<p>In <a href="https://github.com/mlpack/mlpack/pull/683#discussion_r66456126">src/mlpack/methods/edge_boxes/feature_extraction_impl.hpp</a>:</p>
<pre style='color:#555'>> + }
> + return input_data;
> +}
> +
> +template<typename MatType, typename CubeType>
> +arma::vec StructuredForests<MatType, CubeType>::
> +GetFeatureDimension()
> +{
> + /*
> + shrink: amount to shrink channels
> + p_size: size of image patches
> + n_cell: number of self similarity cells
> + n_orient: number of orientations per gradient scale
> + */
> + arma::vec P(2);
> + int shrink, p_size, n_cell;
</pre>
<p>Same, could you use size_t and const at here. The new thing is, we could apply lazy evaluation at here.Rather than declare your parameters as</p>
<p><code>int shrink, p_size, n_cell;</code></p>
<p>you can</p>
<p>const size_t shrink = options["shrink"];<br>
const size_t p_size = options["p_size"];<br>
const size_t n_cell = options["n_cell"];</p>
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