source: proiecte/pmake3d/make3d_original/Make3dSingleImageStanford_version0.1/LearningCode/Learning/Learn.m @ 37

% *  This code was used in the following articles:
% *  [1] Learning 3-D Scene Structure from a Single Still Image, 
% *      Ashutosh Saxena, Min Sun, Andrew Y. Ng, 
% *      In ICCV workshop on 3D Representation for Recognition (3dRR-07), 2007.
% *      (best paper)
% *  [2] 3-D Reconstruction from Sparse Views using Monocular Vision, 
% *      Ashutosh Saxena, Min Sun, Andrew Y. Ng, 
% *      In ICCV workshop on Virtual Representations and Modeling 
% *      of Large-scale environments (VRML), 2007. 
% *  [3] 3-D Depth Reconstruction from a Single Still Image, 
% *      Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng. 
% *      International Journal of Computer Vision (IJCV), Aug 2007. 
% *  [6] Learning Depth from Single Monocular Images, 
% *      Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng. 
% *      In Neural Information Processing Systems (NIPS) 18, 2005.
% *
% *  These articles are available at:
% *  http://make3d.stanford.edu/publications
% * 
% *  We request that you cite the papers [1], [3] and [6] in any of
% *  your reports that uses this code. 
% *  Further, if you use the code in image3dstiching/ (multiple image version),
% *  then please cite [2].
% *  
% *  If you use the code in third_party/, then PLEASE CITE and follow the
% *  LICENSE OF THE CORRESPONDING THIRD PARTY CODE.
% *
% *  Finally, this code is for non-commercial use only.  For further 
% *  information and to obtain a copy of the license, see 
% *
% *  http://make3d.stanford.edu/publications/code
% *
% *  Also, the software distributed under the License is distributed on an 
% * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either 
% *  express or implied.   See the License for the specific language governing 
% *  permissions and limitations under the License.
% *
% */
function []=Learn(LearnType,LearnAlg,HistFeaType,HistFeaDate,AbsFeaType,AbsFeaDate,SkyExclude,LearnLog,LearnNear,WeiBatchNumber)

global GeneralDataFolder ScratchDataFolder LocalFolder ClusterExecutionDirectory...
    ImgFolder VertYNuPatch VertYNuDepth HoriXNuPatch HoriXNuDepth a_default b_default Ox_default Oy_default...
    Horizon_default filename batchSize NuRow_default SegVertYSize SegHoriXSize WeiBatchSize PopUpVertY PopUpHoriX taskName;

%This function is the meta function of all type and algorithm of learning
switch LearnType
   case 'Abs'
      disp('LearnType is Absolute depth');
      WeiBatchNumber
      % input : LearnType,LearnAlg,WeiBatchNumber,LogScale,SkyExclude
      LearnDepth(LearnAlg,AbsFeaType,AbsFeaDate,WeiBatchNumber,LearnLog,SkyExclude,LearnNear);
   case 'Var'
      disp('LearnType is Variance');
      WeiBatchNumber
      DepthDirectory = [ScratchDataFolder '/Abs_robustfit_Nonsky1_Log1_Near0'];
      % input : LearnType,LearnAlg,WeiBatchNumber,LogScale,SkyExclude
      LearnVariance(LearnAlg,AbsFeaType,AbsFeaDate,WeiBatchNumber,LearnLog,SkyExclude,LearnNear, DepthDirectory);

%Learning the ration d_i/d_j never never worked even after more than 40 man-hours.
%   case 'Ratio'                
%      disp('LearnType is depth ratio');
%      LearnRatio(LearnAlg,HistFeaType,HistFeaDate,AbsFeaType,AbsFeaDate,WeiBatchNumber,LearnLog,SkyExclude,LearnNear);
%Learning the difference (d_i-d_j) never never worked even after more than 40 man-hours.
%   case 'Diff'         
%      disp('LearnType is depth difference');
%      LearnDiff(LearnAlg,HistFeaType,HistFeaDate,AbsFeaType,AbsFeaDate,WeiBatchNumber,LearnLog,SkyExclude,LearnNear);
   case 'DisCts'
      disp('LearnType is depth disContinuity');
      LearnDisCts(LearnAlg,HistFeaType,HistFeaDate,AbsFeaType,AbsFeaDate,WeiBatchNumber,LearnLog,SkyExclude,LearnNear);
   case 'Fractional'
      disp('LearnType is Fractional Depth');
      LearnFractionalDepth(LearnAlg,AbsFeaType,AbsFeaDate,WeiBatchNumber,LearnLog,SkyExclude,LearnNear);
   otherwise
      disp('LearnType is None.');
end
return;