Comments (8)
- There is no need to delete or move any files from the kitti depth dataset. You can keep the raw
val
folder while having theval_selection_cropped
folder in the same directory. - Yes, we need to download the raw data and extract the rgb images. The rgb images need to be structured in a similar way to the depth dataset.
The reason why I did not release the downloaded rgb dataset was to avoid violation of the kitti' licences.
from self-supervised-depth-completion.
@fangchangma thank you for your reply. Creating the rgb dataset is one tedious task because I have to look for each drive id and download the data and then selecting the corresponding images that are there in the depth-dataset.
Just for the confirmation, after downloading all the relevant rgb files, the dir structure should look like this?
from self-supervised-depth-completion.
@fangchangma thank you for your reply. Creating the rgb dataset is one tedious task because I have to look for each drive id and download the data and then selecting the corresponding images that are there in the depth-dataset.
Just for the confirmation, after downloading all the relevant rgb files, the dir structure should look like this?
Hello,
I have the same problem, and I don't know how to match rgb and d in the flower structure. Can you give me some advice?
Thank you.@swapnesh-wani
from self-supervised-depth-completion.
@fangchangma thank you for your reply. Creating the rgb dataset is one tedious task because I have to look for each drive id and download the data and then selecting the corresponding images that are there in the depth-dataset.
Just for the confirmation, after downloading all the relevant rgb files, the dir structure should look like this?
Hello,
I have the same problem, and I don't know how to match rgb and d in the flower structure. Can you give me some advice?
Thank you.@swapnesh-wani
Hi @WANGYINGYU, I haven't downloaded the rgb dataset yet. But, I think the rgb dataset should look like my previous comment. Waiting for @fangchangma to confirm.
from self-supervised-depth-completion.
Hi. I just uploaded the scripts for downloading the RGB dataset. The README has also been updated to provide more details regarding the folder structures. Please let me know if it is unclear.
from self-supervised-depth-completion.
@fangchangma thanks for uploading the scripts. That will surely help a lot.
from self-supervised-depth-completion.
@swapnesh-wani @fangchangma Thank you for your reply. But I still have a few questions about the datasets.
1)Is the val_selection_cropped folder in the kitti_depth folder downloaded from the manually selected validation and test data sets (5 GB) in kitti depth?
2)The velodyne_raw folder in the /kitti_depth/train/20******drive****_sync/proj_depth/ folder is downloaded from kitti depth's projected raw LiDaR scans data set (2 GB) and placed In the corresponding position?
from self-supervised-depth-completion.
- Yes
- Yes
from self-supervised-depth-completion.
Related Issues (20)
- Error while loading "calib_cam_to_cam.txt" - can not reshape the array.
- question about depth-estimation results HOT 2
- What is the network used for single d?
- Why I can't get the result when using the trained model you provided?
- How can I get the result in your paper?
- About extracting trained model HOT 2
- Clip output in model.py
- inference HOT 2
- colorize the depth map HOT 1
- some problem about photometric_loss
- Use your pretrained model: GPU run out of memory. 8.95 gb already allocated
- Save output depth map HOT 1
- dataset extracting
- Training doesn't converge HOT 4
- silog error measurement
- Running Error in train mode sparse+photo HOT 1
- To much warning. HOT 2
- Use Stereo Pair Instead of Temporal Pair for Self-Supervised Training?
- The result cannot be reproduced
- Some questions about the details of the code
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