Closed yangbinchao closed 1 year ago
Hi,
you can easily log the ground truth with the tensor2array
function.
Here, in a very similar project, I made a little function that logs best and worst results that you can work on : https://github.com/ClementPinard/unsupervised-depthnet/blob/master/test_depth.py#L50
Note that the depth here is only a bunch of lidar rays, so not continuous.
Hi,
you can easily log the ground truth with the
tensor2array
function. Here, in a very similar project, I made a little function that logs best and worst results that you can work on : https://github.com/ClementPinard/unsupervised-depthnet/blob/master/test_depth.py#L50Note that the depth here is only a bunch of lidar rays, so not continuous.
Thank you very much. That solved my problem
Hi,
you can easily log the ground truth with the
tensor2array
function. Here, in a very similar project, I made a little function that logs best and worst results that you can work on : https://github.com/ClementPinard/unsupervised-depthnet/blob/master/test_depth.py#L50Note that the depth here is only a bunch of lidar rays, so not continuous.
Thank you for your reply, how can this kind of GT be generated ?
Hi, you can easily log the ground truth with the
tensor2array
function. Here, in a very similar project, I made a little function that logs best and worst results that you can work on : https://github.com/ClementPinard/unsupervised-depthnet/blob/master/test_depth.py#L50 Note that the depth here is only a bunch of lidar rays, so not continuous.Thank you for your reply, how can this kind of GT be generated ?
hi,have you achieve this funciton?
Hi, doing chores to clean up mi issue list, the visualization above can be obtained through scipy ND interpolator. See https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.LinearNDInterpolator.html#scipy.interpolate.LinearNDInterpolator
So you just need to use this function to get the 3d points from lidar, and https://github.com/ClementPinard/SfmLearner-Pytorch/blob/master/data/kitti_raw_loader.py#L165 then use scipy's function to construct the interpolated depth map.
Note that it won't be accurate so it's only for vizualisation purpose.
I want to compare my prediction performance by visualizing the true value of the picture(depth). How to display the ground_truth of the depth map?