Our result shows argus_facedetect can run >20 fps at 12M, but “detectnet-camera facenet” can only run ~5fps at 12M. Just wondering what will cause this difference?
The camera board is “LI-JETSON-KIT-IMX377” (from Leopard Imaging).
It can be reproduced with default board ov5693. But since the full resolution of ov5693 is 5M, the difference is not very obvious by human eyes (argus_facedetect runs ~30fps, detectnet-camera facenet runs ~25fps).
Suppose detectnet-camera will have lower performance.
Jetson_inference targets for demonstrating various deep learning use case (ex. classification, detection, segmentation).
Some optimization did’nt be applied for simpliciy.
There is two possible issue inside the pipeline: 1. A memory copy from GStreamer to CUDA 2. Multi-times overlay when rendering. More face will have lower performance.
However, argus is our deep learning pipeline specified for Argus and some optimization is done for it.
Thanks.