[37] | 1 | % * This code was used in the following articles:
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| 2 | % * [1] Learning 3-D Scene Structure from a Single Still Image,
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| 3 | % * Ashutosh Saxena, Min Sun, Andrew Y. Ng,
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| 4 | % * In ICCV workshop on 3D Representation for Recognition (3dRR-07), 2007.
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| 5 | % * (best paper)
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| 6 | % * [2] 3-D Reconstruction from Sparse Views using Monocular Vision,
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| 7 | % * Ashutosh Saxena, Min Sun, Andrew Y. Ng,
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| 8 | % * In ICCV workshop on Virtual Representations and Modeling
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| 9 | % * of Large-scale environments (VRML), 2007.
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| 10 | % * [3] 3-D Depth Reconstruction from a Single Still Image,
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| 11 | % * Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng.
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| 12 | % * International Journal of Computer Vision (IJCV), Aug 2007.
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| 13 | % * [6] Learning Depth from Single Monocular Images,
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| 14 | % * Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng.
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| 15 | % * In Neural Information Processing Systems (NIPS) 18, 2005.
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| 16 | % *
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| 17 | % * These articles are available at:
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| 18 | % * http://make3d.stanford.edu/publications
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| 19 | % *
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| 20 | % * We request that you cite the papers [1], [3] and [6] in any of
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| 21 | % * your reports that uses this code.
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| 22 | % * Further, if you use the code in image3dstiching/ (multiple image version),
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| 23 | % * then please cite [2].
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| 24 | % *
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| 25 | % * If you use the code in third_party/, then PLEASE CITE and follow the
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| 26 | % * LICENSE OF THE CORRESPONDING THIRD PARTY CODE.
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| 27 | % *
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| 28 | % * Finally, this code is for non-commercial use only. For further
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| 29 | % * information and to obtain a copy of the license, see
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| 30 | % *
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| 31 | % * http://make3d.stanford.edu/publications/code
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| 32 | % *
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| 33 | % * Also, the software distributed under the License is distributed on an
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| 34 | % * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
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| 35 | % * express or implied. See the License for the specific language governing
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| 36 | % * permissions and limitations under the License.
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| 37 | % *
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| 38 | % */
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| 39 | function []=gen_Sup_new(sigm,k,min,SelectSegmentationPara); |
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| 40 | % this function generate superpixel using default parameter |
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| 41 | % but can also change to manually input parameter |
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| 42 | |
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| 43 | %%% Jeff's Comments |
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| 44 | % The global variable filename specifies a vector of names. For |
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| 45 | % each file specified, read in the jpg and write out a ppm of size |
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| 46 | % SegVertYSize x SegHoriXSize. Send that image to the CMU |
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| 47 | % segmentation program with params 0.8*[sigm, k, min]. If |
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| 48 | % SelectSegmenationPara is true, then display the results and ask |
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| 49 | % the user to enter new sigm, k, and min; repeat until user is happy. |
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| 50 | % |
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| 51 | % Resize both the image and the CMU output to PopUpVertY x |
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| 52 | % PopUpHoriX and write them to the scratch/ppm folder. |
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| 53 | % |
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| 54 | % Take the unresized CMU output and call suprgb2ind, converting it |
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| 55 | % from an image to a matrix of superpixel indicies. save this |
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| 56 | % index image to scratch/data/MedSeg/ and a low res (VertYNuDepth x |
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| 57 | % HoriXNuDepth) version to scratch/data/. |
