Using custom model in deepstream

[Fiona.Chen]

@vinaygouda.ttssl

it was yolov8 model converted into engine file

@vinaygouda.ttssl

[property]
gpu-id=0
net-scale-factor=0.00392156862745098
tlt-model-key=tlt_encode
tlt-encoded-model=…/…/…/…/samples/models/Primary_Detector/resnet18_trafficcamnet.etlt
model-engine-file=…/…/…/…/samples/models/Primary_Detector/resnet18_trafficcamnet.etlt_b1_gpu0_int8.engine
#model-engine-file=/home/trinity/AIML
labelfile-path=…/…/…/…/samples/models/Primary_Detector/labels.txt
#labelfile-path=/opt/nvidia/deepstream/deepstream-7.0/sources/deepstream_python_apps/apps/deepstream-test1/labels.txt
int8-calib-file=…/…/…/…/samples/models/Primary_Detector/cal_trt.bin
force-implicit-batch-dim=1
batch-size=1
process-mode=1
model-color-format=0

You didn’t set the yolo model in the configuration file.

Please refer to DeepStream SDK FAQ - Intelligent Video Analytics / DeepStream SDK - NVIDIA Developer Forums for how to configure the gst-nvinfer with your model.

As to our experience, you need to customize the yolov8 postprocessing function by yourself.