@numbqq please help me! Thanks you? demo edit in code, new camera Sony IMX586 8000 x 6000 48 MP, please help me! ISO Low Min Max 1 - 102400, Up Exposure time min max 1/25000s - 256s
How to run the build_vx.sh, as it gives me the following message, any help is apprecaited.
I am trying to compile my own model and build it on the khadas aml_nputy _app so as to generate binaries, but having difficulty in running this script. Please help!!!
It’s not clear which paths to give, and it throws out the error. The steps for compiling are not very clear in the documentation. Please help me out
I have compiled my model successfully in the sdk acuity toolkit but I am not able to compile it in the aml_npu-app-master so that I could move the .so files to the board for compilation. Please guide.
Thanks @Frank for the suggestion, I am able to generate the .so files now, but when I try to run the model on theVIM3 board it through’s out error saying that the model is incorrect.
Then while checking on the model I found that the website from which I took the model is different than the one is recommended in the khadas website ? the example uses 416x416 model but on the website it’s using 608x608?
any recommendations on how to get the correct model so that I can start to deploy my own models on the VIM3 board???
looking forward to your reply in anticipation
Also, if someone could please mentions the correct path’s and the devices where we have to do every step during the conversion specifically, that will be a great clarification too. Thanks in advance.
Also, how can we run the same example for a video sequence?? should we just follow the similar procedure of copying the files to detect_demo_picture to detect_demo? If you could provide some instructions on that it will be really helpful for us to move forward in the development of our product. Thanks in advance.
When I train yolov4 , I use 416x416 . And if you get the cfg file with darknet github , it’s 608x608 , 608x608 puts too much pressure on the NPU. I do not recommend using 608x60. I have tried many versions. In the case of combining the recognition accuracy and frame rate, 416x416 is the most suitable one.
So, I suggest you train a 416x416 model yourself. When 608x608 runs on VIM3, if there are more classes recognized, the frame rate may be 0. If you need to use 608, you need to edit the source code and recompile
@Frank I wanted to run this model but it is giving me errors during the conversion, can you please shed some light on why it is not converting to .nb format??? Thanks.