Once the package has been installed, make sure it's working by running the following demo script (described in more detail below):
The script should output the following lines. The CNS manual contains a troubleshooting section if you encounter problems.>> hmax_cvpr06_run_simple
sampled 2048 "s2" features from "image_0010.jpg" computed feature vector for "image_0002.jpg" (??? sec)
hmax package, each of these stages is represented as a CNS group, composed of multiple CNS layers, one layer per scale. This allows all the scales of a group to share common parameters and (if applicable) a common feature dictionary. All the units or cells in a group are of the same type (dot product, max pooling, etc.)
Under the directory
hmax/demo there are several demo scripts.
These demo scripts illustrate the overall process of instantiating a model, learning a feature dictionary, and computing feature vectors for images. When you start looking into the code, look at |
More extensive demo scripts that perform some of the experiments in the above papers.|
hmax_cvpr06_params_base hmax_cvpr06_params_full hmax_pnas07_params
Each of these contains a compact set of parameters that defines a particular feedforward model (number of "S" and "C" stages, the particular cell type of each stage, its parameters, pooling ranges, etc.) The meaning of these parameters is documented in each cell type's "Construct" method, found in the file |
hmax package itself consists of the file
hmax.m plus many pairs of files named
hmax_type.h, each of which defines a different cell type. Some of the ".m" files also contain useful methods, many of which you will have seen used in the above demo scripts.
hmax.Model- converts a compact HMAX parameter set into a full CNS model structure which you can then instantiate and run on the GPU.
hmax_input.Load- loads a new image into an input layer of an instantiated model.
hmax_s.SampleFeatures- adds new features to a dictionary by sampling.
hmaxpackage currently consists of:
|r1||2011-02-25||Reorganized & renamed from "fhpkg" (Feature Hierarchy package).|
|r20||2012-04-10||Tested under CUDA 4.1.|