-
Notifications
You must be signed in to change notification settings - Fork 69
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
[Question] questions on detailed about dataset #2
Comments
Thank you for your interest in our project.
|
Thanks for replying, and question 3 is about the route file, I knew there are additional maps but the CARLA leaderboard public routes didn't provide the route files about these two. That's why I am curious about it. Thanks again. |
We use randomized routes the collect our dataset. This is similar to our previous project World on Rails. |
Oh, I see. I will try to check again. Thanks for answering. Really appreciate. Related to: issue comment |
Yes, I also just realized this issue and I am currently compressing the trajectories into .gz files. I will upload them in a few hours. |
ha! thanks for replying so quickly. btw, I notice even for the business box it still have the maximum upload size which is 150G here |
I will split the gz file so each file is around 8G |
Thanks! and is that possible for once download button to download all? will appear the error as shown above |
Yes should be possible, the files split format are going to be same as the world on rails dataset, except the format is in lmdb and can be directly used with the repo. If not separating them as like two downloads should also work. |
Thanks! I will wait for updating. Thanks agin! |
Hi, may I ask how to open the .mdb file? I want to have a look on the data. |
you should read code on dataset here, the repo show how to see data. For example: LAV/lav/utils/datasets/basic_dataset.py Lines 34 to 46 in 23e2f1b
|
Hi @Kin-Zhang , the dataset is now on box: https://utexas.box.com/s/fcj52g9juilnp4mt5k5fsqcqkxae77cb Let me know if you encounter any issues downloading or using the dataset. Thanks! |
Hi @dotchen, I also see the new dataset link, thank you very much! btw, may I ask how long did it take to train LAV on 4 Titan Pascal? And how long will it take to collect the data for about 400K frames? |
Hi, I wonder how I could decompress the downloaded files? I have removed the postfix, but it says that they are not in gzip format. |
Hi @Watson52 , Each stage takes different amount of time, but they are all around 2-3 days of time with 4 Titan pascal. It might be faster if you have better GPUs. |
The files are split tar.gz files, please download them all and then decompress them, no need to remove the postfix. |
Here is stack answer for how to extract split file you can try following command: zcat LAV-full.gz.* | tar -x |
Hi @dotchen. I have some questions before training:
|
The provided weight is the 45 DS entry in the ablations. The number in the file names corresponds to the number of epoch they are trained in.
|
Thanks for letting me know.
self.seg_model = RGBSegmentationModel(self.seg_channels).to(self.device)
self.seg_model.load_state_dict(torch.load(self.seg_model_dir, map_location=self.device))
self.seg_model.eval() @dotchen is this seg model use the
I also found the whole datasets may not provide all lidar_sem data in it since when I tried trained all towns here lack of File "/LAV/lav/utils/datasets/lidar_painted_dataset.py", line 27, in __getitem__
lidar_painted = self.__class__.access('lidar_sem', lmdb_txn, index, 1).reshape(-1,len(self.seg_channels))
File "/LAV/lav/utils/datasets/basic_dataset.py", line 83, in <listcomp>
return np.stack([np.frombuffer(lmdb_txn.get((f'{tag}_{t:05d}{suffix}').encode()), dtype) for t in range(index,index+T)])
TypeError: a bytes-like object is required, not 'NoneType' |
I will have to take a deeper look. In the mean-time you can relabel the dataset by running the point painting script. |
Ok looks like I might have overwritten some of the lmdb while testing the refactored code, causing it to miss some of the frames... |
Thanks for letting me know. |
Thanks for all discussions done here. It was very helpful to catch up the work.
File "/LAV/lav/utils/datasets/lidar_painted_dataset.py", line 27, in __getitem__
lidar_painted = self.__class__.access('lidar_sem', lmdb_txn, index, 1).reshape(-1,len(self.seg_channels))
File "/LAV/lav/utils/datasets/basic_dataset.py", line 83, in <listcomp>
return np.stack([np.frombuffer(lmdb_txn.get((f'{tag}_{t:05d}{suffix}').encode()), dtype) for t in range(index,index+T)])
TypeError: a bytes-like object is required, not 'NoneType' |
I fixed the problem, I forgot to do a pull request that can let others know. |
@Kin-Zhang Thank you for your comment! |
Hello thank you for your information! I had a problem when I tried to download and extract the dataset here I downloaded 2 parts of the copressed file (16GB), and ran
Do you know how I should extract the file? |
You must download all the dataset, only have two of them, cannot extract correctly. |
Thanks for providing the codes, it's amazing work. 🤩
Here are some questions after I read the paper and code readme:
Looking forward to your reply, and thanks again for this paper and codes.
The text was updated successfully, but these errors were encountered: