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deepstream_yolo/nvdsinfer_custom_impl_Yolo/nvdsparsebbox_Yolo_cuda.cu
2024-11-07 11:25:17 -03:00

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/*
* Copyright (c) 2018-2024, NVIDIA CORPORATION. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a
* copy of this software and associated documentation files (the "Software"),
* to deal in the Software without restriction, including without limitation
* the rights to use, copy, modify, merge, publish, distribute, sublicense,
* and/or sell copies of the Software, and to permit persons to whom the
* Software is furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
* THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
* DEALINGS IN THE SOFTWARE.
*
* Edited by Marcos Luciano
* https://www.github.com/marcoslucianops
*/
#include <thrust/host_vector.h>
#include <thrust/device_vector.h>
#include "nvdsinfer_custom_impl.h"
extern "C" bool
NvDsInferParseYoloCuda(std::vector<NvDsInferLayerInfo> const& outputLayersInfo, NvDsInferNetworkInfo const& networkInfo,
NvDsInferParseDetectionParams const& detectionParams, std::vector<NvDsInferParseObjectInfo>& objectList);
__global__ void decodeTensorYoloCuda(NvDsInferParseObjectInfo *binfo, const float* output, const uint outputSize,
const uint netW, const uint netH, const float* preclusterThreshold)
{
int x_id = blockIdx.x * blockDim.x + threadIdx.x;
if (x_id >= outputSize) {
return;
}
float maxProb = output[x_id * 6 + 4];
int maxIndex = (int) output[x_id * 6 + 5];
if (maxProb < preclusterThreshold[maxIndex]) {
binfo[x_id].detectionConfidence = 0.0;
return;
}
float bx1 = output[x_id * 6 + 0];
float by1 = output[x_id * 6 + 1];
float bx2 = output[x_id * 6 + 2];
float by2 = output[x_id * 6 + 3];
bx1 = fminf(float(netW), fmaxf(float(0.0), bx1));
by1 = fminf(float(netH), fmaxf(float(0.0), by1));
bx2 = fminf(float(netW), fmaxf(float(0.0), bx2));
by2 = fminf(float(netH), fmaxf(float(0.0), by2));
binfo[x_id].left = bx1;
binfo[x_id].top = by1;
binfo[x_id].width = fminf(float(netW), fmaxf(float(0.0), bx2 - bx1));
binfo[x_id].height = fminf(float(netH), fmaxf(float(0.0), by2 - by1));
binfo[x_id].detectionConfidence = maxProb;
binfo[x_id].classId = maxIndex;
}
static bool NvDsInferParseCustomYoloCuda(std::vector<NvDsInferLayerInfo> const& outputLayersInfo,
NvDsInferNetworkInfo const& networkInfo, NvDsInferParseDetectionParams const& detectionParams,
std::vector<NvDsInferParseObjectInfo>& objectList)
{
if (outputLayersInfo.empty()) {
std::cerr << "ERROR: Could not find output layer in bbox parsing" << std::endl;
return false;
}
const NvDsInferLayerInfo& output = outputLayersInfo[0];
const uint outputSize = output.inferDims.d[0];
thrust::device_vector<float> perClassPreclusterThreshold = detectionParams.perClassPreclusterThreshold;
thrust::device_vector<NvDsInferParseObjectInfo> objects(outputSize);
int threads_per_block = 1024;
int number_of_blocks = ((outputSize) / threads_per_block) + 1;
decodeTensorYoloCuda<<<number_of_blocks, threads_per_block>>>(
thrust::raw_pointer_cast(objects.data()), (float*) (output.buffer), outputSize, networkInfo.width,
networkInfo.height, thrust::raw_pointer_cast(perClassPreclusterThreshold.data()));
objectList.resize(outputSize);
thrust::copy(objects.begin(), objects.end(), objectList.begin());
return true;
}
extern "C" bool
NvDsInferParseYoloCuda(std::vector<NvDsInferLayerInfo> const& outputLayersInfo, NvDsInferNetworkInfo const& networkInfo,
NvDsInferParseDetectionParams const& detectionParams, std::vector<NvDsInferParseObjectInfo>& objectList)
{
return NvDsInferParseCustomYoloCuda(outputLayersInfo, networkInfo, detectionParams, objectList);
}
CHECK_CUSTOM_PARSE_FUNC_PROTOTYPE(NvDsInferParseYoloCuda);