72 lines
2.8 KiB
Plaintext
72 lines
2.8 KiB
Plaintext
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# extend picture relation with distdata objects for all avaliable types:
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let images2 = images feed extend[
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hsv128: getdistdata2(.Pic, hsv128),
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hsv256: getdistdata2(.Pic, hsv256),
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lab256: getdistdata2(.Pic, lab256),
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hsv128_ncompr: getdistdata2(.Pic, hsv128_ncompr),
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hsv256_ncompr: getdistdata2(.Pic, hsv256_ncompr),
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lab256_ncompr: getdistdata2(.Pic, lab256_ncompr)] consume;
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# create mtrees for all avaliable data and distance function types:
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# (using default config object)
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let mt_hsv128E = images2 createmtree2[hsv128, default, euclid];
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let mt_hsv128Q = images2 createmtree2[hsv128, default, quadratic];
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let mt_hsv256E = images2 createmtree2[hsv256, default, euclid];
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let mt_hsv256Q = images2 createmtree2[hsv256, default, quadratic];
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let mt_lab256E = images2 createmtree2[lab256, default, euclid];
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let mt_lab256Q = images2 createmtree2[lab256, default, quadratic];
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let mt_hsv128E_ncompr = images2 createmtree2[hsv128_ncompr, default, euclid];
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let mt_hsv128Q_ncompr = images2 createmtree2[hsv128_ncompr, default, quadratic];
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let mt_hsv256E_ncompr = images2 createmtree2[hsv256_ncompr, default, euclid];
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let mt_hsv256Q_ncompr = images2 createmtree2[hsv256_ncompr, default, quadratic];
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let mt_lab256E_ncompr = images2 createmtree2[lab256_ncompr, default, euclid];
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let mt_lab256Q_ncompr = images2 createmtree2[lab256_ncompr, default, quadratic];
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# create a mtree with default values from picture attribute
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query images createmtree[Pic];
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# createmtree3 operator (only needed for non-distdata attributes - distdata will
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# also work, but the last parameter is ignored in this case, leading to the same
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# signature as createmtree2)
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let mt = images createmtree3[Pic, mlbdistHP, euclid, lab256];
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let mt = images createmtree3[Pic, randomBal, quadratic, hsv256];
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# example search querries (assuming an existung picture p1)
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# The relation must contain at least the tuples-ids, that had been indized in
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# the mtree, otherwhise the query would lead to a crash in the current version!
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query mt_lab256E nnsearch(images, p1, 10);
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query mt_lab256E rangesearch(images, p1, 0.1);
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# examples for gdistance operator (assuming two pictures p1 and p2)
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query gdistance(p1, p2);
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query gdistance2(p1, p2, quadratic);
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query gdistance3(p1, p2, euclid, lab256);
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query gdistance3(p1, p2, euclid, hsv256);
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# the same gdistance queries with distdata attributes:
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#
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# create distdata attributes:
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let dd1 = getdistdata(p1);
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let dd2 = getdistdata(p2);
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let dd1_lab256 = getdistdata2(p1, lab256);
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let dd2_lab256 = getdistdata2(p2, lab256);
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let dd1_hsv256 = getdistdata2(p1, hsv256);
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let dd2_hsv256 = getdistdata2(p2, hsv256);
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# use distdata attributes to compute the distance between p1 and p2:
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query gdistance(dd1, dd2);
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query gdistance2(dd1, dd2, quadratic);
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query gdistance2(dd1_lab256, dd2_lab256, euclid);
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query gdistance2(dd1_hsv256, dd2_hsv256, euclid);
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