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GPU Batched NMS

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This commit is contained in:
Marcos Luciano
2022-06-19 12:12:04 -03:00
parent f621c0f429
commit f80aa10cf2
6 changed files with 47 additions and 56 deletions
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56
nvdsinfer_custom_impl_Yolo/nvdsparsebbox_Yolo.cpp
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@@ -32,14 +32,11 @@
#include "yoloPlugins.h"
extern "C" bool NvDsInferParseYolo(
std::vector<NvDsInferLayerInfo> const& outputLayersInfo,
NvDsInferNetworkInfo const& networkInfo,
NvDsInferParseDetectionParams const& detectionParams,
std::vector<NvDsInferParseObjectInfo>& objectList);
std::vector<NvDsInferLayerInfo> const& outputLayersInfo, NvDsInferNetworkInfo const& networkInfo,
NvDsInferParseDetectionParams const& detectionParams, std::vector<NvDsInferParseObjectInfo>& objectList);
static NvDsInferParseObjectInfo convertBBox(
const float& bx1, const float& by1, const float& bx2,
const float& by2, const uint& netW, const uint& netH)
const float& bx1, const float& by1, const float& bx2, const float& by2, const uint& netW, const uint& netH)
{
NvDsInferParseObjectInfo b;
@@ -62,9 +59,8 @@ static NvDsInferParseObjectInfo convertBBox(
}
static void addBBoxProposal(
const float bx1, const float by1, const float bx2, const float by2,
const uint& netW, const uint& netH, const int maxIndex,
const float maxProb, std::vector<NvDsInferParseObjectInfo>& binfo)
const float bx1, const float by1, const float bx2, const float by2, const uint& netW, const uint& netH,
const int maxIndex, const float maxProb, std::vector<NvDsInferParseObjectInfo>& binfo)
{
NvDsInferParseObjectInfo bbi = convertBBox(bx1, by1, bx2, by2, netW, netH);
if (bbi.width < 1 || bbi.height < 1) return;
@@ -75,14 +71,11 @@ static void addBBoxProposal(
}
static std::vector<NvDsInferParseObjectInfo> decodeYoloTensor(
const int* counts, const float* boxes,
const float* scores, const float* classes,
const uint& netW, const uint& netH)
const int* counts, const float* boxes, const float* scores, const float* classes, const uint& netW, const uint& netH)
{
std::vector<NvDsInferParseObjectInfo> binfo;
uint numBoxes = counts[0];
for (uint b = 0; b < numBoxes; ++b)
{
float bx1 = boxes[b * 4 + 0];
@@ -99,10 +92,8 @@ static std::vector<NvDsInferParseObjectInfo> decodeYoloTensor(
}
static bool NvDsInferParseCustomYolo(
std::vector<NvDsInferLayerInfo> const& outputLayersInfo,
NvDsInferNetworkInfo const& networkInfo,
NvDsInferParseDetectionParams const& detectionParams,
std::vector<NvDsInferParseObjectInfo>& objectList,
std::vector<NvDsInferLayerInfo> const& outputLayersInfo, NvDsInferNetworkInfo const& networkInfo,
NvDsInferParseDetectionParams const& detectionParams, std::vector<NvDsInferParseObjectInfo>& objectList,
const uint &numClasses)
{
if (outputLayersInfo.empty())
@@ -113,28 +104,23 @@ static bool NvDsInferParseCustomYolo(
if (numClasses != detectionParams.numClassesConfigured)
{
std::cerr << "WARNING: Num classes mismatch. Configured: "
<< detectionParams.numClassesConfigured
std::cerr << "WARNING: Num classes mismatch. Configured: " << detectionParams.numClassesConfigured
<< ", detected by network: " << numClasses << std::endl;
}
std::vector<NvDsInferParseObjectInfo> objects;
for (uint idx = 0; idx < outputLayersInfo.size() / 4; ++idx)
{
const NvDsInferLayerInfo &counts = outputLayersInfo[idx * 4 + 0];
const NvDsInferLayerInfo &boxes = outputLayersInfo[idx * 4 + 1];
const NvDsInferLayerInfo &scores = outputLayersInfo[idx * 4 + 2];
const NvDsInferLayerInfo &classes = outputLayersInfo[idx * 4 + 3];
const NvDsInferLayerInfo &counts = outputLayersInfo[0];
const NvDsInferLayerInfo &boxes = outputLayersInfo[1];
const NvDsInferLayerInfo &scores = outputLayersInfo[2];
const NvDsInferLayerInfo &classes = outputLayersInfo[3];
std::vector<NvDsInferParseObjectInfo> outObjs =
decodeYoloTensor(
(const int*)(counts.buffer), (const float*)(boxes.buffer),
(const float*)(scores.buffer), (const float*)(classes.buffer),
networkInfo.width, networkInfo.height);
std::vector<NvDsInferParseObjectInfo> outObjs =
decodeYoloTensor(
(const int*)(counts.buffer), (const float*)(boxes.buffer), (const float*)(scores.buffer),
(const float*)(classes.buffer), networkInfo.width, networkInfo.height);
objects.insert(objects.end(), outObjs.begin(), outObjs.end());
}
objects.insert(objects.end(), outObjs.begin(), outObjs.end());
objectList = objects;
@@ -142,10 +128,8 @@ static bool NvDsInferParseCustomYolo(
}
extern "C" bool NvDsInferParseYolo(
std::vector<NvDsInferLayerInfo> const& outputLayersInfo,
NvDsInferNetworkInfo const& networkInfo,
NvDsInferParseDetectionParams const& detectionParams,
std::vector<NvDsInferParseObjectInfo>& objectList)
std::vector<NvDsInferLayerInfo> const& outputLayersInfo, NvDsInferNetworkInfo const& networkInfo,
NvDsInferParseDetectionParams const& detectionParams, std::vector<NvDsInferParseObjectInfo>& objectList)
{
int num_classes = kNUM_CLASSES;