Inference not proper when deploying with this pipeline

Hello,

I have trained the detectnetV2 model on custom dataset using TAO toolkit. However, when I deploy the model with Isaac ROS Gems pipeline, the output inference is not reflecting the output metrics and the inference that I am seeing while using the TAO pipeline.

Later, I deployed the same model with deepstream and noticed that inference was as per the output metrics which I noticed while training the model.

I tried matching the hyper-parameters in the params.yaml file to match the config file of deepstream which I had used but there was no significant improvement in output inference. I am attaching the output images for i) TAO inference ii) Isaac ROS Gems inference iii) Deepstream inference for reference

Model was trained on 6000 images with 500 epochs which gave average precision(mAP) of ~95%. The config file used for training is same provided with DetectnetV2 for TAO training, no changes were done.

Isaac ROS Gems:

TAO inference:

Deep-stream:

Thanks,
Mayank