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| 58 | %%%% |
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| 59 | |
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| 60 | |
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| 61 | % default parameter |
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| 62 | if nargin < 4 |
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| 63 | SelectSegmentationPara = 0; % if SelectSegmentationPara == 1, enable the parameter interation with user. |
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| 64 | end |
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| 65 | |
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| 66 | % declaim global variable |
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| 67 | global GeneralDataFolder ScratchDataFolder LocalFolder ClusterExecutionDirectory... |
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| 68 | ImgFolder VertYNuPatch VertYNuDepth HoriXNuPatch HoriXNuDepth a_default b_default Ox_default Oy_default... |
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| 69 | Horizon_default filename batchSize NuRow_default SegVertYSize SegHoriXSize PopUpVertY PopUpHoriX; |
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| 70 | |
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| 71 | scale =[0.8 1.6 5]; % use different scale to generate small(0.8) middle(1.6) 5(large) scale of superpixel |
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| 72 | |
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| 73 | % generate superpixel of each image |
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| 74 | |
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| 75 | NuPics = size(filename,2); |
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| 76 | for i = 1:NuPics |
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| 77 | %for i = 1:10 |
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| 78 | % i |
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| 79 | for j = 1:1%3% number of scale of superpixel |
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| 80 | |
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| 81 | |
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| 82 | % sigm_new = |
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| 83 | % load image and process it to Hi Medi and Low Resolution |
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| 84 | Img = imread([GeneralDataFolder '/' ImgFolder '/' filename{i} '.jpg']); % Readin the high resolution image |
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| 85 | [VertYSizeHiREs HoriXSizeHiREs dummy]= size(Img);% find the dimension size of the Hi Resolution image |
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| 86 | clear dummy; |
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| 87 | % Loadin the GroundTruth data to know the depthMap size |
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| 88 | % depthfile = strrep(filename{i},'img','depth'); % the depth filename(without .file extension) associate with the *jpg file |
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| 89 | % load([GeneralDataFolder '/depthMap/' depthfile '.mat']); |
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| 90 | % [VertYSizeLowREs HoriXSizeLowREs]= size(depthMap);% find the dimension size of the depth data |
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| 91 | % in the new laser data we have scatter depthmap so use a |
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| 92 | % predecided LowRes |
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| 93 | VertYSizeLowREs = VertYNuDepth; |
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| 94 | HoriXSizeLowREs = HoriXNuDepth; |
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| 95 | |
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| 96 | % using a fixed range of median size image [SegVertYSize SegHoriXSize ] |
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| 97 | % to generate superpixel to reduce computation |
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| 98 | if VertYSizeHiREs*HoriXSizeHiREs > SegVertYSize*SegHoriXSize |
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| 99 | % Ratio = [VertYSizeHiREs HoriXSizeHiREs]./[SegVertYSize SegHoriXSize] |
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| 100 | % Ratio = [1 1] |
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| 101 | % [VertYSizeHiREs HoriXSizeHiREs ]./floor(Ratio) |
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| 102 | % pause |
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| 103 | Img = imresize(Img,[SegVertYSize+1 SegHoriXSize+1 ],'nearest'); % Downsample high resolution image to a fixed median size image |
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| 104 | %Img = imresize(Img,[VertYSizeHiREs HoriXSizeHiREs ]./floor(Ratio),'nearest'); % Downsample high resolution image to a range of median size image |
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| 105 | imwrite(Img,[ScratchDataFolder '/ppm/' filename{i} '.ppm'],'ppm');% store median Resolution image to PPM format to feed in CMU C++ function |
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| 106 | else |
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| 107 | imwrite(Img,[ScratchDataFolder '/ppm/' filename{i} '.ppm'],'ppm');% store median Resolution image to PPM format to feed in CMU C++ function |
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| 108 | end |
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| 109 | |
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| 110 | % choose superpixel of the images |
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| 111 | % default segmentation parameter |
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| 112 | ok = 0; % ok ==1 means accept the segmentation |
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| 113 | while 1 |
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| 114 | % call segment function writen in C++ from MIT |
