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Add YOLO-NAS and ONNX support

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This commit is contained in:
Marcos Luciano
2023-05-14 15:07:22 -03:00
parent b4e2dbdcf8
commit 801e094321
7 changed files with 21 additions and 21 deletions
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2
config_infer_primary_yoloV5_onnx.txt
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@@ -16,7 +16,7 @@ network-type=0
cluster-mode=2
maintain-aspect-ratio=1
symmetric-padding=1
parse-bbox-func-name=NvDsInferParseYolo_ONNX
parse-bbox-func-name=NvDsInferParse_YOLO_ONNX
custom-lib-path=nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so
[class-attrs-all]

2
config_infer_primary_yoloV6_onnx.txt
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@@ -16,7 +16,7 @@ network-type=0
cluster-mode=2
maintain-aspect-ratio=1
symmetric-padding=1
parse-bbox-func-name=NvDsInferParseYolo_ONNX
parse-bbox-func-name=NvDsInferParse_YOLO_ONNX
custom-lib-path=nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so
[class-attrs-all]

2
config_infer_primary_yoloV7_onnx.txt
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@@ -16,7 +16,7 @@ network-type=0
cluster-mode=2
maintain-aspect-ratio=1
symmetric-padding=1
parse-bbox-func-name=NvDsInferParseYolo_ONNX
parse-bbox-func-name=NvDsInferParse_YOLO_ONNX
custom-lib-path=nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so
[class-attrs-all]

2
config_infer_primary_yoloV8_onnx.txt
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@@ -16,7 +16,7 @@ network-type=0
cluster-mode=2
maintain-aspect-ratio=1
symmetric-padding=1
parse-bbox-func-name=NvDsInferParseYoloV8_ONNX
parse-bbox-func-name=NvDsInferParse_YOLOV8_ONNX
custom-lib-path=nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so
[class-attrs-all]

2
config_infer_primary_yolox_legacy_onnx.txt
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@@ -17,7 +17,7 @@ network-type=0
cluster-mode=2
maintain-aspect-ratio=1
symmetric-padding=0
parse-bbox-func-name=NvDsInferParseYoloX_ONNX
parse-bbox-func-name=NvDsInferParse_YOLOX_ONNX
custom-lib-path=nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so
[class-attrs-all]

2
config_infer_primary_yolox_onnx.txt
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@@ -16,7 +16,7 @@ network-type=0
cluster-mode=2
maintain-aspect-ratio=1
symmetric-padding=0
parse-bbox-func-name=NvDsInferParseYoloX_ONNX
parse-bbox-func-name=NvDsInferParse_YOLOX_ONNX
custom-lib-path=nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so
[class-attrs-all]

