This is a PyTorch(0.4.1) implementation of Deep Ordinal Regression Network for Monocular Depth Estimation. At present, we can provide train script in NYU Depth V2 dataset and Kitti Dataset!

Note: we modify the ordinal layer using matrix operation, making trianing faster.

• DORN model in nyu and kitti
• Training DORN on nyu and kitti datasets
• Results evaluation on nyu test set
• Calculate alpha and beta in nyu dataset
• Realize the ordinal loss in paper

Some friends asked me about how to use the NYU Depth V2 dataset. The best choice is to use all the Images (about 120k) in the dataset, but if you just want to test the code, you can use the nyu_depth_v2_labeled.mat and turn it to a h5 file. The convert script is 'create_nyu_h5.py' and you need to change the file paths to yours.