Notebooks Classificador
This commit is contained in:
DiogoCosta18
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Load Diff
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@@ -0,0 +1,961 @@
|
||||
run,architecture,grid,grid_index,tile_index,row,col,source_path,score,mean,std,saturation,sharpness,exposure_score,contrast_score,detail_score,color_score
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.7545376674909341,0.5586341023445129,0.12475372850894928,0.3098646104335785,0.012272229418158531,0.7542684301733971,0.519807202120622,1.0,0.8154331853515223
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.7593448067256836,0.35332736372947693,0.14404259622097015,0.3831081986427307,0.008653096854686737,0.6041480116546154,0.6001774842540424,0.9921886318123451,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.9525878772923821,0.5241501331329346,0.3510676324367523,0.3647458553314209,0.022909104824066162,0.8620308339595795,1.0,1.0,0.959857514030055
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.7095987265826474,0.49222832918167114,0.0913277193903923,0.29169315099716187,0.0034171135630458593,0.9617864713072777,0.3805321641266346,0.7670444106564817,0.7676135552556891
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.9141213849186898,0.38839614391326904,0.248654305934906,0.4194767475128174,0.013700177893042564,0.7137379497289658,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.9496999841967695,0.47258105874061584,0.33243075013160706,0.27019327878952026,0.03126365691423416,0.9768158085644245,1.0,1.0,0.7110349441829481
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.8351491647723474,0.45492032170295715,0.24781660735607147,0.021942120045423508,0.017632482573390007,0.9216260053217411,1.0,1.0,0.05774242117216712
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.8024060817141282,0.4370657205581665,0.2197197526693344,0.045618437230587006,0.01176534965634346,0.8658303767442703,0.9154989694555601,1.0,0.12004851902786054
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.6557122263077059,0.6841288805007935,0.2226022332906723,0.047703325748443604,0.02228841930627823,0.36209724843502045,0.9275093053778013,1.0,0.12553506775906212
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.7053433787861937,0.3807450532913208,0.19525142014026642,0.010970894247293472,0.018412042409181595,0.6898282915353775,0.8135475839177768,1.0,0.02887077433498282
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.9597365334630013,0.4648057818412781,0.21918489038944244,0.42363959550857544,0.012437568977475166,0.952518068253994,0.9132703766226768,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.9016706772148609,0.5735244154930115,0.23147985339164734,0.38165542483329773,0.033601272851228714,0.7077362015843391,0.964499389131864,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.9120497883150451,0.4331885576248169,0.3386186361312866,0.26836997270584106,0.01995547115802765,0.8537142425775528,1.0,1.0,0.7062367702785292
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.8598220698535443,0.5386441349983215,0.17184075713157654,0.3957240879535675,0.017268937081098557,0.8167370781302452,0.7160031547149023,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.7806122546362527,0.4119107127189636,0.20364314317703247,0.441266804933548,0.0013961864169687033,0.7872209772467613,0.8485130965709686,0.559568129963735,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0001.png,1,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0001.png,0.8230576974192731,0.44262832403182983,0.26020944118499756,0.020503897219896317,0.011849427595734596,0.8832135125994682,1.0,1.0,0.05395762426288504
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.8998476877808571,0.5348783135414124,0.20103688538074493,0.5457454323768616,0.01619734987616539,0.8285052701830864,0.8376536890864372,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.9812861617654561,0.46003857254981995,0.27224647998809814,0.4570789933204651,0.023630764335393906,0.9376205392181873,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.7420650539086349,0.5928292274475098,0.3344661593437195,0.02122393250465393,0.007521435152739286,0.647408664226532,1.0,0.9578583461869316,0.055852453959615606
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.9720733910014754,0.4618774652481079,0.2704009711742401,0.35229361057281494,0.025064971297979355,0.9433670789003372,1.0,1.0,0.9270884488758288
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.833084571145867,0.4547576606273651,0.31825003027915955,0.017098136246204376,0.030236052349209785,0.921117689460516,1.0,1.0,0.04499509538474836
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.7242124849244168,0.6618639230728149,0.1652834117412567,0.34986764192581177,0.03201981633901596,0.4316752403974533,0.6886808822552364,1.0,0.9207043208573994
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.7384208043400002,0.6048873662948608,0.3096829056739807,0.01394019927829504,0.027470922097563744,0.6097269803285599,1.0,1.0,0.036684734942881686
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.6106346278251241,0.21221114695072174,0.1588122397661209,0.4094204604625702,0.004881285130977631,0.16315983422100555,0.6617176656921705,0.8526855114046854,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.5587454412524638,0.23907819390296936,0.18229030072689056,0.017091788351535797,0.015121573582291603,0.24711935594677936,0.7595429196953773,1.0,0.04497839039877841
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.7776214455188818,0.4174554944038391,0.14888633787631989,0.49546483159065247,0.003931847400963306,0.8045484200119972,0.6203597411513329,0.8005959886795313,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.6441286732110473,0.21925386786460876,0.17080029845237732,0.5611382722854614,0.005940636619925499,0.1851683370769025,0.7116679102182388,0.9003111960900193,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.955621548742056,0.5273370146751404,0.30989617109298706,0.41411760449409485,0.015149565413594246,0.8520718291401863,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.9379227348064122,0.5395410060882568,0.254978746175766,0.36414748430252075,0.01970071718096733,0.8139343559741974,1.0,1.0,0.9582828534276862
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.7201142754209668,0.6283286809921265,0.17947918176651,0.21488603949546814,0.03531326353549957,0.5364728718996048,0.7478299240271251,1.0,0.565489577619653
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.8876708376564477,0.3642846345901489,0.2504919767379761,0.37025678157806396,0.018406979739665985,0.6383894830942154,1.0,1.0,0.9743599515212209
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0002.png,2,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0002.png,0.9283315275452638,0.47205090522766113,0.22538556158542633,0.2635980248451233,0.011152489110827446,0.975159078836441,0.9391065066059431,1.0,0.6936790127503244
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.8586176541802989,0.528627336025238,0.2003055214881897,0.36663907766342163,0.004562776070088148,0.8480395749211311,0.8346063395341238,0.8363917125379082,0.9648396780616358
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.7858749721199275,0.26752373576164246,0.22805717587471008,0.5977087020874023,0.016115520149469376,0.3360116742551328,0.950238232811292,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.7536362484587651,0.5852681398391724,0.23954956233501434,0.0073167141526937485,0.03268556296825409,0.6710370630025864,0.9981231763958931,1.0,0.019254510928141445
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.5154432408321509,0.3417609930038452,0.14347687363624573,0.04783596843481064,0.0015792122576385736,0.5680031031370163,0.5978203068176906,0.5872543949069381,0.125884127460028
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.8249723659142068,0.4270785450935364,0.18514028191566467,0.23600755631923676,0.015848493203520775,0.8346204534173012,0.7714178413152695,1.0,0.6210725166295704
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.8648055293058095,0.3481628894805908,0.2968728244304657,0.35062047839164734,0.012981856241822243,0.5880090296268463,1.0,1.0,0.9226854694517035
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.8721946236885333,0.3808496594429016,0.22183451056480408,0.4574553072452545,0.007325959857553244,0.6901551857590675,0.9243104606866837,0.9514197190192317,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.7095855738691413,0.27421942353248596,0.18987368047237396,0.6059479713439941,0.005044713616371155,0.35693569853901874,0.7911403353015583,0.8606510548678727,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.9354947239160538,0.5107810497283936,0.24028459191322327,0.28969162702560425,0.032173462212085724,0.9038092195987701,1.0,1.0,0.7623463869094849
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.7184575937296215,0.5963011384010315,0.1650904268026352,0.18018808960914612,0.022538598626852036,0.6365589424967766,0.6878767783443134,1.0,0.47417918318196345
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.8459408931434155,0.4996097683906555,0.131460040807724,0.48573726415634155,0.013038482517004013,0.9387194737792015,0.5477501700321834,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.814499861270924,0.44499677419662476,0.16504618525505066,0.4865788519382477,0.0033741698134690523,0.8906149193644524,0.6876924385627111,0.7640306155710997,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.6293126838085683,0.34668371081352234,0.15933012962341309,0.013006241992115974,0.012032881379127502,0.5833865962922573,0.6638755400975546,1.0,0.03422695261083151
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.6962179163568899,0.7100358009338379,0.2800619900226593,0.1567537486553192,0.02437450736761093,0.2811381220817566,1.0,1.0,0.412509864882419
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.8181977607309819,0.3186354637145996,0.21558161079883575,0.5210000276565552,0.017162248492240906,0.4957358241081239,0.8982567116618156,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0003.png,3,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0003.png,0.8527785818227757,0.5013974905014038,0.20327767729759216,0.217881977558136,0.006736705079674721,0.9331328421831131,0.8469903220733007,0.9309423550916126,0.5733736251529894
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.5895350809422575,0.36464041471481323,0.08890166878700256,0.23955386877059937,0.003430658020079136,0.6395012959837914,0.37042361994584405,0.7679874739630475,0.6304049178173667
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.8943183845595309,0.5314095616340637,0.2107905000448227,0.3268676996231079,0.02474066987633705,0.8393451198935509,0.8782937501867613,1.0,0.8601781569029155
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.8592290036380291,0.48304200172424316,0.12966470420360565,0.40858709812164307,0.018466269597411156,0.9904937446117401,0.540269600848357,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.8956946209073067,0.381428062915802,0.23048464953899384,0.3853580951690674,0.02593258023262024,0.6919626966118813,0.9603527064124744,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.7436427799943237,0.3414962887763977,0.1721288114786148,0.5121854543685913,0.004504946526139975,0.5671759024262428,0.7172033811608951,0.8333159796727292,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.8115268671265001,0.3547556400299072,0.20915274322032928,0.3197314143180847,0.007749638985842466,0.6086113750934601,0.8714697634180387,0.9651710270531206,0.8413984587318019
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.8115414392444642,0.3684893846511841,0.2586754858493805,0.31895413994789124,0.003327572252601385,0.6515293270349503,1.0,0.7607187646181933,0.8393529998628717
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.8835286594535176,0.5304690599441528,0.29684287309646606,0.20480328798294067,0.011063450947403908,0.8422841876745224,1.0,1.0,0.5389560210077387
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.9128316894173623,0.387020468711853,0.27525776624679565,0.6243563890457153,0.012326443567872047,0.7094389647245407,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.6316506314551138,0.2844827175140381,0.11516134440898895,0.30810052156448364,0.00884288176894188,0.38900849223136913,0.479838935037454,0.9975111053644723,0.8107908462223253
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.8472280944599525,0.4859713912010193,0.24093836545944214,0.007159893400967121,0.022441085427999496,0.9813394024968147,1.0,1.0,0.01884182473938716
