0);
assert(detections_per_im > 0);
assert(count > 0);
}
BatchedNmsPlugin(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 3;
}
Dims getOutputDimensions(int index,
const Dims *inputs, int nbInputDims) TRT_NOEXCEPT override {
assert(nbInputDims == 3);
assert(index < this->getNbOutputs());
return Dims2(_detections_per_im, index == 1 ? 4 : 1);
}
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 {
static int size = -1;
if (size < 0) {
size = batchedNms(_nms_method, maxBatchSize, nullptr, nullptr, _count,
_detections_per_im, _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 batchedNms(_nms_method, batchSize, inputs, outputs, _count,
_detections_per_im, _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 < 3);
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 == 3);
assert(inputDims[0].d[0] == inputDims[2].d[0]);
assert(inputDims[1].d[0] == inputDims[2].d[0]);
_count = inputDims[0].d[0];
}
IPluginV2Ext *clone() const TRT_NOEXCEPT override {
return new BatchedNmsPlugin(_nms_method, _nms_thresh, _detections_per_im, _count);
}
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 BatchedNmsPluginCreator : public IPluginCreator {
public:
BatchedNmsPluginCreator() {}
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 BatchedNmsPlugin(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(BatchedNmsPluginCreator);
} // namespace nvinfer1
#undef PLUGIN_NAME
#undef PLUGIN_VERSION
#undef PLUGIN_NAMESPACE