Yolov8 model on a custom dataset used as sgie returns Segmentation fault (core dumped)

Accelerated Computing Intelligent Video Analytics DeepStream SDK
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• Hardware Platform (Jetson / GPU) - GeForce RTX 2080 Ti
• DeepStream Version - 6.3
• TensorRT Version - 8.6.1
• NVIDIA GPU Driver Version (valid for GPU only) - 535.161.07

I trained a Yolov8n model on a custom dataset, for license plate detection and i want to use it as secondary model. Primary model was a Yolov8m too, from: DeepStream-Yolo/config_infer_primary_yoloV8.txt at master · marcoslucianops/DeepStream-Yolo · GitHub.

I get segmentation fault when i add my trained yolov8n for plates as secondary model in pipeline. I mention that i downloaded the .pt and convert it in .onnx same as for primary model python3 export_yoloV8.py -w yolov8s.pt --dynamic

This is pgie config

[property]
gpu-id=0
net-scale-factor=0.0039215697906911373
model-color-format=0
onnx-file=/opt/nvidia/deepstream/deepstream-6.3/sources/deepstream_python_apps/apps/DeepStream-Yolo/yolov8m.onnx
model-engine-file=/opt/nvidia/deepstream/deepstream-6.3/sources/deepstream_python_apps/apps/DeepStream-Yolo/model_b1_gpu0_fp32.engine
labelfile-path=labels.txt
filter-out-class-ids=1;4;6;8;9;10;11;12;13;14;15;16;17;18;19;20;21;22;23;24;25;26;27;28;29;30;31;32;33;34;35;36;37;38;39;40;41;42;43;44;45;46;47;48;49;50;51;52;53;54;55;56;57;58;59;60;61;62;63;64;65;66;67;68;69;70;71;72;73;74;75;76;77;78;79
batch-size=1
network-mode=0
num-detected-classes=80
interval=0
gie-unique-id=1
process-mode=1
network-type=0
cluster-mode=2
maintain-aspect-ratio=1
symmetric-padding=1
#workspace-size=2000
parse-bbox-func-name=NvDsInferParseYolo
#parse-bbox-func-name=NvDsInferParseYoloCuda
custom-lib-path=nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so
engine-create-func-name=NvDsInferYoloCudaEngineGet

[class-attrs-all]
nms-iou-threshold=0.45
pre-cluster-threshold=0.25
topk=300

and this is sgie config:

[property]
gpu-id=0
net-scale-factor=0.0039215697906911373
model-color-format=0
onnx-file=/opt/nvidia/deepstream/deepstream-6.3/sources/deepstream_python_apps/apps/DeepStream-Yolo/best.onnx
model-engine-file=lpr.onnx_b1_gpu0_fp32.engine
#int8-calib-file=calib.table
labelfile-path=labels.txt
batch-size=1
network-mode=0
num-detected-classes=1
interval=0
gie-unique-id=2
operate-on-gie-id=1
operate-on-class-ids=2
process-mode=1
network-type=3
cluster-mode=4
maintain-aspect-ratio=1
symmetric-padding=1
#workspace-size=2000
parse-bbox-instance-mask-func-name=NvDsInferParseYolo
#parse-bbox-func-name=NvDsInferParseYolo
custom-lib-path=nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so
#engine-create-func-name=NvDsInferYoloCudaEngineGet


[class-attrs-all]
pre-cluster-threshold=0.25
topk=300
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There is no update from you for a period, assuming this is not an issue any more. Hence we are closing this topic. If need further support, please open a new one. Thanks.

can you share the whole log? can you use gdb to get the crash stack?

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