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.4586441533185386,0.15696296095848083,0.16091114282608032,0.7654194831848145,0.0007641658885404468,0.0,0.6704630951086681,0.43002089914375247,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.7715456023812294,0.40743064880371094,0.1606440544128418,0.22489489614963531,0.015978895127773285,0.7732207775115967,0.6693502267201742,1.0,0.5918286740779877
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.8133123606443405,0.6550119519233704,0.22190885245800018,0.5648695230484009,0.038659438490867615,0.4530876502394676,0.9246202185750008,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.893380181863904,0.4470275938510895,0.1794334501028061,0.488193541765213,0.013053730130195618,0.8969612307846546,0.7476393754283588,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0004.png,4,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0004.png,0.8741027908889871,0.4827801585197449,0.15858162939548492,0.3254881203174591,0.016781821846961975,0.9913120046257973,0.6607567891478539,1.0,0.856547685045945
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.907768871125422,0.448178231716156,0.2107820361852646,0.3144480586051941,0.021893009543418884,0.9005569741129875,0.8782584841052692,1.0,0.8274948910663003
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.8039472896997866,0.44701677560806274,0.2252752035856247,0.008296813815832138,0.021059446036815643,0.8969274237751961,0.9386466816067696,1.0,0.02183372056797931
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.9318601943552495,0.5526824593544006,0.25198668241500854,0.3896118402481079,0.032747358083724976,0.772867314517498,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.8767036567000966,0.4646499752998352,0.1851481795310974,0.2778030037879944,0.028165467083454132,0.952031172811985,0.7714507480462393,1.0,0.7310605362841958
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.38463021956243315,0.23538875579833984,0.11072921752929688,0.01894732192158699,0.00228615989908576,0.23558986186981212,0.4613717397054037,0.6722501322727574,0.0498613734778605
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.7372267697273276,0.286445677280426,0.2164098471403122,0.46430760622024536,0.0038042094092816114,0.39514274150133144,0.9017076964179676,0.7926865534061516,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.8786685809493066,0.6094201803207397,0.2474713772535324,0.38691121339797974,0.023118214681744576,0.5955619364976883,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.8696450907737017,0.35869845747947693,0.22669222950935364,0.5497492551803589,0.013579826802015305,0.6209326796233654,0.9445509562889736,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.8233137778937817,0.5261629819869995,0.13327325880527496,0.49656835198402405,0.021564697846770287,0.8557406812906265,0.5553052450219791,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.382277699169396,0.16975241899490356,0.07428576797246933,0.6958059668540955,0.001173350028693676,0.03047630935907375,0.3095240332186222,0.521110385584349,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.7702151579907561,0.3096632659435272,0.19988080859184265,0.3563356399536133,0.007513006683439016,0.4676977060735227,0.832836702466011,0.9575841207361948,0.9377253682989823
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.9107583697885275,0.3848089277744293,0.2420244812965393,0.39233115315437317,0.0095355324447155,0.7025278992950916,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.9117341909557581,0.38584980368614197,0.2577420771121979,0.3969506323337555,0.028145231306552887,0.7057806365191936,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.9243011623620987,0.4225029945373535,0.22256368398666382,0.5036839246749878,0.03184037283062935,0.8203218579292297,0.927348683277766,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.6619402099524138,0.26035311818122864,0.16354040801525116,0.531673789024353,0.004902512766420841,0.3136034943163396,0.6814183667302132,0.8537346065537919,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0005.png,5,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0005.png,0.8609141348583063,0.44484877586364746,0.17759594321250916,0.3676582872867584,0.0061057633720338345,0.8901524245738983,0.7399830967187881,0.9069808286923825,0.9675218086493642
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.875421778857708,0.5746668577194214,0.21133756637573242,0.3896825909614563,0.03409885615110397,0.7041660696268082,0.8805731932322185,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.7810890753741003,0.4248238503932953,0.24505583941936493,0.011037391610443592,0.006280225235968828,0.8275745324790478,1.0,0.9138394020840022,0.029045767395904188
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.7865731326373,0.5845127105712891,0.3116176724433899,0.0875362902879715,0.022526144981384277,0.6733977794647217,1.0,1.0,0.23035865865255656
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.8591934063749928,0.3876144587993622,0.21951551735401154,0.32111066579818726,0.00818733312189579,0.7112951837480068,0.9146479889750481,0.9786249774983253,0.8450280678899664
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.6532358039510788,0.3147972822189331,0.11174239218235016,0.70570969581604,0.005324860103428364,0.48374150693416607,0.46559330075979233,0.8737414465715652,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.7858239174281296,0.3296286463737488,0.24441830813884735,0.19455255568027496,0.01192161999642849,0.5300895199179649,1.0,1.0,0.5119804096849341
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.8589211200609018,0.47416725754737854,0.318678081035614,0.03645293414592743,0.0220384132117033,0.9817726798355579,1.0,1.0,0.09592877406823007
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.9243404397446858,0.4492695927619934,0.2036893665790558,0.3762975037097931,0.014060743153095245,0.9039674773812294,0.8487056940793991,1.0,0.9902565887099818
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.8971401409883248,0.5035743713378906,0.17587903141975403,0.378460556268692,0.016842877492308617,0.9263300895690918,0.7328292975823085,1.0,0.9959488322860316
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.7544976327801437,0.36918866634368896,0.14592470228672028,0.5229775905609131,0.006029176525771618,0.653714582324028,0.6080195928613346,0.9039095208981394,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.6670329091978492,0.24327167868614197,0.1800692081451416,0.388423889875412,0.004938778933137655,0.26022399589419376,0.7502883672714233,0.8555168009926564,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.7846233867108079,0.3194371163845062,0.20846299827098846,0.5017948150634766,0.005891444161534309,0.49824098870158207,0.8685958261291187,0.8982893690463906,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.6997036429714174,0.37598657608032227,0.12620475888252258,0.278771311044693,0.006379921920597553,0.6749580502510071,0.5258531620105108,0.9176758892065436,0.7336087132755079
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.9343138402229861,0.5160537958145142,0.24139896035194397,0.29922282695770264,0.009966598823666573,0.8873318880796432,1.0,1.0,0.7874284919939543
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.8053720891475677,0.394361674785614,0.1485264152288437,0.3891766667366028,0.012834908440709114,0.7323802337050438,0.6188600634535154,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0006.png,6,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0006.png,0.43927690061584435,0.15315912663936615,0.08104534447193146,0.5397039651870728,0.0032062034588307142,0.0,0.33768893529971444,0.75188088010372,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.8493201643228531,0.4572209119796753,0.17145398259162903,0.2694404721260071,0.012126946821808815,0.9288153499364853,0.7143915941317877,1.0,0.7090538740158081
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.769081329384276,0.30254387855529785,0.2055985927581787,0.39737173914909363,0.006279023829847574,0.4454496204853059,0.856660803159078,0.9137928091638432,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.8151628826815037,0.5378580689430237,0.1702156662940979,0.40093761682510376,0.004380045458674431,0.819193534553051,0.7092319428920746,0.826540957791864,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.6111208545718048,0.591734766960144,0.1315007209777832,0.0037906200159341097,0.02074606902897358,0.6508288532495499,0.5479196707407634,1.0,0.009975315831405552
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.646148418909625,0.7471302151679993,0.20146562159061432,0.2400357872247696,0.0406423881649971,0.1652180776000023,0.839440089960893,1.0,0.6316731242757094
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.8904819957964021,0.40772008895874023,0.3016814589500427,0.32071495056152344,0.006617442704737186,0.7741252779960632,1.0,0.9265856223879277,0.843986712004009
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.7260528919725296,0.3227294385433197,0.1426870971918106,0.49903637170791626,0.008251594379544258,0.5085294954478741,0.5945295716325443,0.9805406873936162,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.7036572464083265,0.35407277941703796,0.22536706924438477,0.009349950589239597,0.0071435365825891495,0.6064774356782436,0.9390294551849365,0.9452576367197429,0.024605133129577888
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.7750198364946898,0.5274783372879028,0.16703392565250397,0.241154283285141,0.0050767576321959496,0.8516301959753036,0.6959746902187666,0.8621835615693362,0.6346165349608973
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.8794440545141697,0.351406991481781,0.2869923710823059,0.5339280366897583,0.024457525461912155,0.5981468483805656,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.8372685394396907,0.3613077402114868,0.21205411851406097,0.33813637495040894,0.009057862684130669,0.6290866881608963,0.8835588271419208,1.0,0.8898325656589708
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.8015177220302192,0.390240341424942,0.15443000197410583,0.3613290786743164,0.011990748345851898,0.7195010669529438,0.6434583415587743,1.0,0.950865996511359
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.8176741555725273,0.40279310941696167,0.18400675058364868,0.27878618240356445,0.01006361935287714,0.7587284669280052,0.7666947940985362,1.0,0.7336478484304327
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.9672669764608145,0.48784127831459045,0.21969453990459442,0.4469306170940399,0.012913118116557598,0.9754960052669048,0.9153939162691435,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.9368669483810663,0.4143889248371124,0.23870186507701874,0.4027857184410095,0.010187076404690742,0.7949653901159763,0.9945911044875781,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0007.png,7,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0007.png,0.780505416539763,0.34109261631965637,0.19911116361618042,0.5398318767547607,0.004775059409439564,0.5659144259989262,0.8296298484007518,0.8473685368794388,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.7970287408912766,0.5013858675956726,0.22536815702915192,0.011146023869514465,0.006544208154082298,0.9331691637635231,0.9390339876214664,0.9238721968459908,0.029331641761880172
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.7108458863424235,0.43045708537101746,0.16398027539253235,0.005869795568287373,0.011441962793469429,0.8451783917844296,0.6832511474688848,1.0,0.015446830442861506
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.7697381906155869,0.4496918022632599,0.11186768114566803,0.5492039918899536,0.004504089243710041,0.9052868820726871,0.46611533810695016,0.833270098246783,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.6989638672105051,0.35959097743034363,0.13119755685329437,0.5479761362075806,0.0037838509306311607,0.6237218044698238,0.5466564868887266,0.7914015192117597,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.8932776227593422,0.5262240171432495,0.22980892658233643,0.25169041752815247,0.01662326045334339,0.8555499464273453,0.9575371940930685,1.0,0.6623432040214539
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.6088977974402533,0.3927351236343384,0.14018476009368896,0.005774964112788439,0.00488344207406044,0.7272972613573074,0.5841031670570374,0.8527923112751862,0.015197273981022207
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.882893174082825,0.40290549397468567,0.22173728048801422,0.32426077127456665,0.014655661769211292,0.7590796686708927,0.9239053353667259,1.0,0.8533178191435964
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.7554918011846511,0.5855017304420471,0.2542382478713989,0.011145839467644691,0.01503431424498558,0.6703070923686028,1.0,1.0,0.02933115649380182