30
nvdsinfer_custom_impl_Yolo/nvdsparsebbox_Yolo_cuda.cu
View File

@@ -31,7 +31,7 @@
#include "utils.h"
#include "yoloPlugins.h"
__global__ void decodeTensorYolo_ONNX(NvDsInferParseObjectInfo *binfo, const float* detections, const int numClasses,
__global__ void decodeTensor_YOLO_ONNX(NvDsInferParseObjectInfo *binfo, const float* detections, const int numClasses,
const int outputSize, float netW, float netH)
{
uint x_id = blockIdx.x * blockDim.x + threadIdx.x;
@@ -74,7 +74,7 @@ __global__ void decodeTensorYolo_ONNX(NvDsInferParseObjectInfo *binfo, const flo
binfo[x_id].classId = maxIndex;
}
__global__ void decodeTensorYoloV8_ONNX(NvDsInferParseObjectInfo *binfo, const float* detections, const int numClasses,
__global__ void decodeTensor_YOLOV8_ONNX(NvDsInferParseObjectInfo *binfo, const float* detections, const int numClasses,
const int outputSize, float netW, float netH)
{
uint x_id = blockIdx.x * blockDim.x + threadIdx.x;
@@ -115,7 +115,7 @@ __global__ void decodeTensorYoloV8_ONNX(NvDsInferParseObjectInfo *binfo, const f
binfo[x_id].classId = maxIndex;
}
__global__ void decodeTensorYoloX_ONNX(NvDsInferParseObjectInfo *binfo, const float* detections, const int numClasses,
__global__ void decodeTensor_YOLOX_ONNX(NvDsInferParseObjectInfo *binfo, const float* detections, const int numClasses,
const int outputSize, float netW, float netH, const int *grid0, const int *grid1, const int *strides)
{
uint x_id = blockIdx.x * blockDim.x + threadIdx.x;
@@ -233,7 +233,7 @@ __global__ void decodeTensor_PPYOLOE_ONNX(NvDsInferParseObjectInfo *binfo, const
}
static bool
NvDsInferParseCustomYolo_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayersInfo,
NvDsInferParseCustom_YOLO_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayersInfo,
NvDsInferNetworkInfo const& networkInfo, NvDsInferParseDetectionParams const& detectionParams,
std::vector<NvDsInferParseObjectInfo>& objectList)
{
@@ -257,7 +257,7 @@ NvDsInferParseCustomYolo_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayer
int threads_per_block = 1024;
int number_of_blocks = ((outputSize - 1) / threads_per_block) + 1;
decodeTensorYolo_ONNX<<<threads_per_block, number_of_blocks>>>(
decodeTensor_YOLO_ONNX<<<threads_per_block, number_of_blocks>>>(
thrust::raw_pointer_cast(objects.data()), (const float*) (layer.buffer), numClasses, outputSize,
static_cast<float>(networkInfo.width), static_cast<float>(networkInfo.height));
@@ -268,7 +268,7 @@ NvDsInferParseCustomYolo_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayer
}
static bool
NvDsInferParseCustomYoloV8_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayersInfo,
NvDsInferParseCustom_YOLOV8_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayersInfo,
NvDsInferNetworkInfo const& networkInfo, NvDsInferParseDetectionParams const& detectionParams,
std::vector<NvDsInferParseObjectInfo>& objectList)
{
@@ -292,7 +292,7 @@ NvDsInferParseCustomYoloV8_ONNX(std::vector<NvDsInferLayerInfo> const& outputLay
int threads_per_block = 1024;
int number_of_blocks = ((outputSize - 1) / threads_per_block) + 1;
decodeTensorYoloV8_ONNX<<<threads_per_block, number_of_blocks>>>(
decodeTensor_YOLOV8_ONNX<<<threads_per_block, number_of_blocks>>>(
thrust::raw_pointer_cast(objects.data()), (const float*) (layer.buffer), numClasses, outputSize,
static_cast<float>(networkInfo.width), static_cast<float>(networkInfo.height));
@@ -303,7 +303,7 @@ NvDsInferParseCustomYoloV8_ONNX(std::vector<NvDsInferLayerInfo> const& outputLay
}
static bool
NvDsInferParseCustomYoloX_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayersInfo,
NvDsInferParseCustom_YOLOX_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayersInfo,
NvDsInferNetworkInfo const& networkInfo, NvDsInferParseDetectionParams const& detectionParams,
std::vector<NvDsInferParseObjectInfo>& objectList)
{
@@ -349,7 +349,7 @@ NvDsInferParseCustomYoloX_ONNX(std::vector<NvDsInferLayerInfo> const& outputLaye
int threads_per_block = 1024;
int number_of_blocks = ((outputSize - 1) / threads_per_block) + 1;
decodeTensorYoloX_ONNX<<<threads_per_block, number_of_blocks>>>(
decodeTensor_YOLOX_ONNX<<<threads_per_block, number_of_blocks>>>(
thrust::raw_pointer_cast(objects.data()), (const float*) (layer.buffer), numClasses, outputSize,
static_cast<float>(networkInfo.width), static_cast<float>(networkInfo.height),
thrust::raw_pointer_cast(d_grid0.data()), thrust::raw_pointer_cast(d_grid1.data()),
@@ -434,24 +434,24 @@ NvDsInferParseCustom_PPYOLOE_ONNX(std::vector<NvDsInferLayerInfo> const& outputL
}
extern "C" bool
NvDsInferParseYolo_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayersInfo, NvDsInferNetworkInfo const& networkInfo,
NvDsInferParse_YOLO_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayersInfo, NvDsInferNetworkInfo const& networkInfo,
NvDsInferParseDetectionParams const& detectionParams, std::vector<NvDsInferParseObjectInfo>& objectList)
{
return NvDsInferParseCustomYolo_ONNX(outputLayersInfo, networkInfo, detectionParams, objectList);
return NvDsInferParseCustom_YOLO_ONNX(outputLayersInfo, networkInfo, detectionParams, objectList);
}
extern "C" bool
NvDsInferParseYoloV8_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayersInfo, NvDsInferNetworkInfo const& networkInfo,
NvDsInferParse_YOLOV8_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayersInfo, NvDsInferNetworkInfo const& networkInfo,
NvDsInferParseDetectionParams const& detectionParams, std::vector<NvDsInferParseObjectInfo>& objectList)
{
return NvDsInferParseCustomYoloV8_ONNX(outputLayersInfo, networkInfo, detectionParams, objectList);
return NvDsInferParseCustom_YOLOV8_ONNX(outputLayersInfo, networkInfo, detectionParams, objectList);
}
extern "C" bool
NvDsInferParseYoloX_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayersInfo, NvDsInferNetworkInfo const& networkInfo,
NvDsInferParse_YOLOX_ONNX(std::vector<NvDsInferLayerInfo> const& outputLayersInfo, NvDsInferNetworkInfo const& networkInfo,
NvDsInferParseDetectionParams const& detectionParams, std::vector<NvDsInferParseObjectInfo>& objectList)
{
return NvDsInferParseCustomYoloX_ONNX(outputLayersInfo, networkInfo, detectionParams, objectList);
return NvDsInferParseCustom_YOLOX_ONNX(outputLayersInfo, networkInfo, detectionParams, objectList);
}
extern "C" bool