Levi Pereira

Many tanks for your time, the current behavior is really annoying.

Added: Two repositories to test [YOLOv9 QAT Models](https://github.com/levipereira/triton-server-yolo/releases/tag/v0.0.1) - **Triton-Server**: Deploy Models on TensorRT format. [https://github.com/levipereira/triton-server-yolo](https://github.com/levipereira/triton-server-yolo) - **Triton Client**: Allows users to evaluate coco dataset or inference their own images/videos....

@demuxin Yes.

@trivedisarthak check OP

The Original Implementation in #327

could you please provide more details or clarify the issue you’re facing?

Why did you want implement NMS? End2End already incorporates Efficient NMS as a built-in plugin. You can try change End2End parameters --topk-all --iou-thres --conf-thres Check this https://github.com/levipereira/triton-server-yolo/releases/tag/v0.0.1 https://github.com/levipereira/triton-server-yolo/?tab=readme-ov-file#evaluation-test-on-tensorrt

https://github.com/NVIDIA/TensorRT/tree/32c64a324e58f252eae4e5681f5c39dbe22ef2d5/plugin/efficientNMSPlugin did you check plugin?

https://github.com/NVIDIA/TensorRT/tree/28733f0fdccde2967fed395b06ca491af3a561a9/plugin/efficientNMSPlugin#limitations

> https://github.com/levipereira/yolov9/blob/main/models/experimental.py#L140 > > `output = output[0]` will gets output of auxiliary branch. `output = output[1]` will gets output of main branch, which is correct one. https://github.com/WongKinYiu/yolov9/issues/130#issuecomment-1974964596