function config = config_cornell_base(results_path, dataset_path)
%% Cornell Base Configuration File
% Machine Memory Parameters used for Dictionary Learning
config.max_sample_mem = 32e9; % in bytes
config.max_samples_per_image = 1000; % max number of samples
config.max_total_samples = 1e6; % max number of total samples
config.blk_size = 2^10;

%% Data info
% Labels are binary.
data_info.labels = {'not_graspable', 'graspable'};
data_info.token_expr = '^(\d+_\d+).png$';
% Formats used to construct the original filename from tokens.
data_info.rgb_format    = '%s.png';
data_info.gt_format  = '%s_gt.mat';

config.pool_type = 'max';

%% Creat HMP Architecture Params
config.raw_feature_types = {
    % feature type,   subdirectory name,   file format,      num_channels
    {'rgb',           '*RAW_RGB',          '%s.png',         3},
    {'depth',         'depth',             '%s.mat',         1},
    {'normals',       'normals',           '%s.mat',         3},
    {'curvature',     'curvature',         '%s.mat',         2},
    {'shape_index',   'curvature',         '%s.mat',         2}};

%% Cornell Model Params
% Cornell specific params.
model_params.setting = 'recognition';
model_params.pos_dist_thresh = 21;
model_params.box_pad = 35;
model_params.max_img_samples = 20;
% model_params.max_neg_dist = 45;
% Usual params.
model_params.model_type = 'one-vs-all';
model_params.svm_package = 'liblinear';
model_params.learner = 'SVR';
model_params.norm_each_feat = 'L2';
model_params.center_data = 0;
model_params.unit_variance = 0;
model_params.svm_C = [100, 10, 5, 1, .1, .01, 0.001];
model_params.weight_classes = false;
model_params.tune_subset = 1.00;
model_params.sparse_threshold = 0.025;

%% Folder Paths for Organization
paths.results      = results_path;
paths.dataset      = dataset_path;
paths.img_feats    = fullfile(results_path, 'img_feats');
paths.seg_feats    = fullfile(results_path, 'seg_feats');
paths.hmp_dicts    = fullfile(results_path, 'hmp_dicts');
paths.depth        = fullfile(paths.img_feats, 'depth');
paths.normals      = fullfile(paths.img_feats, 'normals');
paths.curvature    = fullfile(paths.img_feats, 'curvature');
make_directory_structure(paths);

config.paths = paths;
config.data_info = data_info;
config.load_params = [];
config.model_params = model_params;