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| 115 | disp([LocalFolder '/../third_party/Superpixels/segment ' num2str(sigm*scale(j)) ' ' num2str(k*scale(j)) ... |
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| 116 | ' ' num2str(min*scale(j)) ' ' ScratchDataFolder '/ppm/' filename{i} '.ppm' ' ' ... |
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| 117 | ScratchDataFolder '/ppm/' filename{i} '_' num2str(sigm*scale(j)) '_' ... |
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| 118 | num2str(k*scale(j)) '_' num2str(min*scale(j)) '.ppm']); |
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| 119 | system([LocalFolder '/../third_party/Superpixels/segment ' num2str(sigm*scale(j)) ' ' num2str(k*scale(j)) ... |
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| 120 | ' ' num2str(min*scale(j)) ' ' ScratchDataFolder '/ppm/' filename{i} '.ppm' ' ' ... |
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| 121 | ScratchDataFolder '/ppm/' filename{i} '_' num2str(sigm*scale(j)) '_' ... |
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| 122 | num2str(k*scale(j)) '_' num2str(min*scale(j)) '.ppm']); |
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| 123 | % system([LocalFolder '/../third_party/Superpixels/segment ' num2str(sigm*scale(j)) ' ' num2str(k*scale(j)) ... |
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| 124 | % ' ' num2str(min*scale(j)) ' ' ScratchDataFolder '/ppm/' filename{i} '.ppm' ' ' ... |
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| 125 | % ScratchDataFolder '/ppm/' filename{i} '.ppm']); |
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| 126 | |
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| 127 | MediResImgSuperpixel = imread([ScratchDataFolder '/ppm/' filename{i} '_' num2str(sigm*scale(j)) '_' num2str(k*scale(j)) '_' num2str(min*scale(j)) '.ppm']); % Readin the high resolution image |
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| 128 | MediResImgSuperpixel = MediResImgSuperpixel(1:(end-1),1:(end-1),1:3); |
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| 129 | figure(1); image(MediResImgSuperpixel); % show the superpixel in Medi Resolution |
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| 130 | imwrite(MediResImgSuperpixel,[ScratchDataFolder '/ppm/' 'test' int2str(i) '.jpg'],'jpg'); |
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| 131 | |
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| 132 | % check if need to select segmentation parameter |
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| 133 | if SelectSegmentationPara==1; |
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| 134 | ok = input('Is the segmentation of image OK');% input new segmentation parameter |
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| 135 | else |
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| 136 | ok =1 ;% accept default segmentation parameter |
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| 137 | end |
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| 138 | |
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| 139 | % finish segmentation clean up the ppm folder. |
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| 140 | if ok==1; |
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| 141 | delete([ScratchDataFolder '/ppm/' filename{i} '_' num2str(sigm*scale(j)) '_' num2str(k*scale(j)) '_' num2str(min*scale(j)) '.ppm']); |
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| 142 | % delete([ScratchDataFolder '/ppm/' filename{i} '.ppm']); |
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| 143 | |
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| 144 | % generating [PopUpVertY, PopUpHoriX] (default 800 x 600) |
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| 145 | % .ppm superpixel and image for photopopup software. |
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| 146 | newfilename = strrep(filename{i},'.','') |
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| 147 | SupPopup = imresize(MediResImgSuperpixel,[PopUpVertY, PopUpHoriX],'nearest'); |
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| 148 | imwrite(SupPopup,[ScratchDataFolder '/ppm/' newfilename '.ppm'],'ppm'); |
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| 149 | ImgPopup = imresize(Img,[PopUpVertY, PopUpHoriX],'nearest'); |
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| 150 | imwrite(ImgPopup,[ScratchDataFolder '/ppm/' newfilename '.jpg'],'jpg'); |
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| 151 | % return; |
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| 152 | break; |
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| 153 | end |
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| 154 | sigm = input('type sigm of segmentation'); |
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| 155 | k = input('type k of segmentation'); |
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| 156 | min = input('type min of segmentation'); |
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| 157 | |
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| 158 | end |
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| 159 | % ============used to test no residual superpixel================ |
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| 160 | % end; |
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| 161 | %end; |
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| 162 | %return; |
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| 163 | % =============================================================== |
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| 164 | |
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| 165 | % index superpixel |
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| 166 | [MediResImgIndexSuperpixelSepTemp dummy]= suprgb2ind(MediResImgSuperpixel); clear dummy; |
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| 167 | LowResImgIndexSuperpixelSep{i,j} = imresize(MediResImgIndexSuperpixelSepTemp,... |
