Can't deepstream-test3 output the results of multiple channels at the same time?

[autodrive2022]

• deepstream-app version 6.1.0
• DeepStreamSDK 6.1.0
• CUDA Driver Version: 11.4
• CUDA Runtime Version: 11.0
• TensorRT Version: 8.2
• cuDNN Version: 8.4
• libNVWarp360 Version: 2.0.1d3

1. Question: When I was using deepstream-test3 for multiple video detection, I found that there was no way to output the correct results of each video channel at the same time.
2. The problem: The results of the four channels are jumping from channel 1 to channel 2. Normally, all four channels should have test results at the same time, but it is not the case.
3. Test: I did not modify the code of deepstream-test3. I have observed the needle feeding the nfinfer and it is feeding all four frames at the same time.

config_infer_primary.txt：

[property]
gpu-id=0
net-scale-factor=0.0039215697906911373
model-color-format=0
custom-network-config=yolov5s.cfg
model-file=yolov5s.wts
model-engine-file=model_b4_gpu0_fp32.engine
#int8-calib-file=calib.table
labelfile-path=labels.txt
batch-size=4
network-mode=0
num-detected-classes=80
interval=0
gie-unique-id=1
process-mode=1
network-type=0
cluster-mode=4
maintain-aspect-ratio=0
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

[autodrive2022]

I solved the problem！
Thanks for the official reminder in my other question.
The problem is really due to the fact that my engine model may not support dynamic batchsize setting
I modified it to re-survive the engine and it loaded with no problems at all, and fixed what seemed to be a target ghosting problem.

[Amycao]

Glad to know.