Comments (3)
So, I took the vp's as pairs of coordinates and plotted 3 lines, each starting from the center. Each of these lines indicate the direction towards a VP.
To my understanding, The edges of the bounding boxes must be parallel to the direction of VPs.
But for few, it's not.
Am I missing anything here?
from boxcars.
The easiest and safest way how to compute the 2D image coordinates of the vanishing points is to use intersection of lines on the 3D bounding box which should be parallel. I have always done it like this when I was working with the dataset.
It is possible that the the crop offset is not taken into account for the position of the vanishing points for some videos (the ones with non numeric name). These were the first videos which we processed and the dataset was extended after that. Therefore, it is possible that we have an inconsistency in the coordinates of the vanishing points.
from boxcars.
Thank you! That cleared my doubt.
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Related Issues (20)
- Bounding Box Estimator HOT 1
- this command error : python3 scripts/train_eval.py --eval path-to-model.h5 HOT 3
- No such file :dataset.pkl HOT 1
- AttributeError: 'NoneType' object has no attribute 'TF_DeleteStatus' HOT 1
- Where to find the NET that estimates 3D bb ? HOT 2
- Use trained model for single image prediction HOT 3
- BCNN, CBL and PCM are all using VGGNet as baselines, but achieve worse performance
- This is just a car patch classification example HOT 4
- Training on Custom data
- Is there any full image corresponding to the patch
- Link to dataset is down HOT 13
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- How to create the pickle files for my own dataset?
- Link to trained model is down
- requirements.txt file
- Dataset link is down HOT 2
- Trained Model fails in evaluation and single image classification HOT 1
- list of 107 classes from model
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