I have a problem on the Jetson Xavier NX 16GB Modul with Jetpack > 5.0 and deepstream. Sometimes (not related to temperature or runtime) an error shows up like shown in the video attached. It’s a strange error because sometimes its working without an error for 5 minutes or so and then the error appears suddenly. I use the git repo from Marcos Luciano DeepStream-Yolo to run YOLOv5s on the Seeeds reComputer J2012 (so basically the 16GB NX module + their carrier board). I tried the same with JP 4.6.x and it works without any problems. The video shows an image from the COCO Dataset converted to a video file to work with the deepstream-app but the error also appears when using the image + gstreamer + deepstreamer plugins. The output detection is performed with pretrained Yolov5s.
Yes but can you see the flickering in some frames? It loses the correct bounding box and shows two BBoxes in the middle of the object. I don’t have this behavior on JP 4.6.x. There the BBox is always correct.
Hi @yuweiw, the pretrained YOLOv5s is working with your repo witout any errors. But I’m not able to get a custom model to work with your repo (tao). I basically converted the custom model in the same enviroment and in the same way as the pretrained one. I changed the number of classes and made a new label file. It successfully converts the model to an engine model but on inference it did not detect anything.
Do you know what had changed in Deepstreamer or/and Jetpack and why Marcos Lucianos repo working fine with JP 4.6.x and not with JP 5.X? I also tested Deepstreamer 6.1 on our workstation and its working. So it must be related to the Jetson Devices.
There is no update from you for a period, assuming this is not an issue anymore.
Hence we are closing this topic. If need further support, please open a new one.
Thanks
Could you please attach your config file and demo when you run it in deepstream?
Sorry for the late reply we had experienced the same issue on 18.04. We guess that the issue is related to current issues. Maybe with the board (Seeed A206) or due to throttling? How do I set the max. current to 5000mA on JP5.0? While short tests with the tao implementation the issue is not present.
For the problem with the custom model I trained the pretrained Model again on the COCO Dataset but only for persons, so that it’s close to our model. Here is the result
No detections are displayed (No Person detected). With the pretrained model it’s working. So it seems like there is a problem with custom yolov5 models with the tao implementation. Here is the config file (2.0 KB)
. I changed the number of classes to 1 and also the input size to 640 according to the exported ONNX model.
About how to improve performance, you can refer the link below: Boost the clocks
By comparison the effect between our yolov5 model and your model, it may be the your model’s problem. Your env may have some diffrences with the maintainer of the github repo. You can open a topic at that github repo.
So basically this is the solution. So its seems like to be an error with the conversion process to TensorRT (engine). The process is different in the Tao implementation but the engine files can be used in Marcos Deepstream-Yolo