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.5396268888817806,0.844924807548523,0.2291971743106842,0.007930399850010872,0.05406677722930908,0.0,0.9549882262945175,1.0,0.020869473289502293
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.8613160230219364,0.5235291719436646,0.16169969737529755,0.40834808349609375,0.019339991733431816,0.8639713376760483,0.6737487390637398,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.7321886953701707,0.6097853779792786,0.31042152643203735,0.009784967638552189,0.01916937530040741,0.5944206938147545,1.0,1.0,0.025749914838295234
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.8331833370029926,0.33568674325942993,0.21478161215782166,0.40492361783981323,0.015957213938236237,0.5490210726857185,0.8949233839909236,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.5088473971517982,0.12006480991840363,0.10350232571363449,0.40002232789993286,0.006385215558111668,0.0,0.43125969047347706,0.9178779600390201,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.7030484216346921,0.2965622544288635,0.1651538461446762,0.3865181505680084,0.005337495356798172,0.42675704509019863,0.6881410256028175,0.8743160017071486,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.8323472074380046,0.39097630977630615,0.21305964887142181,0.2520219683647156,0.0095682917162776,0.7218009680509567,0.8877485369642576,1.0,0.6632157062229357
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0008.png,8,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0008.png,0.5792033701237205,0.18457084894180298,0.1619434654712677,0.517056941986084,0.0041741495952010155,0.07678390294313442,0.6747644394636154,0.8149554696067822,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.8595949189116271,0.485787957906723,0.1843118816614151,0.298603355884552,0.005179741885513067,0.9819126315414906,0.7679661735892296,0.8670461265140358,0.7857983049593473
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.6028219508007169,0.19069211184978485,0.13923847675323486,0.437399297952652,0.01030984427779913,0.09591284953057777,0.5801603198051453,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.7336863054232182,0.5513945817947388,0.1982884407043457,0.006987376604229212,0.012560537084937096,0.7768919318914413,0.8262018362681072,1.0,0.018387833169024242
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.6670747307930264,0.6282001733779907,0.10933477431535721,0.3718968629837036,0.0056978557258844376,0.536874458193779,0.4555615596473217,0.890170128630621,0.9786759552202726
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.4287850607902928,0.2971642017364502,0.09910248965024948,0.008129455149173737,0.002492319094017148,0.42863813042640697,0.4129270402093729,0.6924260565837508,0.021393303024141413
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.8743150602045812,0.4599578380584717,0.2946867346763611,0.10919828712940216,0.02124294824898243,0.937368243932724,1.0,1.0,0.2873639134984267
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.8105629876452056,0.4211808145046234,0.1557983011007309,0.3064271807670593,0.012138865888118744,0.8161900453269482,0.6491595879197121,1.0,0.8063873178080508
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.804760357855182,0.5664476752281189,0.1747012436389923,0.2974855303764343,0.023043829947710037,0.7298510149121284,0.7279218484958013,1.0,0.7828566588853535
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.6948749497532846,0.2902379035949707,0.13822153210639954,0.44017231464385986,0.010719917714595795,0.40699344873428356,0.5759230504433315,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.8288026563823223,0.34265631437301636,0.20604988932609558,0.4261782765388489,0.010843470692634583,0.5708009824156761,0.8585412055253983,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.9331365078687668,0.4384240508079529,0.21769116818904877,0.46462100744247437,0.013590224087238312,0.8700751587748528,0.9070465341210365,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.9031721539795399,0.44615936279296875,0.18791820108890533,0.521428644657135,0.009995403699576855,0.8942480087280273,0.7829925045371056,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.8932308070361614,0.41031843423843384,0.20684581995010376,0.4193262457847595,0.024767670780420303,0.7822451069951057,0.8618575831254324,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.7570139667723568,0.2662753164768219,0.23317767679691315,0.5077286958694458,0.005107289180159569,0.33211036399006855,0.9715736533204715,0.863635046316779,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.8732785806059837,0.35115379095077515,0.23525752127170563,0.41009122133255005,0.011141548864543438,0.5973555967211723,0.9802396719654402,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0009.png,9,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0009.png,0.8602951680751223,0.4846940040588379,0.1919434517621994,0.18940842151641846,0.009361225180327892,0.9853312373161316,0.7997643823424976,1.0,0.49844321451689066
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.8469079197629502,0.5111610889434814,0.15641345083713531,0.3308650553226471,0.012622418813407421,0.9026215970516205,0.6517227118213972,1.0,0.870697514006966
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.7822690353141096,0.33351975679397583,0.18741919100284576,0.6403491497039795,0.007028179243206978,0.5422492399811745,0.7809132958451908,0.9412810982648001,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.6131865660610952,0.6606355309486389,0.15420351922512054,0.10077087581157684,0.018221400678157806,0.4355139657855034,0.6425146634380023,1.0,0.26518651529362325
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.8051183959156577,0.46463191509246826,0.22866183519363403,0.009745027869939804,0.006425432860851288,0.9519747346639633,0.9527576466401418,0.9194078399872734,0.025644810184052114
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.7481512544941831,0.5874038934707642,0.26845401525497437,0.010588700883090496,0.008188189938664436,0.664362832903862,1.0,0.9786506170977449,0.027865002323922358
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.8529746122658253,0.4173896312713623,0.1693374663591385,0.47458702325820923,0.010883152484893799,0.8043425977230072,0.7055727764964104,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.8588580984426172,0.479427695274353,0.35124045610427856,0.02379973977804184,0.07146435976028442,0.9982115477323532,1.0,1.0,0.06263089415274169
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.7668434718721792,0.5449010133743286,0.14114394783973694,0.2565208673477173,0.00970851257443428,0.7971843332052231,0.5880997826655706,1.0,0.6750549140729403
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.7776098706220326,0.5767411589622498,0.15460778772830963,0.31678059697151184,0.020487023517489433,0.6976838782429695,0.6441991155346235,1.0,0.8336331499250311
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.9174275484328207,0.4640711843967438,0.21460025012493134,0.2890799343585968,0.01801297813653946,0.9502224512398243,0.8941677088538806,1.0,0.7607366693647284
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.7589390004741559,0.5512765049934387,0.17035728693008423,0.16556505858898163,0.008570555597543716,0.777260921895504,0.709822028875351,0.9898379474100473,0.4356975226025832
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.8784318123352023,0.4552675485610962,0.2071256935596466,0.3053433895111084,0.005664038006216288,0.9227110892534256,0.8630237231651943,0.8887243331051369,0.8035352355555484
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.8947002198547125,0.43727806210517883,0.18780162930488586,0.5342007875442505,0.025740642100572586,0.8664939440786839,0.7825067887703578,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.9049478150904179,0.4964229464530945,0.17627546191215515,0.4802337884902954,0.017999855801463127,0.9486782923340797,0.7344810913006465,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.9813835850671718,0.4987140893936157,0.2715086340904236,0.37728437781333923,0.025151735171675682,0.9415184706449509,1.0,1.0,0.9928536258245769
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0010.png,10,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0010.png,0.716300159169756,0.23789291083812714,0.21230025589466095,0.4700593948364258,0.006222758442163467,0.2434153463691474,0.8845843995610874,0.9116009415627422,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.8617069907486439,0.39766180515289307,0.1911192387342453,0.3902971148490906,0.022736594080924988,0.7426931411027908,0.7963301613926888,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.9391638579141153,0.4860605299472809,0.2516518831253052,0.2402755320072174,0.09339642524719238,0.9810608439147472,1.0,1.0,0.6323040315979406
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.8260683723746457,0.3666582703590393,0.21132534742355347,0.47827720642089844,0.005301555152982473,0.6458070948719978,0.8805222809314728,0.8726782385344182,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.7919605132192373,0.390259712934494,0.14087362587451935,0.4148794710636139,0.010153334587812424,0.7195616029202938,0.5869734411438307,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.6491830306928028,0.2559933364391327,0.14960849285125732,0.364663302898407,0.0062568290159106255,0.29997917637228977,0.6233687202135723,0.9129304843970083,0.9596402707852815
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.6657208744436504,0.27518025040626526,0.12619151175022125,0.5309655666351318,0.009614264592528343,0.35993828251957904,0.525797965625922,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.7608880448498223,0.37905919551849365,0.17089742422103882,0.2328089475631714,0.015220238827168941,0.6845599859952927,0.7120726009209951,1.0,0.6126551251662404
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.7145841657723252,0.2859361171722412,0.17513622343540192,0.3232502341270447,0.013347038067877293,0.3935503661632539,0.7297342643141747,1.0,0.8506585108606439
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.8596613200479433,0.3479235768318176,0.26016852259635925,0.3381568491458893,0.013945198617875576,0.5872611775994301,1.0,1.0,0.8898864451207612
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.6983062481439671,0.2997108995914459,0.15603455901145935,0.36176618933677673,0.006386489141732454,0.4365965612232686,0.6501439958810806,0.9179265514136339,0.9520162877283598
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.8818235804557416,0.47700607776641846,0.15765540301799774,0.4270445704460144,0.007290821056813002,0.9906439930200577,0.6568975125749906,0.9502445151089086,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.774190147260302,0.5137311220169067,0.20070448517799377,0.012495584785938263,0.013682609423995018,0.8945902436971664,0.8362686882416408,1.0,0.03288311785773227
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.48064235309765546,0.14640486240386963,0.1200752854347229,0.8573397397994995,0.002828537719324231,0.0,0.5003136893113455,0.7221929852170071,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.5637109845914624,0.18502452969551086,0.15317346155643463,0.652617335319519,0.0038432846777141094,0.07820165529847156,0.6382227564851444,0.7951346442255104,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.717459922656417,0.22427037358283997,0.20576515793800354,0.6185629367828369,0.009624357335269451,0.200844917446375,0.8573548247416815,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0011.png,11,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0011.png,0.8127584176343619,0.34211820363998413,0.20422905683517456,0.370963454246521,0.0076253050938248634,0.5691193863749504,0.850954403479894,0.9612133528487059,0.9762196164382131
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.6864065705368491,0.2741782069206238,0.14817701280117035,0.5917714834213257,0.008119042962789536,0.3568068966269494,0.6174042200048765,0.9765729421892052,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.9713950715959072,0.47971469163894653,0.21733003854751587,0.40844476222991943,0.010058732703328133,0.9991084113717079,0.9055418272813162,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.8162724675512627,0.4501749575138092,0.23194971680641174,0.010883957147598267,0.022110294550657272,0.9067967422306538,0.966457153360049,1.0,0.028641992493679647
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.8952369228397545,0.3791632056236267,0.247663214802742,0.35408759117126465,0.018146997317671776,0.6848850175738335,1.0,1.0,0.9318094504506964
