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Implementation questions #2
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Please ignore the mtr. It refers to my toy dataset.
FYI, the dataset directory should imitate the PointRCNN dataset directory. 'det3d To generate the augmented training dataset, try running After generating the database, you could change the path in |
There is not an easy way to implement the 3 different classes (car, pedestrian and cyclist) detection of the kitti dataset? Because the version implemented in the paper does classify the objects in multiple classes rigth? Thanks for your time |
@Mfertega Did you resolve your issue? I think I am having a similar problem. My goal is to implement the setup in the original repo with as few changes as possible. I corrected the various bugs outlined here, and then trained the model over 160 epochs (here is a notebook showing the changes I made and the training results). Even though I made the corrections, the model still produces bad results. And if you look at the learning curves, the validation loss increases for some reason. Any idea what's going on? |
Hi @tjtanaa, first of all thank you. I have been working with your code and this package but I have a couple of questions. In your repository with the code you have 3 versions, the _v2, the v2_2 and the mtr. My application is for detecting cars, pedestrian and cyclists with an VLP-16. I know the version _v2_2 does not fit that porpoise, and I know the v2 version will work, but I don't understand clearly the mtr version.
Adding to this question, I would appreciate if you could tell me how do you have the kitti dataset arrange, in order to minimize the changes to your code.
The final question is about the training, I have training the neural network of the first repo but I always obtained bad results compared to the model submitted by the author and the paper, do you have a value of the loss for me to check or maybe the number of epochs?.
Thank you for your time.
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