I’m testing the yolo models that come with the 4.02 deepstream sdk.
The yolo3 model seems very accurate but I can only process 1 stream on a jetson nano at around 2fps. If I change yolo-v3.cfg to 416x416 I can get around 11 fps on a live source rtsp camera. AS soon as I add more cameras though it slowly dies and you get huge latency.
So I’ve tested the yolo3 lite model. Obviously I can get better fps and I can have it running in the deepstream-app with 4 rtsp sources but the accuracy seems very low. It struggles to find people unless they still still directly in front of the camera. I’ve played with varying settings like interval = 4 or 8 and a tracker and it makes no difference to the accuracy.
When using the standard deepstream resnet10 model that accuracy is great, but I notice false detections. Where it will say a chair inside our house is a person all the time for example. This is why I thought of using Yolo for better accuracy but it seems this is not the case with the yolo lite models.
Is there any guidance here…?
I read in another thread that yolo is not officially supported by deepstream??