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.8108695181944456,0.43630632758140564,0.23908624053001404,0.007535489741712809,0.02226063422858715,0.8634572736918926,0.9961926688750585,1.0,0.019830236162402128
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.9931557374587933,0.4784943461418152,0.26595890522003174,0.5266944169998169,0.008175451308488846,0.9952948316931725,1.0,0.9782691518033664,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.9205608076170871,0.5526833534240723,0.2633109390735626,0.351377010345459,0.016436833888292313,0.7728645205497742,1.0,1.0,0.9246763430143657
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.7959507714801258,0.3819081783294678,0.15686550736427307,0.6137540936470032,0.007817976176738739,0.6934630572795868,0.6536062806844711,0.9673198803636337,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.79812374677073,0.30458009243011475,0.25100991129875183,0.42348554730415344,0.004833739250898361,0.4518127888441087,1.0,0.8503196404699894,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.9081090591847897,0.5377892255783081,0.2098291665315628,0.6009770035743713,0.01834665611386299,0.8194086700677872,0.8742881938815117,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.9247215962723682,0.500356912612915,0.22976577281951904,0.2700507640838623,0.012169701978564262,0.9363846480846405,0.9573573867479961,1.0,0.7106599054838482
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.9528578683341804,0.4682837128639221,0.22772490978240967,0.3272705674171448,0.02386489138007164,0.9633866026997566,0.9488537907600403,1.0,0.8612383353082758
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.862411005422473,0.4177171289920807,0.17664095759391785,0.5214425921440125,0.015117242932319641,0.8053660281002522,0.7360039899746578,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.9598501920700073,0.45587438344955444,0.22597436606884003,0.4988783597946167,0.020012032240629196,0.9246074482798576,0.9415598586201668,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.8650946329102704,0.37269696593284607,0.2405259609222412,0.29308444261550903,0.028306839987635612,0.664678018540144,1.0,1.0,0.7712748489881817
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.7886823602020742,0.3391212821006775,0.17660492658615112,0.3878621459007263,0.014586799778044224,0.5597540065646172,0.7358538607756298,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.7800788427911904,0.31115302443504333,0.23668862879276276,0.4070294499397278,0.003460435662418604,0.47235320135951053,0.9862026199698448,0.7700483855695351,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.9391630170745662,0.5017827749252319,0.23649747669696808,0.34262484312057495,0.00630668830126524,0.9319288283586502,0.9854061529040337,0.9148634963821362,0.9016443240015131
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.7712428817574523,0.5294139981269836,0.21210214495658875,0.006183420307934284,0.025031905621290207,0.8455812558531761,0.8837589373191198,1.0,0.01627215870509022
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.8566811236111742,0.6218043565750122,0.2461337447166443,0.3537108600139618,0.01103892270475626,0.5568613857030869,1.0,1.0,0.9308180526683205
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.8376682562263388,0.3607521057128906,0.22964757680892944,0.28475600481033325,0.014505776576697826,0.6273503303527832,0.9568649033705394,1.0,0.7493579073956138
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.9891186870634555,0.4683932662010193,0.25315365195274353,0.42203789949417114,0.012284314259886742,0.9637289568781853,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.5655229001103006,0.5717395544052124,0.14466263353824615,0.024601956829428673,0.002023695269599557,0.7133138924837112,0.6027609730760257,0.6439565667756836,0.06474199165639125
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.8070361636579038,0.2997651696205139,0.23822307586669922,0.3248429298400879,0.024911997839808464,0.4367661550641061,0.9925961494445801,1.0,0.8548498153686523
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.8654121831059456,0.4027549624443054,0.1902635246515274,0.5719152688980103,0.012333137914538383,0.7586092576384544,0.7927646860480309,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.7781528002965323,0.3499597907066345,0.20828506350517273,0.29097089171409607,0.005918635055422783,0.5936243459582329,0.867854431271553,0.8994089447512873,0.7657128729318318
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.9213138908147812,0.5233176946640015,0.20953938364982605,0.47362884879112244,0.015652017667889595,0.8646322041749954,0.8730807652076086,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.4911369412626021,0.1367371678352356,0.11293863505125046,0.7546923160552979,0.003919710870832205,0.0,0.4705776460468769,0.799854589794156,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.5426214516948177,0.1607101410627365,0.16714097559452057,0.3070922791957855,0.0047724274918437,0.0022191908210517086,0.6964207316438358,0.8472353537227971,0.8081375768310145
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.8714720599573349,0.4545878469944,0.16664092242717743,0.43773460388183594,0.007223552092909813,0.9205870218575001,0.694337176779906,0.9479792014644525,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.5526559902011956,0.8025230169296265,0.2603263556957245,0.00672850850969553,0.06973238289356232,0.0,1.0,1.0,0.017706601341304026
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.8802813161164522,0.4259483516216278,0.18476378917694092,0.5297917127609253,0.021040260791778564,0.8310885988175869,0.7698491215705872,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.7407415405785639,0.5424097776412964,0.15462270379066467,0.39153799414634705,0.0018547483487054706,0.8049694448709488,0.6442612657944362,0.6238893095157935,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.7587375699248361,0.4254619777202606,0.20579728484153748,0.006638244725763798,0.012493796646595001,0.8295686803758144,0.8574886868397396,1.0,0.017469065067799466
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.7731683049350978,0.29915544390678406,0.1941680610179901,0.5130757689476013,0.013549610041081905,0.4348607622087003,0.8090335875749588,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.8925165824592114,0.36535102128982544,0.2630952000617981,0.44784021377563477,0.01910003088414669,0.6417219415307045,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.9000832740805651,0.5424793362617493,0.28022435307502747,0.27526605129241943,0.03489815443754196,0.8047520741820335,1.0,1.0,0.7243843455063669
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.8814360807208639,0.5581095814704895,0.2190711796283722,0.33142292499542236,0.021359482780098915,0.7559075579047203,0.9127965817848842,1.0,0.8721655920932168
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.7512215759115,0.5901047587394714,0.32564619183540344,0.011260127648711205,0.014131704345345497,0.6559226289391518,1.0,1.0,0.029631914865029484
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.9090647824108601,0.576175332069397,0.23938332498073578,0.4051344394683838,0.023894552141427994,0.6994520872831345,0.9974305207530658,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.7038594809605887,0.38715076446533203,0.1900695115327835,0.008407499641180038,0.014668822288513184,0.7098461389541626,0.7919562980532646,1.0,0.022124999055736942
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.8055793151259423,0.2726179361343384,0.2450747936964035,0.6575278043746948,0.015183239243924618,0.35193105041980755,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.6873617286133359,0.2956738770008087,0.18449264764785767,0.2508673071861267,0.006496814079582691,0.42398086562752735,0.768719365199407,0.9221003629566118,0.6601771241740176
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.800081877018276,0.3557407259941101,0.20855067670345306,0.268246054649353,0.01240632589906454,0.6116897687315941,0.8689611529310545,1.0,0.7059106701298764
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.7996633984148503,0.28442543745040894,0.2264116406440735,0.42042145133018494,0.01109558530151844,0.38882949203252803,0.9433818360169729,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.8768068260268161,0.5338320732116699,0.26701149344444275,0.1957617998123169,0.024476852267980576,0.8317747712135315,1.0,1.0,0.5151626310850445
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.9009054427393594,0.430291086435318,0.26297423243522644,0.4992072582244873,0.003762240521609783,0.8446596451103687,1.0,0.7900301968249951,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0014.png,14,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0014.png,0.8039119759084362,0.38075992465019226,0.1704365760087967,0.3392230272293091,0.01465622428804636,0.6898747645318508,0.7101524000366529,1.0,0.8926921769192344
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.7432192665724952,0.24435082077980042,0.22781600058078766,0.41463130712509155,0.006374833174049854,0.2635963149368764,0.949233335753282,0.9174814854617903,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.8307682323612664,0.45102840662002563,0.1656930297613144,0.255392462015152,0.016262967139482498,0.9094637706875801,0.6903876240054767,1.0,0.672085426355663
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.7878784725540563,0.5474376678466797,0.16663503646850586,0.23511230945587158,0.013947145082056522,0.789257287979126,0.6943126519521078,1.0,0.618716603831241
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.9247153528034686,0.40815919637680054,0.24393706023693085,0.3599008023738861,0.01962270960211754,0.7754974886775017,1.0,1.0,0.9471073746681213
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.5864899270236492,0.6555646061897278,0.1594225913286209,0.0045688822865486145,0.018462948501110077,0.4513606056571007,0.6642607972025871,1.0,0.012023374438285828
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.7942999303340912,0.3399207592010498,0.1804993748664856,0.5016100406646729,0.011573918163776398,0.5622523725032806,0.7520807286103567,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.8627199716866016,0.40566039085388184,0.18593068420886993,0.430484801530838,0.02167251892387867,0.7676887214183807,0.7747111842036247,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.8996455028653145,0.37295520305633545,0.24502159655094147,0.5237715244293213,0.015282982960343361,0.6654850095510483,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.975370334677006,0.4722314476966858,0.3008243143558502,0.3360551595687866,0.03294828534126282,0.9757232740521431,1.0,1.0,0.8843556830757543
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.9019431434571743,0.4112498164176941,0.21311715245246887,0.39880985021591187,0.03857170417904854,0.785155676305294,0.8879881352186203,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.9076573254834663,0.4421848952770233,0.3213356137275696,0.23587609827518463,0.011420232243835926,0.8818277977406979,1.0,1.0,0.6207265744083806
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.7160310596227647,0.3161490559577942,0.13571305572986603,0.4689984619617462,0.009724211879074574,0.48796579986810695,0.5654710655411085,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.8484421701219521,0.4870491921901703,0.2939058542251587,0.012795329093933105,0.0162888765335083,0.9779712744057178,1.0,1.0,0.03367191866824502
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.6716685353196115,0.41652441024780273,0.09809814393520355,0.3237360119819641,0.0028388802893459797,0.8016387820243835,0.4087422663966815,0.7230547589911194,0.8519368736367476
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.6985199927401385,0.622435450553894,0.21625640988349915,0.029722878709435463,0.017423739656805992,0.5548892170190811,0.9010683745145798,1.0,0.07821810186693542
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0015.png,15,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0015.png,0.8383523071727896,0.4447466731071472,0.15891675651073456,0.3717041611671448,0.006034497171640396,0.889833353459835,0.6621531521280607,0.9041241148796655,0.9781688451766968
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.7467232157133128,0.31056469678878784,0.20241448283195496,0.2597951292991638,0.018338143825531006,0.4705146774649621,0.8433936784664791,1.0,0.6836713928925363
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.8761748644866441,0.4614783525466919,0.186544269323349,0.27957504987716675,0.014470174908638,0.9421198517084122,0.7772677888472875,1.0,0.7357238154662282
