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  • Committer: Suren A. Chilingaryan
  • Date: 2010-04-22 13:42:41 UTC
  • Revision ID: csa@dside.dyndns.org-20100422134241-fv5m2ufk8n2tc9h5
Implementation of image and fragment modes, support for non-cacheable grids

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automate_image.m
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% 0 - in the end
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% 1 - per iteration
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OPTIMIZE = 5;
 
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OPTIMIZE = 4;
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CORRSIZE = 15;  
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PRECISION = 1000;
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SILENT = 1;
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if OPTIMIZE > 2
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%    Verification of GPU local sum and denom computations
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%    dic_basecorr3(CORRSIZE, PRECISION, OPTIMIZE, hwid, base_points_x, base_points_y, base);
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    normxcorr_hw(hwid, 3, base_points_x, base_points_y);
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    if OPTIMIZE > 4
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        normxcorr_hw(hwid, 4, strcat(imagedir, filenamelist(1,:)));
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    else
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        base = uint8(mean(double(imread([imagedir, filenamelist(1,:)])),3));            % read in the base image ( which is always  image number one. You might want to change that to improve correlation results in case the light conditions are changing during the experiment
 
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%       Verification of GPU local sum and denom computations
 
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%       dic_basecorr3(CORRSIZE, PRECISION, OPTIMIZE, hwid, base_points_x, base_points_y, base);
 
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        normxcorr_hw(hwid, 4, base);
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    end 
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else
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        normxcorr_hw(hwid, 13, strcat(imagedir, filenamelist((i+1),:)));
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        input_correl = normxcorr_hw(hwid, 14);
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    elseif OPTIMIZE > 2
 
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        input = uint8(mean(double(imread([imagedir, filenamelist((i+1),:)])),3));       % read in the image which has to be correlated
 
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        %Validate findpeak
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        %dic_cpcorr3(CORRSIZE, PRECISION, OPTIMIZE, hwid, ncp, input);
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        input = uint8(mean(double(imread([imagedir, filenamelist((i+1),:)])),3));       % read in the image which has to be correlated
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        normxcorr_hw(hwid, 13, input)
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        input_correl = normxcorr_hw(hwid, 14);
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    elseif OPTIMIZE > 0