@Akkisony Many people have reported the problem of the single-category yolo model, so I will make a single-category yolo model this week to see where the problem is
@Akkisony I successfully converted a hand detection model. I will release it this week or next. You can follow the forum or docs at that time.
@Frank Looking forward to the release. I hope now single class detection works using yolov3.
Thank you
@Frank I was working with 1 class yolov3 tengine model.
However, I still did not get an answer what changes I need to make to get my model running. I am facing issue of multiple detections in a single frame (problem on Non max suppression) though my model preforms better on CPU.
@Frank
I mean to say, I have trained a model with single class and I did inference on CPU. I was able to get the detections.
Later, I converted the model to NPU compatible(tengine format) using tengine SDK and now when I do inference, I get the result as explained in my post below.
I get predicitions of 2000+ bouding boxes in a single frame - which is wrong.
@Frank
https://drive.google.com/drive/folders/14wDTO81KBYYfyz0Jj0aWsCXWFixbHpwS?usp=sharing
please find the cfg file.
#batch=1
#subdivisions=1
# Training
batch=64
subdivisions=16
you should use bahtch=1 subdivisions=1
@Frank Thanks. May be I forgot to change the parameter of cfg file while converting using tengine sdk. I will try and update you.
Thanks again!
@Frank I was not successful, i still have the same problem when I try to do inference on NPU (video).
I changed batch and subdivision to 1, while converting the model to tmfile using tengine sdk.
However, during training it was 16 and 64.
https://drive.google.com/drive/folders/14wDTO81KBYYfyz0Jj0aWsCXWFixbHpwS?usp=sharing
Please find the model and cfg.
@Frank Okay, thank you.
May be if you can just try running (through video) the converted model in the above link, you might get to know my problem I was talking about.