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| 168 | [VertYSizeLowREs HoriXSizeLowREs],'nearest'); %Downsample to size size as prediected depth map |
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| 169 | |
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| 170 | % merage all small point in higher scale segmentation |
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| 171 | if j ~= 1 |
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| 172 | LowResImgIndexSuperpixelSep{i,j} = premergAllsuperpixel(LowResImgIndexSuperpixelSep{i,j}); |
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| 173 | end |
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| 174 | if j == 1; |
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| 175 | MediResImgIndexSuperpixelSep = MediResImgIndexSuperpixelSepTemp; |
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| 176 | end |
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| 177 | % refining superpixel |
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| 178 | % superpixel segmentation LowResImgSeperatedSuperpixel |
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| 179 | %LowResImgsuperpixel = imresize(MediResImgSuperpixel,[VertYSizeLowREs HoriXSizeLowREs],'nearest'); %Downsample high resolution image to the same pixel size of GroundTruth data |
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| 180 | %[LowResImgIndexSuperpixel LowResImgIndexSuperpixel_list]= suprgb2ind(LowResImgsuperpixel); |
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| 181 | |
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| 182 | % comment: cmu's superpixel might be connected. use premergsuperpixel to |
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| 183 | % deal with nonconnected superpixels and very small superpixels |
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| 184 | %[LowResImgIndexSuperpixelSepTemp]=premergsuperpixel(LowResImgIndexSuperpixel); % hard work 1min |
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| 185 | |
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| 186 | % reorder the index number of the LowResImgIndexSuperpixelSep |
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| 187 | %[LowResImgIndexSuperpixelSep{i,j} LowResImgIndexSuperpixelSep_list]= ordersup(LowResImgIndexSuperpixelSepTemp); |
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| 188 | |
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| 189 | % show superpixel |
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| 190 | figure(2); |
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| 191 | imagesc(LowResImgIndexSuperpixelSep{i,j}); |
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| 192 | newmap = rand(max(max(LowResImgIndexSuperpixelSep{i,j})),3); |
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| 193 | colormap(newmap); |
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| 194 | |
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| 195 | % process the MediResImgSuperpixel to have the same number of |
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| 196 | % LowResImgIndexSuperpixelSep |
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| 197 | % if j==1 |
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| 198 | % tic |
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| 199 | % [MediResImgIndexSuperpixel dummy]= suprgb2ind(MediResImgSuperpixel); clear dummy; |
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| 200 | % MediResImgIndexSuperpixelSep = imresize(LowResImgIndexSuperpixelSep{i,1},size(MediResImgIndexSuperpixel),'nearest'); |
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| 201 | % NuSupMedi = max(max(MediResImgIndexSuperpixel)); |
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| 202 | % LowToMediResImgIndexSuperpixel = zeros(size(MediResImgIndexSuperpixel)); |
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| 203 | % for k = 1:NuSupMedi |
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| 204 | % mask = MediResImgIndexSuperpixel==k; |
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| 205 | % LowToMediResImgIndexSuperpixel(mask) = analysesupinpatch(MediResImgIndexSuperpixelSep(mask)); |
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| 206 | % % [list_sup] = analysesupinpatch(MediResImgIndexSuperpixelSep(mask)); |
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| 207 | % % [I C] = max(list_sup(2,:)); |
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| 208 | % % LowToMediResImgIndexSuperpixel(mask) = list_sup(1,C); |
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| 209 | % end |
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| 210 | % LowToMediResImgIndexSuperpixelSep{i} =... |
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| 211 | % premergAllsuperpixel(LowToMediResImgIndexSuperpixel); |
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| 212 | % toc |
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| 213 | % end |
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| 214 | % =============== |
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| 215 | end |
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| 216 | save([ScratchDataFolder '/data/MedSeg/MediResImgIndexSuperpixelSep' num2str(i) '.mat'], 'MediResImgIndexSuperpixelSep'); |
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| 217 | end |
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| 218 | % ============= |
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| 219 | |
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| 220 | % save result for later application |
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| 221 | save([ScratchDataFolder '/data/LowResImgIndexSuperpixelSep.mat'], 'LowResImgIndexSuperpixelSep'); |
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| 222 | |
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| 223 | return; |
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