Hello @mchi,
I still have the issue when I tried setting the sink as you suggested. The bounding boxes are random even in the out.mp4 file.
I looked at the other link you suggested (Random Bounding Box in FasterRCNN etlt model in Xavier 30W Mode) and I don’t think my problem is the same. I am not using a etlt model, I just have a yolov3-custom.weights & cfg trained with Darknet. Also my issue is not related to batch size so far , as I’m trying to perform inference on 1 stream with batch size=1.
Also my issue is different from what @gjtjx reported. When I downloaded the yolov3 weights and config ran the sample video I was seeing correct bounding boxes. Once I made changes to NUM_CLASSES_YOLO and built the nvdsinfer_custom_impl_Yolo, I started seeing this random/bad bounding boxes.
I’m still trying to figure out the issue any thoughts and ideas will be helpful.
Thanks,
Dilip.