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 []=Depth_error(DepthDirectory, SkyExclude, detail,baseline) |
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40 | |
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41 | global GeneralDataFolder ScratchDataFolder LocalFolder ClusterExecutionDirectory... |
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42 | ImgFolder VertYNuPatch VertYNuDepth HoriXNuPatch HoriXNuDepth a_default b_default Ox_default Oy_default... |
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43 | Horizon_default filename batchSize NuRow_default SegVertYSize SegHoriXSize WeiBatchSize PopUpVertY PopUpHoriX taskName; |
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44 | |
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45 | % prepare report |
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46 | ReportName = [ScratchDataFolder '/result/DepthErrorTable.txt' ]; |
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47 | check = dir(ReportName) |
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48 | DateStamp = date; |
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49 | if isempty(check) |
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50 | disp('is empty') |
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51 | fid = fopen(ReportName, 'w+'); |
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52 | fprintf(fid, '%s %s %s %s %s %s %s\n', DateStamp,'MeanAbsError','RMSError','MeanAbsLogError','RMSLogError','MeanAbsFraError','RMSFraError'); |
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53 | fclose(fid); |
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54 | end |
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55 | DepthDirectory |
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56 | check = dir([DepthDirectory]); |
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57 | if isempty(check) |
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58 | disp('empty') |
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59 | end |
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60 | %return; |
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61 | |
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62 | NuPics = size(filename,2); |
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63 | load([ScratchDataFolder '/data/MaskGSky.mat']); |
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64 | l =1; |
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65 | PicsInd = [19:60 109:134] % for Ashutosh preivious work |
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66 | %for i= 1:NuPics |
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67 | for i= PicsInd |
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68 | % in case can't find the laser depth |
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69 | depthfile = strrep(filename{i},'img','depth_sph_corr'); |
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70 | check = dir([ScratchDataFolder '/Gridlaserdata/' depthfile '.mat']); |
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71 | if isempty(check) |
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72 | continue; |
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73 | end |
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74 | load([ScratchDataFolder '/Gridlaserdata/' depthfile '.mat']); |
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75 | laserdepth = Position3DGrid(:,:,4); |
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76 | clear Position3DGrid; |
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77 | |
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78 | % load learned or predicted depth |
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79 | depthfile = strrep(filename{i},'img','depth_learned'); |
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80 | if baseline ==1 |
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81 | disp('load baseline') |
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82 | check = dir([DepthDirectory '_baseline/' depthfile '.mat']) |
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83 | if isempty(check) |
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84 | continue; |
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85 | end |
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86 | load([DepthDirectory '_baseline/' depthfile '.mat']); |
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87 | depthMap = depthMap_base; |
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88 | elseif baseline == 2 |
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89 | disp('load baseline2') |
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90 | check = dir([DepthDirectory '_baseline2/' depthfile '.mat']) |
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91 | if isempty(check) |
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92 | continue; |
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93 | end |
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94 | load([DepthDirectory '_baseline2/' depthfile '.mat']); |
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95 | depthMap = depthMap_base2; |
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96 | else |
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97 | check = dir([DepthDirectory '/' depthfile '.mat']) |
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98 | if isempty(check) |
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99 | continue; |
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100 | end |
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101 | load([DepthDirectory '/' depthfile '.mat']); |
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102 | end |
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103 | |
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104 | i |
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105 | filename{i} |
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106 | % calculate average abs error RMS error on linear and log scale, and fractional error |
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107 | if SkyExclude == 1 |
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108 | disp('Sky Exlude') |
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109 | |
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110 | % remove big error so that it won't effect linear and fractional term |
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111 | AbsLogError=abs( log10(depthMap(:))-log10(laserdepth(:)) ); |
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112 | %AbsLogError = AbsLogError(mask); % get rid of the sky |
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113 | % do auto scaling =============like for CMU |
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114 | if median(depthMap(:)) >20 |
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115 | continue; |
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116 | end |
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117 | scale = median(AbsLogError(:)); |
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118 | depthMap = depthMap*exp(scale); |
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119 | % laserdepth = laserdepth*exp(-scale); |
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120 | |
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121 | % ======================================== |
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122 | maskBigError = (depthMap >70); % 80+30 |
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123 | % maskBigError = (depthMap >Inf); % 80+30 |
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124 | |
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125 | mask = ~(maskSky{i}|maskBigError); |
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126 | sum(mask(:)) |
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127 | AbsLogError=abs( log10(depthMap(:))-log10(laserdepth(:)) ); |
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128 | AbsLogError = AbsLogError(mask); % get rid of the sky |
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129 | AbsError=abs( (depthMap(:))-(laserdepth(:)) ); |
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130 | AbsError = AbsError(mask); |
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131 | AbsFraError = abs( (depthMap(:)-laserdepth(:))./laserdepth(:)); |
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132 | AbsFraError = AbsFraError(mask); |
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133 | else |
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134 | AbsLogError=abs( log10(depthMap(:))-log10(laserdepth(:)) ); |
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135 | AbsError=abs( (depthMap(:))-(laserdepth(:)) ); |
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136 | AbsFraError = abs( (depthMap(:)-laserdepth(:))./laserdepth(:)); |
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137 | end |
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138 | |
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139 | |
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140 | WholeAbsLogError{l} = AbsLogError; |
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141 | WholeAbsError{l} = AbsError; |
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142 | WholeAbsFraError{l} = AbsFraError; |
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143 | l = l +1; |
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144 | |
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145 | end |
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146 | |
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147 | MeanAbsError = mean(cell2mat(WholeAbsError')); |
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148 | RMSError = sqrt(mean(cell2mat(WholeAbsError').^2)); |
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149 | MeanAbsLogError = mean(cell2mat(WholeAbsLogError')); |
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150 | RMSLogError = sqrt(mean(cell2mat(WholeAbsLogError').^2)); |
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151 | MeanAbsFraError = mean(cell2mat(WholeAbsFraError')); |
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152 | RMSFraError = sqrt(mean(cell2mat(WholeAbsFraError').^2)); |
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153 | if detail |
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154 | disp('report detail'); |
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155 | save([ScratchDataFolder '/result/DepthErrorReport' DateStamp '.mat'],... |
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156 | 'WholeAbsError','WholeAbsLogError','WholeAbsFraError','MeanAbsError','RMSError','MeanAbsLogError','RMSLogError','MeanAbsFraError','RMSFraError'); |
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157 | end |
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158 | |
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159 | fid = fopen(ReportName, 'a+'); |
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160 | fprintf(fid, '%s %g %g %g %g %g %g\n %s %d\n', DateStamp,MeanAbsError,RMSError,MeanAbsLogError,RMSLogError,MeanAbsFraError,RMSFraError, DepthDirectory, baseline); |
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161 | fclose(fid); |
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162 | |
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163 | |
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