commiting most of the code

LICENSE

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+Copyright (c) 2016, University of Michigan
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
+
+3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

README.md

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-# hg-pose
-Code to test and use the model from "Stacked Hourglass Networks for Human Pose Estimation"
+# Stacked Hourglass Networks for Human Pose Estimation (Demo Code)
+
+This repository includes some basic Torch code for evaluation and visualization of our network output. A pretrained model is available on the project site at [www-personal.umich.edu/~alnewell/pose](http://www-personal.umich.edu/~alnewell/pose). Include it in the main directory of this repository to run the demo code.
+
+In addition, if you download the full [MPII Human Pose dataset](human-pose.mpi-inf.mpg.de) and replace images/ you can generate full predictions on the validation and test sets.
+
+To run this code you must have installed:
+
+- [Torch7](https://github.com/torch/torch7)
+- hdf5 (and the [torch-hdf5](https://github.com/deepmind/torch-hdf5/) package)
+- cudnn
+- qlua (for displaying results)
+
+(If there are any other dependencies that I have (likely) forgotten, get in touch and I will list them here)
+
+For displaying the demo images:
+`qlua main.lua demo`
+
+For generating predictions:
+`th main.lua predict-[valid or test]`
+
+For evaluation on a set of validation predictions:
+`th main.lua eval`