Please provide complete information as applicable to your setup.
**• Hardware Platform (Jetson / GPU)**Xavier
• DeepStream Version5
• 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)
In ultralytics/yolov5, use (python models/export.py --weights yolov5s.pt --img 640 --batch 1 ) to get onnx, And with config.txt
[property]
gpu-id=0
net-scale-factor=0.0039215697906911373
model-color-format=0
onnx-file=/home/nvidia/nvme/zhangsishuai.onnx
model-engine-file=/home/nvidia/nvme/zhangsishuai.onnx_b1_gpu0_fp16.engine.enc
labelfile-path=/home/nvidia/nvme/model/person/person.txt
batch-size=1
gie-unique-id=40001
#output-blob-names=prob
process-mode=1
0=FP32, 1=INT8, 2=FP16 mode
network-mode=2
num-detected-classes=80
interval=0
cluster-mode=2
maintain-aspect-ratio=1
output-tensor-meta=0
secondary-reinfer-interval=0
force-implicit-batch-dim=0
parse-bbox-func-name=NvDsInferParseCustomYoloV5
engine-create-func-name=BuildCustomYOLOv5Engine
custom-lib-path=/opt/nvidia/deepstream/deepstream-5.0/sources/libs/nvdsinfer_customparser/libnvds_infercustomparser.so
[class-attrs-all]
pre-cluster-threshold=0.2
post-cluster-threshold=0.3
parsebbox code is
Yolov5-in-Deepstream-5.0/nvdsparsebbox_Yolo.cpp at master · DanaHan/Yolov5-in-Deepstream-5.0 (github.com)
But after nms, the object is 0?
I observed that the output layer is：
1 OUTPUT kFLOAT 397 3x80x80x85
2 OUTPUT kFLOAT 458 3x40x40x85
3 OUTPUT kFLOAT 519 3x20x20x85
4 OUTPUT kFLOAT 561 25200x85
and used just one layer in code,