Comments (3)
I saw in the paper that 2d pictures of network design are only used in training, and good results can be obtained without using 2d pictures in testing. However, I found that the test still needs to load pictures. Did I do anything wrong? Thank you very much
from 2dpass.
Thats just how the dataloader is programmed, if you don't have the pictures downloaded, it will still search for them and return errors. I created a fork that makes the dataloader ignore the 2D information when using --baseline only. It works for training, and I hope it works for test too (still training so I can't run it in test yet).
https://github.com/Montyro/2DPASS
from 2dpass.
Thats just how the dataloader is programmed, if you don't have the pictures downloaded, it will still search for them and return errors. I created a fork that makes the dataloader ignore the 2D information when using --baseline only. It works for training, and I hope it works for test too (still training so I can't run it in test yet).
https://github.com/Montyro/2DPASS
Thank you very much for your work, which has helped me a lot. Hope you can get a good result. Could you remind me if it works for the test too.
from 2dpass.
Related Issues (20)
- inference time of 2DPASS (4scale-64dimension)
- Problems that arise during training
- Dataset Nuscenes HOT 1
- link dataset nuscenses HOT 1
- class noise
- Intensity HOT 1
- about pretrained model HOT 4
- use of intensity in 2DPASS
- When I swapped the 3D network for my own, some problems occurred
- multi-scales
- SPVCNN-nuscenes
- Running Inferences on Real-Time Data
- pre-trained model in Table 2 HOT 4
- the sacle of the 3dconv
- difference betwe paper and code about modali fuse HOT 1
- Size mismatch for pretrained model
- Segmentation fault(core dumped)
- ValueError: Input must be 1- or 2-d. HOT 1
- some issues about the idfference between the paper and the code HOT 1
- About the trainingTime
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