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Deep Monocular Visual Odometry using PyTorch (Experimental)
hi, I am new to visual odometry and want to run this code. which one of the Kitti datasets were used in the code?
Hello! The training set I use is 00, 02, 05, 08. I don’t know what the reason is during training. There are always more than 1 pictures not trained. Do you know what the reason is?
Line 61 in 7a8e73f
Thank you
In def__getitem__(self, index)
, dataset.py you are stacking the entire train, test set sequences and returning it back. How ever getitem iterable and returns images with labels over index.
Hello,
I cannot replicate the result of the original paper. If you can do it, please upload the pretrained weights. Thanks!
Because I trained it for 100 epochs, the network almost learned nothing. The testing loss is too high and the results are not visually convincing at all. Have you found a way to solve it? Thanks!
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