Query on Multi-Camera Calibration Accuracy vs Unified ID Reassociation Stability in MV3DT

[nikhilahire5]

Hi Kesong,

Query on PeopleNet-Transformer model constantly misses bounding boxes - Calibration Accuracy vs Unified ID Reassociation Stability in MV3DT

I use TAO container to check the peoplenet_transformer model. Step: Login TAO5.0 container $ docker run --runtime=nvidia -it --rm --shm-size=96GB -v /localhome/local-morganh:/localhome/local-morganh nvcr.io/nvidia/tao/tao-toolkit:5.0.0-pyt /bin/bash Prepare infer.yaml results_dir: /localhome/local-morganh/peoplenet_transformer/results inference: conf_threshold: 0.2 #0.5 input_width: 960 input_height: 544 color_map: person: red face: blue bag: green dataset: infer…

Morganh has replied to my query on detection issue.

He referred, there is some detection issue for woman but I asked him whether detection issue from single person can cause change of unified ids for other passengers?

He asked me to check with you on this.

Kindly can you advise.