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.6506829364525222,0.5831090211868286,0.1323879361152649,0.18907222151756287,0.004423442296683788,0.6777843087911606,0.5516164004802704,0.8289158080776936,0.497558477677797
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.8203354813158512,0.404049813747406,0.15323102474212646,0.44978874921798706,0.017404763028025627,0.7626556679606438,0.6384626030921936,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.8569143503904343,0.5433372259140015,0.1730343997478485,0.4627038836479187,0.019491128623485565,0.8020711690187454,0.7209766656160355,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.8411121944847859,0.5319052934646606,0.1652536392211914,0.3374561071395874,0.022706329822540283,0.8377959579229355,0.6885568300882976,1.0,0.8880423872094405
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.884892939325226,0.44047823548316956,0.17845477163791656,0.37715286016464233,0.02034679800271988,0.8764944858849049,0.7435615484913191,1.0,0.9925075267490587
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.7285709449969338,0.322512686252594,0.1645842343568802,0.3918088674545288,0.005507936701178551,0.5078521445393562,0.6857676431536674,0.8819400347561066,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.7355873623919291,0.5233707427978516,0.18375299870967865,0.17006665468215942,0.0027751706074923277,0.8644664287567139,0.765637494623661,0.717698444644699,0.44754382811094584
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.9084798227015294,0.5499968528747559,0.2278805673122406,0.3527696132659912,0.01753823831677437,0.7812598347663879,0.9495023638010025,1.0,0.9283410875420821
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.7982093503130805,0.34486597776412964,0.18317990005016327,0.4712831676006317,0.008358328603208065,0.5777061805129051,0.763249583542347,0.9836904843860194,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.7055575221973029,0.34307751059532166,0.19303835928440094,0.10798183083534241,0.01715138927102089,0.5721172206103802,0.8043264970183372,1.0,0.28416271272458526
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.7802756648118558,0.3692881166934967,0.1473008245229721,0.37985312938690186,0.011139638721942902,0.6540253646671772,0.6137534355123838,1.0,0.9996134983865839
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.8073003645986319,0.3883167803287506,0.15460270643234253,0.43305689096450806,0.012513567693531513,0.7134899385273457,0.6441779434680939,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.7134816550796753,0.35065758228302,0.223502978682518,0.013582335785031319,0.025194358080625534,0.5958049446344376,0.9312624111771584,1.0,0.035742988907977155
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0016.png,16,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0016.png,0.6053562955771398,0.272235631942749,0.21901960670948029,0.013670315966010094,0.005551657639443874,0.3507363498210908,0.9125816946228346,0.8838588195558328,0.03597451570002656
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.8000689573536971,0.5396853685379028,0.3299698531627655,0.015260775573551655,0.05055173859000206,0.8134832233190536,1.0,1.0,0.04015993571987277
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.6530644088957033,0.27247026562690735,0.1181761622428894,0.45654022693634033,0.008918961510062218,0.3514695800840856,0.4924006760120392,0.9996133282674634,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.7901423561428936,0.38881272077560425,0.18913355469703674,0.5581117868423462,0.0032739692833274603,0.7150397524237633,0.7880564779043198,0.7568539481778749,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.9169885468326117,0.3919905424118042,0.3154178261756897,0.3787267804145813,0.025505347177386284,0.7249704450368881,1.0,1.0,0.9966494221436349
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.8500145824528054,0.4204067289829254,0.164823979139328,0.37962836027145386,0.010730253532528877,0.8137710280716419,0.6867665797472,1.0,0.9990220007143522
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.8821932227595857,0.3858415484428406,0.28026506304740906,0.30518248677253723,0.020398907363414764,0.7057548388838768,1.0,1.0,0.8031118072961506
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.765615213662386,0.2896384596824646,0.1952633261680603,0.4197927713394165,0.01130150817334652,0.405120186507702,0.813597192366918,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.8775255475572729,0.40311914682388306,0.20109966397285461,0.424687922000885,0.008678479120135307,0.7597473338246346,0.837915266553561,0.992907069775257,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.1060203865223869,0.08488570153713226,0.06521442532539368,0.43964800238609314,0.00011834290489787236,0.0,0.2717267721891403,0.13413173859690072,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.7286023513266915,0.6903868913650513,0.21062985062599182,0.28513363003730774,0.029533270746469498,0.3425409644842148,0.8776243776082993,1.0,0.7503516579929151
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.8902436938725019,0.4110713601112366,0.21024318039417267,0.35988613963127136,0.03376898914575577,0.7845980003476143,0.8760132516423862,1.0,0.9470687885033456
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.7448399855155,0.35615774989128113,0.17505337297916412,0.276083767414093,0.006782068405300379,0.6129929684102535,0.7293890540798506,0.9325797770516233,0.7265362300370869
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.6767499036770002,0.2654770612716675,0.17257435619831085,0.4880240261554718,0.00479924026876688,0.329615816473961,0.7190598174929619,0.8485888539476931,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.9328115202486514,0.40833228826522827,0.24062082171440125,0.5199904441833496,0.01580057665705681,0.7760384008288383,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.9405414138773553,0.4455060660839081,0.24673490226268768,0.31129467487335205,0.014735187403857708,0.8922064565122128,1.0,1.0,0.8191965128246107
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0017.png,17,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0017.png,0.7440665274884055,0.4705606698989868,0.1124984622001648,0.25925108790397644,0.00462822150439024,0.9705020934343338,0.46874359250068665,0.8398274638253193,0.6822397050104643
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.9087680444121361,0.4924779534339905,0.17637290060520172,0.40666013956069946,0.01816350594162941,0.9610063955187798,0.7348870858550072,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.8488528393650132,0.4742929935455322,0.27767375111579895,0.010648000054061413,0.012928320094943047,0.9821656048297882,1.0,1.0,0.028021052773845822
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.846041242287397,0.42204126715660095,0.1783185452222824,0.3279097080230713,0.008652274496853352,0.818878959864378,0.7429939384261768,0.9921653206381781,0.8629202842712402
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.9666911387914106,0.47083932161331177,0.23597531020641327,0.3301190137863159,0.030412841588258743,0.9713728800415993,0.9832304591933887,1.0,0.8687342468060945
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.8631674908101559,0.39369702339172363,0.19526122510433197,0.6157183647155762,0.01187051273882389,0.7303031980991364,0.8135884379347166,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.7551792438289052,0.45202067494392395,0.1635371297597885,0.06837073713541031,0.015932418406009674,0.9125646091997623,0.6814047073324522,1.0,0.17992299246160606
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.8884607032725685,0.452422559261322,0.20240382850170135,0.28198474645614624,0.016156919300556183,0.9138204976916313,0.8433492854237556,1.0,0.7420651222530165
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.6955662948021785,0.45507293939590454,0.07398809492588043,0.45716890692710876,0.0026384503580629826,0.9221029356122017,0.30828372885783517,0.7058011818446697,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.8950493446698313,0.4675564169883728,0.24620762467384338,0.14367851614952087,0.010817540809512138,0.961113803088665,1.0,1.0,0.37810135828821284
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.9684420607984067,0.513661801815033,0.2601226568222046,0.4532388746738434,0.030447103083133698,0.894806869328022,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.6384765812863292,0.4098794758319855,0.10772261768579483,0.6401137113571167,0.0009622080833651125,0.7808733619749546,0.4488442403574785,0.4782452023463975,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.8459881986750849,0.47413957118988037,0.1435789167881012,0.4443722367286682,0.005647978745400906,0.9816861599683762,0.5982454866170883,0.8880348187977822,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.9159632013816583,0.5285569429397583,0.30137500166893005,0.2824295163154602,0.018762830644845963,0.8482595533132553,1.0,1.0,0.743235569251211
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.8871443532407284,0.3699425458908081,0.23225857317447662,0.45730137825012207,0.010098276659846306,0.6560704559087753,0.9677440548936527,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.6971903395035225,0.31409573554992676,0.14680181443691254,0.3100327253341675,0.008484655991196632,0.48154917359352123,0.6116742268204689,0.9873679217265111,0.8158755929846513
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0018.png,18,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0018.png,0.7604554773749489,0.41306376457214355,0.2126333862543106,0.018788378685712814,0.009379632771015167,0.7908242642879486,0.8859724427262943,1.0,0.04944310180450741
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.8521001825820171,0.41819798946380615,0.20216156542301178,0.3962128162384033,0.004431429319083691,0.8068687170743942,0.8423398559292158,0.8293504427237365,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.7765876641791117,0.4545985758304596,0.19768491387367249,0.008348237723112106,0.0128417257219553,0.9206205494701862,0.8236871411403021,1.0,0.021969046639768702
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.8445852026343346,0.3910732865333557,0.18236319720745087,0.4763438105583191,0.01713361032307148,0.7221040204167366,0.7598466550310453,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.6105531284659445,0.23113161325454712,0.1169707402586937,0.529464840888977,0.008597764186561108,0.22228629142045986,0.48737808441122377,0.9906152628657575,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.7372971773147584,0.265078067779541,0.19102919101715088,0.38728511333465576,0.015489459037780762,0.3283689618110658,0.795954962571462,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.8101943848948729,0.5640788078308105,0.21445924043655396,0.17972534894943237,0.026313647627830505,0.737253725528717,0.8935801684856415,1.0,0.4729614446037694
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.8910518909584676,0.47009360790252686,0.168345108628273,0.5823169946670532,0.007576141972094774,0.9690425246953964,0.7014379526178043,0.9596309910580294,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.5742638274526449,0.23665672540664673,0.12246014177799225,0.41534799337387085,0.0038780360482633114,0.23955226689577114,0.5102505907416344,0.797291880645693,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.8460940940501658,0.469973623752594,0.23579266667366028,0.027240904048085213,0.025629345327615738,0.9686675742268562,0.9824694444735845,1.0,0.07168658960022424
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.6573484642235072,0.35573288798332214,0.17677509784698486,0.007296023890376091,0.011754566803574562,0.6116652749478817,0.7365629076957703,1.0,0.019200062869410766
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.8445696403125399,0.3968922197818756,0.21284671127796173,0.2696094810962677,0.02717634290456772,0.7402881868183613,0.8868612969915073,1.0,0.7094986344638624
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.7978115466570384,0.5200223922729492,0.22470614314079285,0.011272979900240898,0.01932649128139019,0.8749300241470337,0.9362755964199703,1.0,0.02966573657958131
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.8986510265618562,0.40813741087913513,0.22649267315864563,0.3366961181163788,0.01212324295192957,0.7754294089972973,0.9437194714943569,1.0,0.8860424160957336
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.810674570981979,0.48731565475463867,0.1195012554526329,0.4459676146507263,0.005300406366586685,0.9771385788917542,0.4979218977193038,0.8726257119946464,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.6552491658269183,0.6907745599746704,0.2888643145561218,0.007220800034701824,0.016408154740929604,0.34132950007915497,1.0,1.0,0.019002105354478483
