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Missed/shifted boxes problem #5
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Hi again,
Anyway, I have just read CARLA 0.9.10 update info and I found that this version provides LIDAR instance segmentation. I think it will be more efficient to use it for BBox extraction rather than using depth image. It might also solve the problem No. 2 that you mentioned. I'm working on it. |
Hello @MukhlasAdib I have solved the first problem as we said it was because of synchronization problem. I am working now on solving the missing boxes problem but using the same version 9.8 to avoid the hassle of upgrading CARLA version. |
@eslambakr, thanks a lot for your help! I will try it and perhaps update the code after I am done building the code that uses segmentation LIDAR. Feel free to share anything that you find here |
Fixed shift issue in #5 (for collectData.py)
@eslambakr Thanks for your suggestion, I have updated the code to fix the shift problem. In the other hand, I also have added a function to extract bounding boxes using semantic LIDAR, which seems to solve the missed box problem. |
Thanks for your amazing work.
I have noticed two main problems in your module:
The first one is the shifted boxes as shown below
![230539](https://user-images.githubusercontent.com/25908688/97205437-2b25f680-17c0-11eb-9b38-b7a996cf7e9a.png)
I think this mainly because of CARLA server itself, what do you think?
The second problem is missing Bboxes due to the area that you have chosen becomes out of field of view.
![231251](https://user-images.githubusercontent.com/25908688/97205578-53adf080-17c0-11eb-8179-7165f778076e.png)
I think we could easily solve it by using the segmentation mask instead of generating smaller box from the original one.
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