运行自己训练的模型出错

我将自己训练好的模型文件进行了转换,生成了.engine文件,然后编写了config_infer_primary.txt文件和deepstream_app_config.txt文件,但是我在运行时却出现了如下问题,这是怎么回事 呢?
Deserialize yoloLayer plugin: (Unnamed Layer* 269) [PluginV2IOExt]
Segmentation fault (core dumped)

Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU)
• DeepStream Version
• JetPack Version (valid for Jetson only)
• TensorRT Version
• NVIDIA GPU Driver Version (valid for GPU only)
• Issue Type( questions, new requirements, bugs)
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)
• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description)
• The pipeline being used

Can you specify more details? like which app you are using? and which model used?

我用的是基于yolov5自己训练的模型,现在我可以将程序运行起来了,但是什么都检测不到,出现了如下的问题

这是我的配置文件,我是用yolov5s.engine的时候也是什么都检测不到,我怀疑需要修改nvdsinfer_custom_impl_Yolo中的配置信息,但是我不知道该如何修改
[property]
gpu-id=0
net-scale-factor=0.0039215697906911373
model-color-format=0
model-engine-file=gang.engine
#model-engine-file=yolov5s.engine
#model-engine-file=model_b1_gpu0_fp32.engine
#int8-calib-file=calib.table
labelfile-path=labels.txt
batch-size=1
network-mode=0
num-detected-classes=12
interval=0
gie-unique-id=1
process-mode=1
network-type=0
cluster-mode=2
maintain-aspect-ratio=1
parse-bbox-func-name=NvDsInferParseYolo
#custom-lib-path=nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so
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

Can you confirm your model is working well?

We will support yolov5 in upcoming release. if you are in urgent, you need to add post processing for yolov5 model.