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0019.png,19,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0019.png,0.7811032718733738,0.3114791512489319,0.19196613132953644,0.3778058886528015,0.013307714834809303,0.47337234765291225,0.7998588805397352,1.0,0.9942260227705303
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,1,0,0,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.8456902621926641,0.47216540575027466,0.24522073566913605,0.007689158897846937,0.026696914806962013,0.9755168929696083,1.0,1.0,0.020234628678544572
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,2,0,1,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.8580354317083937,0.4262220859527588,0.2029639184474945,0.3047005534172058,0.006931050680577755,0.8319440186023712,0.8456829935312271,0.9378831752987214,0.8018435616242258
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,3,0,2,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.8584190677459302,0.38848093152046204,0.21223033964633942,0.3266233503818512,0.026523113250732422,0.7140029110014439,0.8842930818597476,1.0,0.859535132583819
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,4,0,3,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.7268820377360833,0.35411930084228516,0.23172320425510406,0.013277675956487656,0.02197645604610443,0.6066228151321411,0.9655133510629337,1.0,0.03494125251707278
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,5,1,0,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.8663382722162887,0.45925769209861755,0.18883401155471802,0.25267890095710754,0.01563076861202717,0.9351802878081799,0.7868083814779918,1.0,0.6649444762029146
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.9824905775487424,0.49867671728134155,0.2486007660627365,0.3911525011062622,0.02533857524394989,0.9416352584958076,1.0,1.0,1.0
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,7,1,2,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.6942733257616821,0.6876616477966309,0.1817881017923355,0.2830265164375305,0.02869051694869995,0.35105735063552856,0.7574504241347313,1.0,0.7448066222040277
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,8,1,3,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.6995152900724683,0.3548176884651184,0.15287499129772186,0.2994121015071869,0.004450107458978891,0.608805276453495,0.6369791304071745,0.8303639223088802,0.7879265829136497
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,9,2,0,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.7313211287684622,0.5973894596099854,0.23988348245620728,0.007782702334225178,0.007397308945655823,0.6331579387187958,0.999514510234197,0.9537890989604284,0.020480795616382046
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,10,2,1,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.7233346639323587,0.4374307096004486,0.16841869056224823,0.006890693213790655,0.013099392876029015,0.8669709675014019,0.7017445440093677,1.0,0.018133403194185934
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,11,2,2,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.8201521050857457,0.38383474946022034,0.19059307873249054,0.3378530442714691,0.007428276818245649,0.6994835920631886,0.7941378280520439,0.9548105410392259,0.8890869586091292
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,12,2,3,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.6955489445673791,0.6466243267059326,0.14668011665344238,0.29996973276138306,0.0123206852003932,0.47929897904396057,0.6111671527226766,1.0,0.789394033582587
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,13,3,0,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.8775790249438662,0.5596475601196289,0.22977720201015472,0.29140201210975647,0.013579258695244789,0.7511013746261597,0.9574050083756447,1.0,0.7668474002888328
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,14,3,1,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.5929520671727672,0.2791813015937805,0.15195143222808838,0.24747346341609955,0.003523734398186207,0.37244156748056423,0.6331309676170349,0.7743736527590557,0.6512459563581567
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,15,3,2,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.792331221856569,0.5539194345474243,0.1550215184688568,0.2985629439353943,0.016959497705101967,0.769001767039299,0.6459229936202368,1.0,0.7856919577247218
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,16,3,3,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.9279440619051456,0.43676942586898804,0.2630649507045746,0.3001309037208557,0.013238211162388325,0.8649044558405876,1.0,1.0,0.7898181676864624
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.7628913777746106,0.39864563941955566,0.18986448645591736,0.27265122532844543,0.0035600236151367426,0.7457676231861115,0.7911020268996557,0.7768199962663973,0.7175032245485407
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.7611940096475577,0.3698378801345825,0.33047229051589966,0.036659859120845795,0.009453600272536278,0.6557433754205704,1.0,1.0,0.09647331347590998
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.6789876241763587,0.4127175807952881,0.14407067000865936,0.27591875195503235,0.0017627556808292866,0.7897424399852753,0.6002944583694141,0.6122450313823883,0.7261019788290325
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.3668024896701126,0.18816962838172913,0.124603770673275,0.45887213945388794,0.00012343046546448022,0.08803008869290363,0.5191823778053125,0.13855499888259107,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.6909713083653636,0.3991561233997345,0.15284113585948944,0.4302128255367279,0.0010789327789098024,0.7473628856241703,0.6368380660812061,0.5028440914150027,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.7453696670875408,0.4370042681694031,0.22190676629543304,0.03495150804519653,0.003577538998797536,0.8656383380293846,0.9246115262309711,0.777992239587426,0.0919776527505172
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.3164164923943671,0.7524522542953491,0.12219692021608353,0.0066132927313447,0.0009079689625650644,0.148586705327034,0.5091538342336814,0.46593528094985504,0.017403401924591316
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.6611469538155842,0.3651946783065796,0.1910868138074875,0.4680827260017395,0.0004319914150983095,0.6412333697080612,0.7961950575311979,0.31967370257522565,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.6577045627978575,0.4569193720817566,0.11670377105474472,0.39999139308929443,0.00046692381147295237,0.9278730377554893,0.48626571272810304,0.33385175061111927,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.8050765151565775,0.5087078809738159,0.16202805936336517,0.5184018015861511,0.002776605077087879,0.9102878719568253,0.6751169140140216,0.7178203174612937,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.6214485311374858,0.4847099781036377,0.11687489598989487,0.2653971314430237,0.0003867613268084824,0.9852813184261322,0.48697873329122865,0.30003396021065204,0.6984135037974307
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.5978538312501849,0.36028122901916504,0.16520895063877106,0.19928491115570068,0.0010631472105160356,0.6258788406848907,0.6883706276615461,0.4996555769496986,0.5244339767255282
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.7444592952004337,0.5706098079681396,0.30288010835647583,0.07901345938444138,0.003807058557868004,0.7168443500995636,1.0,0.7928658669173511,0.20793015627484573
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.7929060568101866,0.3936316668987274,0.22226789593696594,0.4606698453426361,0.0015577770536765456,0.7300989590585232,0.9261162330706915,0.5841659966856888,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.7538208311092871,0.35682809352874756,0.20990991592407227,0.5420700311660767,0.0018852085340768099,0.6150877922773361,0.8746246496836345,0.6276283940839837,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0001.png,1,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0001.png,0.4815692171557062,0.29302898049354553,0.09725406020879745,0.5837064981460571,0.00048568734200671315,0.4157155640423299,0.4052252508699894,0.3411478907280419,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.7842901587094131,0.35678768157958984,0.19774140417575836,0.25998321175575256,0.010966056026518345,0.6149615049362183,0.8239225173989932,1.0,0.6841663467256647
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.4907440327981547,0.6328915357589722,0.16684943437576294,0.037269722670316696,0.0008146517211571336,0.522213950753212,0.695205976565679,0.44322528787787097,0.09807821755346499
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.37545405831083667,0.18723610043525696,0.11006129533052444,0.5960727334022522,0.00028524798108264804,0.0851128138601781,0.45858873054385185,0.24937437995851092,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.6325249371206905,0.42501509189605713,0.09970459342002869,0.628302812576294,0.0007934708846732974,0.8281721621751785,0.4154358059167862,0.4377701867724045,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.7440589077324157,0.49713629484176636,0.19914981722831726,0.13435819745063782,0.001926447614096105,0.9464490786194801,0.8297909051179886,0.6326031281542193,0.35357420381746796
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.41519069063560454,0.2624385952949524,0.087938092648983,0.3576759696006775,0.0003284037229605019,0.32012061029672634,0.3664087193707625,0.27217603599299345,0.9412525515807302
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.8210262310424181,0.3983412981033325,0.20485129952430725,0.4503845274448395,0.003403151873499155,0.7448165565729141,0.8535470813512802,0.7660685586606393,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.8010968356912126,0.4575977027416229,0.21487721800804138,0.382781445980072,0.0007064203964546323,0.9299928210675716,0.8953217417001724,0.4140098674435574,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.6748834936183764,0.54515540599823,0.15268632769584656,0.09364062547683716,0.0044912416487932205,0.7963893562555313,0.6361930320660274,0.8325814893136819,0.24642269862325566
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.5992740329296645,0.32350432872772217,0.1739739179611206,0.40015169978141785,0.00041875772876664996,0.5109510272741318,0.7248913248380026,0.3140853091840972,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.7786330575070187,0.5310583710670471,0.22053061425685883,0.5818937420845032,0.0006699684308841825,0.8404425904154778,0.9188775594035785,0.4033480502452076,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.6203773310599053,0.4487788677215576,0.1615300327539444,0.15300306677818298,0.0005074574728496373,0.9024339616298676,0.673041803141435,0.34935461686429553,0.402639649416271
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.8597139660502846,0.4811953902244568,0.2116411030292511,0.4360826909542084,0.0015644605737179518,0.9962644055485725,0.8818379292885463,0.5851330623965957,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.7826422527086921,0.5284242033958435,0.16135649383068085,0.4578281044960022,0.002633698284626007,0.848674364387989,0.6723187242945036,0.7053773044157775,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.528052307992831,0.29147517681121826,0.16669034957885742,0.3019697070121765,0.000406812148867175,0.4108599275350572,0.6945431232452393,0.30893129680521614,0.794657123716254
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0002.png,2,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0002.png,0.8911951477944692,0.48296621441841125,0.22318270802497864,0.4076688289642334,0.0021687771659344435,0.9907305799424648,0.9299279501040777,0.6599903551220259,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.6693602051072369,0.5813428163528442,0.18909676373004913,0.1714693009853363,0.0020001232624053955,0.6833036988973618,0.787903182208538,0.6412515615460737,0.45123500259299026
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.7268840588970904,0.587814211845398,0.24263732135295868,0.2517995834350586,0.0011371364817023277,0.6630805879831314,1.0,0.5142612403743011,0.6626304827238384
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.8637723605071763,0.48292356729507446,0.2961854338645935,0.07765182852745056,0.007090715691447258,0.9908638522028923,1.0,0.9434446690787333,0.20434691717750147
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.43503496895626226,0.25032204389572144,0.1109653189778328,0.6130366325378418,0.000280270614894107,0.2822563871741296,0.46235549574097,0.24660561632692937,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.7546294376160023,0.49435877799987793,0.19711707532405853,0.3324585258960724,0.0005419884109869599,0.9551288187503815,0.8213211471835773,0.36184327677051326,0.8748908576212431
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.5357790140129729,0.26767510175704956,0.15501296520233154,0.37654876708984375,0.0005646682111546397,0.33648469299078,0.6458873550097148,0.3697189135725972,0.9909178081311677
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.8380298500220915,0.5373179316520691,0.23175550997257233,0.25657814741134644,0.003974109888076782,0.8208814635872841,0.9656479582190514,0.8031607032712692,0.6752056510824906
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.6574755640956861,0.5453730821609497,0.1507633477449417,0.10026170313358307,0.00335856806486845,0.7957091182470322,0.6281806156039238,0.7629266234454134,0.2638465871936396
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.6226501882459492,0.48558998107910156,0.15544915199279785,0.030146734789013863,0.0010011194972321391,0.9825313091278076,0.6477047999699911,0.48671731450483724,0.07933351260266806
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.712641067811896,0.6001120209693909,0.29811814427375793,0.021973062306642532,0.005163596943020821,0.6246499344706535,1.0,0.8662900409775747,0.05782384817537509
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.7871948550681898,0.5719524621963501,0.2298862785100937,0.25806668400764465,0.0030074352398514748,0.712648555636406,0.957859493792057,0.7366960493675858,0.6791228526516965
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.641793152703201,0.3506262004375458,0.14696261286735535,0.30296817421913147,0.0019819033332169056,0.5957068763673306,0.6123442202806473,0.6391404934366022,0.7972846689977143
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.7330849346428717,0.4735666513442993,0.1410803645849228,0.5469887256622314,0.0008459041127935052,0.9798957854509354,0.5878348524371784,0.45106297310575066,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.7550583002372345,0.4771563410758972,0.18608535826206207,0.13383366167545319,0.00245774257928133,0.9911135658621788,0.7753556594252586,0.6891538226954028,0.3521938465143505
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.8596169245685386,0.5084947347640991,0.2006111443042755,0.33566582202911377,0.004127745982259512,0.9109539538621902,0.8358797679344814,0.8122685657563895,0.883331110602931
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0003.png,3,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0003.png,0.7448875964259782,0.44367218017578125,0.1698082685470581,0.38628077507019043,0.0009114266140386462,0.8864755630493164,0.7075344522794088,0.46673836730944257,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.5491046296075472,0.26951032876968384,0.15532337129116058,0.2970895767211914,0.0012788069434463978,0.3422197774052621,0.6471807137131691,0.540049123738822,0.7818146755820826
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.6771935376525813,0.4508514702320099,0.16540850698947906,0.18462368845939636,0.0010625174036249518,0.9089108444750309,0.6892021124561628,0.49952751525174105,0.4858518117352536
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.5863239928853504,0.530262291431427,0.16597238183021545,0.06857383996248245,0.0006445770268328488,0.8429303392767906,0.6915515909592311,0.3956431711068873,0.18045747358548014
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.6644517674317987,0.5887230038642883,0.14212986826896667,0.365724116563797,0.0015117988223209977,0.660240612924099,0.5922077844540279,0.5774098614569212,0.9624318856942026
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.577825087048279,0.3304774761199951,0.13406091928482056,0.5189406275749207,0.0006644886452704668,0.5327421128749847,0.5585871636867523,0.4017052163190312,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.5340191994946679,0.5783567428588867,0.15847237408161163,0.038343675434589386,0.0008497473900206387,0.692635178565979,0.6603015586733818,0.45201006786840314,0.10090440903839312
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.734094921701522,0.5298677682876587,0.17953215539455414,0.2108716368675232,0.0024959566071629524,0.8441632241010666,0.748050647477309,0.6927678248054223,0.5549253601776926
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.7664406340031571,0.37575316429138184,0.2246083915233612,0.3282003700733185,0.0017875334015116096,0.6742286384105682,0.9358682980140051,0.6154351016610587,0.8636851844034696
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.7961962926053767,0.5303654670715332,0.20402401685714722,0.29360610246658325,0.002466082340106368,0.8426079154014587,0.8501000702381134,0.6899470048120466,0.772647638069956
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.8352073635832489,0.44569772481918335,0.2513512670993805,0.32576867938041687,0.0013684495352208614,0.892805390059948,1.0,0.5550913872393476,0.857285998369518
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.5400806479551098,0.2550522983074188,0.16469964385032654,0.2961341142654419,0.0011295280419290066,0.29703843221068393,0.6862485160430273,0.512798073496867,0.7793003006985313
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.5783194705666215,0.5446428060531616,0.16710570454597473,0.009729161858558655,0.001088706310838461,0.7979912310838699,0.6962737689415615,0.5047980477224547,0.025603057522522777
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.7412741169977423,0.46240657567977905,0.20525386929512024,0.18740150332450867,0.0011095014633610845,0.9450205489993095,0.8552244553963344,0.5089053522038146,0.4931618508539702
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.515069844719576,0.2516993284225464,0.14234349131584167,0.6540426015853882,0.0006744695128872991,0.28656040132045757,0.5930978804826736,0.4046894407145464,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.7832001334272339,0.446008563041687,0.15524061024188995,0.39141198992729187,0.0024048658087849617,0.8937767595052719,0.6468358760078748,0.6840653710931596,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0004.png,4,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0004.png,0.6134309337101822,0.5973632335662842,0.23161309957504272,0.014294463209807873,0.001131614437326789,0.6332398951053619,0.9650545815626781,0.5132001577709633,0.037617008446862825
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.644904072994684,0.2747288644313812,0.23279830813407898,0.09033690392971039,0.0046846866607666016,0.35852770134806644,0.9699929505586624,0.8427542929595396,0.23772869455186943
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.5855007666264935,0.264739453792572,0.15723487734794617,0.33775514364242554,0.001902763033285737,0.3273107931017877,0.6551453222831091,0.6297581328192157,0.8888293253748041
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.7529947394891399,0.32671022415161133,0.22624780237674713,0.24029314517974854,0.005378385540097952,0.5209694504737854,0.9426991765697798,0.8761663762730992,0.6323503820519698
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.5716404923462326,0.5789431929588318,0.16808243095874786,0.019546212628483772,0.0015727293211966753,0.6908025220036507,0.7003434623281162,0.5863243471944676,0.05143740165390466
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.7570057447702384,0.4401888847351074,0.13464120030403137,0.2912818491458893,0.004712626338005066,0.8755902647972107,0.5610050012667974,0.8441899506264245,0.7665311819628665
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.7553748180949609,0.5430905818939209,0.14055100083351135,0.39219382405281067,0.0032531137112528086,0.8028419315814972,0.5856291701396307,0.7553339503144901,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.8412784121143784,0.4979163408279419,0.20769041776657104,0.41737836599349976,0.001625870238058269,0.9440114349126816,0.865376740694046,0.5938478377294403,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.7359442257742106,0.3912610113620758,0.2000763863325119,0.30441156029701233,0.0016378737054765224,0.7226906605064869,0.8336516097187996,0.5955163467785843,0.8010830534131903
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.7167930857325282,0.3137442469596863,0.2280748337507248,0.42076218128204346,0.00133905082475394,0.48045077174901973,0.9503118072946867,0.550257248077665,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.5511520051437163,0.5719832181930542,0.14227381348609924,0.0146960923448205,0.001783914165571332,0.7125524431467056,0.5928075561920803,0.6149716650343952,0.03867392722321184
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.780349072794403,0.46945565938949585,0.16047142446041107,0.320072740316391,0.0021062190644443035,0.9670489355921745,0.6686309352517128,0.6532024351390671,0.8422966850431342
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.7313276683393423,0.5984414219856262,0.22421672940254211,0.21991801261901855,0.002586671616882086,0.6298705562949181,0.9342363725105922,0.7011433914975697,0.578731612155312
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.8137034995707862,0.38323140144348145,0.21401239931583405,0.3945028781890869,0.0031493939459323883,0.6975981295108795,0.8917183304826419,0.7476342462909196,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.7622411817917836,0.4944821000099182,0.18153981864452362,0.5074140429496765,0.0006443510064855218,0.9547434374690056,0.7564159110188484,0.3955735089817095,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.4738959535164575,0.23492412269115448,0.08718881756067276,0.47410720586776733,0.0015203093644231558,0.23413788340985786,0.3632867398361365,0.5786742661706369,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0005.png,5,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0005.png,0.7739360061952082,0.49200910329818726,0.14076735079288483,0.4266963601112366,0.001963086659088731,0.9624715521931648,0.5865306283036869,0.6369414081846105,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.6886887093937326,0.618424654006958,0.16508378088474274,0.37317416071891785,0.002161461627110839,0.5674229562282562,0.6878490870197614,0.6592060266474391,0.9820372650497838
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.6215088972502838,0.3120153248310089,0.17621754109859467,0.1688176989555359,0.003435678780078888,0.47504789009690296,0.7342397545774778,0.768336153883137,0.4442571025145681
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.5863781539448947,0.3427355885505676,0.14734266698360443,0.15361320972442627,0.0023734630085527897,0.5710487142205238,0.6139277790983518,0.6809936505478337,0.4042452887484902
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.8813695711258026,0.5256774425506592,0.2570291757583618,0.23378221690654755,0.006646084599196911,0.8572579920291901,1.0,0.9276388778999494,0.6152163602803883
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.6397514414174822,0.3012111485004425,0.23707817494869232,0.02548210322856903,0.003985346294939518,0.44128483906388294,0.9878257289528847,0.8038381842152248,0.06705816639097113
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.5426015126872726,0.4136943817138672,0.09375893324613571,0.17664359509944916,0.0009314829367212951,0.792794942855835,0.3906622218588988,0.47134651346070094,0.464851566051182
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.5638626486351662,0.5996423363685608,0.15750648081302643,0.016911007463932037,0.0024653279688209295,0.6261176988482475,0.6562770033876102,0.6898753611251114,0.04450265122087378
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.5679844338807323,0.2921523153781891,0.1789000779390335,0.7935611009597778,0.00034796964609995484,0.412975985556841,0.7454169914126396,0.2818661631595525,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.8938122158966854,0.507004976272583,0.2635866701602936,0.3133477568626404,0.0036343636456876993,0.9156094491481781,1.0,0.7817579085100215,0.8245993601648431
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.3085464418033443,0.16295188665390015,0.10362079739570618,0.22306188941001892,0.0005168374627828598,0.009224645793438069,0.43175332248210907,0.35280922200374326,0.5870049721316287
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.6872706688027737,0.3059653043746948,0.17968067526817322,0.7144078612327576,0.0026106303557753563,0.45614157617092144,0.7486694802840551,0.7033094074651228,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.5738284744150083,0.5599633455276489,0.10249464213848114,0.32234734296798706,0.0005765077657997608,0.7501145452260971,0.4270610089103381,0.3737337437994891,0.8482824814947028
