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Inconsistencies in inferencing results #23
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Can anyone answer my question? Whether the network is any random layer? |
Do you know the reason ? I meet this question too. |
I do not know the reason? I want to contact the author, but I don't know how to contact the author.Hope the author can give a reply. |
Maybe the reason is the sampling of the points. |
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Looking forward to your new discovery. |
The first point of FPS is random. I have tried the model provided by Openpcdet like pointrcnn and the result is incosistent either. But I run pointpillar which donnot use FPS the result is consistent . You can try is again. |
I don't agree with you.I don't know whether you tried to understand the code.In my experience, each time sampling starts from the first point(index 0).The first point of FPS is no randomness. Here are my experimental results. Hope to your new discovery. |
Each time you run the code, you will get the same sample points.I konw what you mean, but sampling starts from the first point(index 0) in Openpcdet. You can try to read the code written by cuda. Thanks! |
@yifanzhang713 |
I think the reason is about the common property of point-based detection techniques. We are committed to improve it in the next version. Due to the inherently stochastic in our framework (different random sampling initializations in pre-processing, different initiation point in FPS, maximum number in query group, etc. ) Hence, even if we provide the trained weights, it is possible that the results that you obtain differ slightly from the ones presented in the paper. Hope these can help you! |
@yifanzhang713 Thank you for your prompt reply. |
Yeah, I agree to what you mean. But what cannot be ignored is that the sample_points and shuffle_points operation in the data prepossessing, which may affect all the results of processes mentioned above. |
@yifanzhang713 |
@JaydencoolCC Hi, here is my discovery about the randomness. It seems like the shuffle operation in
if you set numpy with fixed seed, you might get a consistent results |
I think so. Thank you so much! |
The same frame point cloud is inputed into the model, but the result is different each time. For example. for the same frame point cloud, two cars are detected by the model for the first time, but three cars are detected by the model for the second time.The results are very erratic. Can you explain that, please?
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