This repository implements a convolutional neural network for monocular depth estimation in an unsupervised manner, using left-right consistency loss as described in the CVPR 2017 paper by Godard et al. The model is trained on stereo image pairs and can predict depth maps from single RGB images. A simplified inference script is provided for running the pretrained model on new images.