TAO's other application with Peoplenet

Is it possible to use Peoplenet model as PGIE and BodyPoseNet as sgie. At customer place we have requirement to detect person and bags so we want to stick to peoplent and top of it want to use bodyposenet. ?

It is possible. deepstream_tao_apps/apps/tao_others/deepstream-bodypose2d-app at release/tao3.0 · NVIDIA-AI-IOT/deepstream_tao_apps · GitHub can be leveraged.

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Hi @Morganh I am following same git link and after using PGIE for person detection and SGIE for BodyPoseNet we are getting following output. I tried to bind Bodyposenet lines inside person’s bounding boxes but not able to succeed. Can you please help.

Can you try to crop the “Person” image and feed into BodyPoseNet to check if it works?

./deepstream-bodypose2d-app 2 ../../../configs/bodypose2d_tao/sample_bodypose2d_model_config.txt file:///person.png ./body2dout

@Morganh is there any sample available for BodyPoseNet just like test5 app’s message broker ?

Hi Priti,
Currently, there is only deepstream_tao_apps/apps/tao_others/deepstream-bodypose2d-app at release/tao3.0 · NVIDIA-AI-IOT/deepstream_tao_apps · GitHub for BodyPoseNet

More, one correction for my comment.
Ii is not suggested to use Peoplenet model as PGIE and BodyPoseNet as sgie.
Please try to use above sample directly.

@Morganh I used Peoplenet as PGIE and BodyPosenet as SGIE and now it is working proper as per my requirements … As we concluded that peoplenet detects persons more accurately than any other models so we use it.
Currently I want to work with messagebroker part just like test5 app.

Thanks for the info. For message broker, pleas check if you can leverage this plugin as test5 app.

Hi @Morganh , As you are suggesting not to use PGIE as peoplenet and SGIE as Bodyposenet, is there any specific reason?
here is working sample of PGIE and SGIE -

Actually there is no specific reason since internal team do not run similar pipeline about it.
Just now I check with them and confirm that Bodypose can be used as SGIE to identify the body parts of the detected people.

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