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nmb_of_modules=40; |
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nmb_of_module_subsets=2; |
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channels_names={'R','G','B','RGg1','RBg1','GBg1','RGg2','RBg2','GBg2','RB','RG','GB','eRGB','BW','X','Y','Z'}; |
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feature_RGB=[1 0 0 |
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0 1 0 |
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0 0 1 |
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0.618 0.382 0 |
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0.618 0 0.382 |
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0 0.618 0.382 |
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0.382 0.618 0 |
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0.382 0 0.618 |
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0 0.382 0.618 |
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0.5 0.5 0 |
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0.5 0 0.5 |
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0 0.5 0.5 |
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1/3 1/3 1/3 |
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0.299 0.587 0.114 |
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0.4125 0.3576 0.1804 |
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0.2126 0.7152 0.0722 |
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0.0193 0.1192 0.9502]; |
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nmb_of_colors=length(channels_names); |
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patch=0; |
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nmb_of_labs_per_module=25; |
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cross_entropy=1; |
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param.image_size=[64,64]; |
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param.downsizing=2; |
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param.x_trim=1; |
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param.y_trim=1; |
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param.compute_decimal_place=4; |
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param.dwnsz_on=1; |
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param.patch=patch; |
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param.nmb_of_modules=nmb_of_modules; |
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param.nmb_of_module_subsets=nmb_of_module_subsets; |
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param.cross_entropy=cross_entropy; |
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param.nmb_of_labs_per_module=nmb_of_labs_per_module; |
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param.channels_names=channels_names; |
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param.nmb_of_colors=nmb_of_colors; |
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param.feature_RGB=feature_RGB; |
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parfor module=1:nmb_of_modules |
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data_param=[]; |
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for subset=1:nmb_of_module_subsets |
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reportname1 = sprintf('Transformed_IN1k_Data/Modularized_Data_for_SGD/modularized_data_patch_%d_module_%d_subset_%d_for_%d_labels_per_module.mat', ... |
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patch,module,subset,nmb_of_labs_per_module); |
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data_load=load(reportname1); |
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data_0=data_load.data; |
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output=fun_transform_data_rgbfeatures(data_0,param); |
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data=output.transformed_image; |
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data_param.mnsv=output.mnsv; |
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data_param.maxsv=output.maxsv; |
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data_param.ipvsz=output.ipvsz; |
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labels=data_load.labels; |
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label_ids=data_load.label_ids; |
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label_table=data_load.label_table; |
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out=fun_save_transformed_data(patch, module, subset,nmb_of_labs_per_module,data,labels,label_ids,label_table,data_param); |
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end |
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module |
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end |
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