You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
A label file such as \train\scene-0001\000_occ.npy contains a np array with a shape of (39068,2). I have a few questions about this array. 1) Considering that the voxel space is (200,200,16), the 39068 points from the array represent occupied voxels from the 640000 total voxels?
2) I want to train a network that will use labels of shape (200,200,16), is there a place in the code where you translate the (39068,2) labels to the full voxel space?
3) Is there a way to extract only the voxels visible to the FRONT camera, in case I want to predict only the front scene, and not the whole surround scene?
Thank you!
The text was updated successfully, but these errors were encountered:
Thank you for your kind response. I do have a few more questions: I see that the flow files contain numpy arrays with shape for eg. (4691,2). 1) The 2 values for each row represent the velocity on both x and y axes? 2) Is there a way to link the flow with the voxel it represents? Is there a way to find out the flow for a specific voxel, from the ground truth provided? Thank you!
A label file such as \train\scene-0001\000_occ.npy contains a np array with a shape of (39068,2). I have a few questions about this array. 1) Considering that the voxel space is (200,200,16), the 39068 points from the array represent occupied voxels from the 640000 total voxels?
2) I want to train a network that will use labels of shape (200,200,16), is there a place in the code where you translate the (39068,2) labels to the full voxel space?
3) Is there a way to extract only the voxels visible to the FRONT camera, in case I want to predict only the front scene, and not the whole surround scene?
Thank you!
The text was updated successfully, but these errors were encountered: