Which system do you use? Android, Ubuntu, OOWOW or others?

Ubuntu

Which version of system do you use? Khadas official images, self built images, or others?

Khadas official images

Please describe your issue below:

Sorry, I encountered trouble when converting the model.
Because my converted model output is very different from the output of pytorch and onnx,
I am troubleshooting the problem in order

About the settings of mean & std :

--channel-mean-value

on pytorch, I use the function in the picture to do image pre-processing

1.mean is [0.485, 0.456, 0.406], so I multiply the mean by 255, which becomes
[123.675 116.28 103.53]. Then the image array will change from [0,255] to [0,1],
so my scale is 1/255, that is 0.00392156.
So the parameter is below, right?

This is for the RGB color channels, the mean across those channels.

Please check this to see how you can find the mean values for your input examples,

you can get the mean values from your training set for example.

yes.

std is standard deviation, you can follow it according to method of finding mean of input images, mentioned above, and apply similar way to get the standard deviation as well.

If the parameters converted by the tool are not the same as my own image pre-processing function, I will go back and study it again.

If it is the same, then I may have encountered a problem when ruuning 0_import_model.sh
Because after I run inference.sh next,
I get iter_0_attach_Concat_Concat_175_out0_0_out0_1_3_3.tensor,
I checked the results of inference, which are far different from the results of using onnx.

I have followed the documentation to confirm and directly specify the input and output nodes.
But I still can’t get similar output. Is there any way I can improve it?

Although the model was not trained by me, it was trained using the author Thohemp’s 6DRepNet.
But I have studied the source code, whether in training or inference code, the following functions are used to process the dataset.