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Wrap DynSLAM as a ROS node #38

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rnunziata opened this issue Oct 12, 2017 · 12 comments
Open

Wrap DynSLAM as a ROS node #38

rnunziata opened this issue Oct 12, 2017 · 12 comments

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@rnunziata
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Have you considered make this a ROS node so that depth, and segment classification can be integrated via ROS messages. This would allow switching between different implementation of these components, and would be language agnostic.

@AndreiBarsan
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Yes, I have. You are correct; those would be very neat advantages, but it would take a bit of time to refactor everything. It's on my todo list, though. And once again, very sorry about the slow replies, it's a busy period here and I'm also CUDA-less. :(

@AndreiBarsan
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Note to self: Peidong suggested ROS2 should be used (http://wiki.ros.org/ROS/Tutorials/WritingPublisherSubscriber%28c%2B%2B%29).

@AndreiBarsan AndreiBarsan changed the title Have you considered make this a ROS node Wrap DynSLAM as a ROS node Dec 9, 2017
@0dmf0
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0dmf0 commented Apr 27, 2020

Yes, I have. You are correct; those would be very neat advantages, but it would take a bit of time to refactor everything. It's on my todo list, though. And once again, very sorry about the slow replies, it's a busy period here and I'm also CUDA-less. :(

Have you already make this a ROS node?

@AndreiBarsan
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Sorry, I haven't added ROS support and I don't think I'll have time in the foreseeable future. I'd be more than happy to review PRs adding that if someone does it!

@0dmf0
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0dmf0 commented May 1, 2020 via email

@AndreiBarsan
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ETH Zurich seem to have a utility for building rosbags from KITTI sequences here: https://github.com/ethz-asl/kitti_to_rosbag

However, since KITTI doesn't come with depth (apart from the LiDAR), you'd need to compute that separately, and modify the code above to include one additional depth or disparity image in each frame.

If you want to, you can use the DispNet also used by this project, or if you want to upgrade to newer tech (DispNet is almost 5 years old), I'd recommend one of my colleague's awesome DeepPruner: https://github.com/uber-research/DeepPruner (MIT licensed)

@0dmf0
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0dmf0 commented May 2, 2020

ETH Zurich seem to have a utility for building rosbags from KITTI sequences here: https://github.com/ethz-asl/kitti_to_rosbag

However, since KITTI doesn't come with depth (apart from the LiDAR), you'd need to compute that separately, and modify the code above to include one additional depth or disparity image in each frame.

If you want to, you can use the DispNet also used by this project, or if you want to upgrade to newer tech (DispNet is almost 5 years old), I'd recommend one of my colleague's awesome DeepPruner: https://github.com/uber-research/DeepPruner (MIT licensed)

Well, so can you explain clearly how to use another KITTI dataset? I don't know how to process another dataset.

@0dmf0
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0dmf0 commented May 2, 2020

Or can you provide another KITTI dataset which has already been processed?
Thanks

@AndreiBarsan
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Do you mean pre-processed for DynSLAM or pre-processed for ROS?
For DynSLAM there are tools in this repo (MNC and dispnet-flownet-docker in preprocessing/) do do it for KITTI data. For ROS I am not sure; I am not familiar with ROSbags.

@0dmf0
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0dmf0 commented May 2, 2020

Do you mean pre-processed for DynSLAM or pre-processed for ROS?
For DynSLAM there are tools in this repo (MNC and dispnet-flownet-docker in preprocessing/) do do it for KITTI data. For ROS I am not sure; I am not familiar with ROSbags.

Everytime I pre-process KITTI data, it shows:
dmf@dmf-GS63-7RE:/media/dmf/丁/DynSLAM$ scripts/preprocess-sequence.sh kitti-tracking data/kitti/tracking training 6Failure: Invalid directory structure for the tracking dataset.
Expected directory structure:
├── training
│   ├── calib
│   ├── image_02
│   │   ├── 0000
│   │   └── etc.
│   ├── image_03
│   │   ├── 0000
│   │   └── etc.
│   └── velodyne
│   ├── 0000
│   └── etc.
└── testing
└── .
Do you know how to solve this?

@AndreiBarsan
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AndreiBarsan commented May 2, 2020 via email

@AndreiBarsan
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AndreiBarsan commented May 2, 2020 via email

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