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mdepth

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Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions

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# Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions
Copyright (C) 2016, Authors.

This is a reference implementation of the algorithm described in the paper:

Ayan Chakrabarti, Jingyu Shao, and Gregory Shakhnarovich, ["**Depth from 
a Single Image by Harmonizing Overcomplete Local Network Predictions**," 
](https://arxiv.org/abs/1605.07081) NIPS 2016.

It is being made available for non-commercial research use only. If you
find this code useful in your research, please consider citing the paper.

Please see the [project page][proj] and contact <ayanc@ttic.edu> with 
any questions.

### Requirements

The top directory contains the inference code. It is entirely in MATLAB 
and has no external Caffe dependencies.

1. You can download our trained neural network model weights,
   available as a .caffemodel.h5 file from the [project page][proj].
   
2. This implementation requires a modern CUDA-capable high-memory GPU
   (it has been tested on an NVIDIA Titan X), and a recent version of
   MATLAB's Parallel Computing Toolbox that supports the `GPUArray`
   class.
   
3. You will also need to compile the mex function postMAP. With modern
   versions of MATLAB, this can be done by running `mexcuda
   postMAP.cu`. Requires the CUDA toolkit with `nvcc` to be installed.

[proj]: http://www.ttic.edu/chakrabarti/mdepth/

### Usage

First, you will need to load the network weights from the model file
as:

```>>> net = loadModel('/path/to/mdepth.caffemodel.h5');```

Then given a floating-point RGB image `img`, normalized to `[0,1]`,
estimate the corresponding depth map as:

```>>> Z = mdepth(img,net);```

Note that we expect `img` to be of size `561x427`, which corresponds
to the axis aligned crops in the NYU dataset where there is a valid
depth map projection. You can recover these as:
`img = imgOrig(45:471, 41:601, :)`.

### Training with Caffe

See the `training/` directory for code and instructions for training
your own network.

mdepth

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