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.7090984465637497,0.5006695985794067,0.14522510766983032,0.2923628091812134,0.0012006573379039764,0.9354075044393539,0.6051046152909597,0.526153754397759,0.769375813634772
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.8038935426327425,0.5164090394973755,0.29033198952674866,0.053713321685791016,0.0051851216703653336,0.8862217515707016,1.0,0.8672975607211948,0.1413508465415553
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.7181829007275435,0.38627299666404724,0.26293039321899414,0.055565256625413895,0.003004607744514942,0.7071031145751476,1.0,0.7364732496956589,0.14622435954056287
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0006.png,6,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0006.png,0.6351663887406743,0.5496786236763,0.21318873763084412,0.04602416977286339,0.0008969003683887422,0.7822543010115623,0.8882864067951839,0.4633469638479757,0.12111623624437734
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.49145303566091636,0.6972036361694336,0.11492282897233963,0.3439701497554779,0.0008937310194596648,0.32123863697052,0.47884512071808183,0.46260087064553634,0.9051846046196786
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.5948701061700659,0.2820001244544983,0.1753661334514618,0.4176972508430481,0.00082223309436813,0.38125038892030727,0.7306922227144241,0.44514929071858583,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.779811782295266,0.5394842028617859,0.22282609343528748,0.1679912507534027,0.003358659101650119,0.8141118660569191,0.9284420559803646,0.7629330794414776,0.44208223882474396
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.8356298410764676,0.4959571659564972,0.1870853751897812,0.46435844898223877,0.0022345317993313074,0.9501338563859463,0.7795223966240883,0.6669318606938288,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.6866426246021369,0.4887099862098694,0.15112730860710144,0.03334802761673927,0.0034734182991087437,0.9727812930941582,0.629697119196256,0.7709416232125675,0.08775796741247177
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.7501512832969368,0.6107369065284729,0.265173077583313,0.31289374828338623,0.0016473501455038786,0.5914471670985222,1.0,0.5968257722220689,0.8234046007457533
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.6926693028853235,0.4306119680404663,0.14235356450080872,0.4665117859840393,0.0008181483717635274,0.8456624001264572,0.5931398520867031,0.4441145088855018,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.780331358591498,0.49369826912879944,0.19463300704956055,0.3320404291152954,0.0009487842326052487,0.9571929089725018,0.8109708627065023,0.4752545465901945,0.8737906029349879
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.7412980596204741,0.5599890947341919,0.23228563368320465,0.1631484031677246,0.0020427361596375704,0.7500340789556503,0.9678568070133527,0.6461204334753172,0.4293379030729595
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.5848569237447105,0.5629514455795288,0.14128856360912323,0.1776966154575348,0.0008974630618467927,0.7407767325639725,0.5887023483713468,0.46347919450245695,0.4676226722566705
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.6769448149378027,0.42911311984062195,0.1025148332118988,0.37989217042922974,0.0015718723880127072,0.8409784995019436,0.4271451383829117,0.5862011515063902,0.9997162379716572
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.5928555971898726,0.2886362075805664,0.12610505521297455,0.5038477182388306,0.002155001275241375,0.40198814868927013,0.5254377300540607,0.6585113342674933,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.705932004298399,0.3796853721141815,0.13530710339546204,0.27446818351745605,0.005693902261555195,0.6865167878568172,0.5637795974810919,0.8900015387079113,0.7222846934669896
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.6454435321261678,0.5916168093681335,0.2060631811618805,0.25747019052505493,0.0005466698785312474,0.6511974707245827,0.8585965881745021,0.3634893780493667,0.6775531329606709
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.7025162935303909,0.34502357244491577,0.22238174080848694,0.385220468044281,0.0006732209585607052,0.5781986638903618,0.926590586702029,0.40431807341069476,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0007.png,7,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0007.png,0.69653711076485,0.34394538402557373,0.2546344995498657,0.045665543526411057,0.004338566213846207,0.5748293250799179,1.0,0.8242497631849549,0.12017248296423962
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.8105690646442799,0.4463285803794861,0.3430221974849701,0.2921926975250244,0.0011007608845829964,0.894776813685894,1.0,0.5071871913250612,0.7689281513816432
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.5326737479032394,0.32279324531555176,0.14871588349342346,0.17151790857315063,0.0010938644409179688,0.5087288916110992,0.6196495145559311,0.5058231538338626,0.45136291729776484
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.7686796767295756,0.3862152099609375,0.18215151131153107,0.44435128569602966,0.0027512123342603445,0.7069225311279297,0.7589646304647129,0.7156541130071316,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.3463194143455768,0.14977681636810303,0.08675044029951096,0.4799230396747589,0.0005133366212248802,0.0,0.361460167914629,0.3515254558847522,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.6172478515948816,0.3447533845901489,0.21430222690105438,0.02608208730816841,0.0022015373688191175,0.5773543268442154,0.89292594542106,0.6634728365430352,0.06863707186360109
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.5791884485377288,0.27958357334136963,0.16799579560756683,0.4554741382598877,0.0007579150842502713,0.3736986666917802,0.6999824816981952,0.4283364160829445,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.6587629447323052,0.4124422073364258,0.13005979359149933,0.35146406292915344,0.0009845802560448647,0.7888818979263306,0.5419158066312473,0.4831512762035695,0.9249054287609301
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.6650145149524358,0.5780848860740662,0.21857582032680511,0.2481795698404312,0.0004908926784992218,0.6934847310185432,0.9107325846950214,0.3431348022580479,0.6531041311590295
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.7461360353781388,0.47371283173561096,0.21052345633506775,0.01775806024670601,0.002892367774620652,0.9803525991737843,0.8771810680627823,0.7274646983338763,0.0467317374913316
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.8140877091931568,0.4614091217517853,0.1792517602443695,0.413550466299057,0.0019031744450330734,0.941903505474329,0.7468823343515396,0.6298078289815847,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.8313572661426499,0.5087400078773499,0.1966741532087326,0.41763734817504883,0.0020757941529154778,0.9101874753832817,0.8194756383697193,0.6498333280669988,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.8969707852348567,0.5056782960891724,0.27795565128326416,0.30253463983535767,0.004029630217701197,0.9197553247213364,1.0,0.8064904778495743,0.7961437890404149
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.5610418519256445,0.23521874845027924,0.15664102137088776,0.2628627419471741,0.0033715497702360153,0.23505858890712272,0.6526709223786991,0.7638455595061588,0.6917440577557212
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.7780147358500503,0.5677659511566162,0.15973970293998718,0.44748347997665405,0.004679420031607151,0.7257314026355743,0.66558209558328,0.8424827455375763,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.7674222094829416,0.3114550709724426,0.2783783972263336,0.36815696954727173,0.0028075119480490685,0.4732970967888833,1.0,0.7204318435525723,0.9688341303875572
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0008.png,8,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0008.png,0.8529371883565194,0.3769072890281677,0.24687594175338745,0.4722301959991455,0.0038951332680881023,0.6778352782130241,1.0,0.7983464195704487,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.5712428976257962,0.3694494962692261,0.16936977207660675,0.17636814713478088,0.0005779281491413713,0.6545296758413315,0.7057073836525282,0.37421109731879365,0.46412670298626546
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.6577941527633568,0.5941555500030518,0.2226116806268692,0.09721886366605759,0.0016176450299099088,0.6432639062404633,0.9275486692786217,0.5926980514841188,0.25583911491067785
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.854410449641763,0.5369629859924316,0.18464846909046173,0.45143336057662964,0.006131654605269432,0.8219906687736511,0.7693686212102573,0.9080106505863622,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.6084897739914267,0.31131839752197266,0.15703009068965912,0.24219462275505066,0.0025626434944570065,0.47286999225616466,0.6542920445402464,0.6989520895651965,0.6373542704080281
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.5408721315950623,0.31839150190353394,0.14789365231990814,0.4145904779434204,0.0002516356180422008,0.49497344344854366,0.6162235513329506,0.23005213264245628,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.8156097048087454,0.5646195411682129,0.2560921013355255,0.21898874640464783,0.004517565947026014,0.7355639338493347,1.0,0.8339903937663362,0.5762861747490732
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.5631951406908619,0.6449512839317322,0.15662221610546112,0.19430014491081238,0.0015391242923215032,0.48452723771333694,0.652592567106088,0.5814470944893811,0.5113161708179274
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.7548856286470811,0.4512518048286438,0.2291537970304489,0.18452197313308716,0.0010176377836614847,0.9101618900895119,0.9548074876268705,0.4902287774343175,0.4855841398239136
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.8116160473244478,0.4504586160182953,0.17013178765773773,0.42625564336776733,0.002647263929247856,0.9076831750571728,0.7088824485739073,0.7065854409404951,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.6137708078794866,0.32876715064048767,0.14678682386875153,0.3277944028377533,0.0014673632103949785,0.527397345751524,0.6116117661197981,0.5707021875285386,0.862616849573035
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.4190401273271829,0.30692440271377563,0.09289928525686264,0.32397937774658203,0.0001359904563287273,0.45913875848054897,0.3870803552369277,0.14915118693210372,0.8525773098594264
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.6768054256060771,0.3119733929634094,0.18533702194690704,0.6837745308876038,0.001750380382873118,0.47491685301065456,0.772237591445446,0.6106363690769879,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.8635888584858199,0.43105971813201904,0.2154752016067505,0.35374802350997925,0.003954203799366951,0.8470616191625595,0.8978133400281271,0.8019559721092254,0.9309158513420507
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.694967044903313,0.49476802349090576,0.19738459587097168,0.02971147745847702,0.0016809384105727077,0.9538499265909195,0.8224358161290487,0.6014124292043264,0.07818809857493952
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.6915902852276714,0.5798747539520264,0.19535939395427704,0.5465143918991089,0.0005483985878527164,0.6878913938999176,0.8139974748094877,0.3640944984593994,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0009.png,9,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0009.png,0.42422370668623893,0.3005353808403015,0.09679935872554779,0.3312526345252991,0.0001530500449007377,0.43917306512594234,0.4033306613564491,0.16285987939982444,0.8717174592771028
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.6704839497870161,0.3670973777770996,0.2225990742444992,0.08863921463489532,0.0020986509043723345,0.6471793055534363,0.9274961426854134,0.6523686065747684,0.2332610911444614
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.7110441686551522,0.4131958484649658,0.22258344292640686,0.030851446092128754,0.0029616323299705982,0.7912370264530182,0.927431012193362,0.7330622186258022,0.08118801603191778
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.7778628373692659,0.4315928518772125,0.20991018414497375,0.3180709183216095,0.0012855345848947763,0.8487276621162891,0.874625767270724,0.5412099947574748,0.8370287324252882
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.8697790173664266,0.46241772174835205,0.24504254758358002,0.21154966950416565,0.004106417298316956,0.9450553804636002,1.0,0.8110238189554411,0.5567096565899096
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.7342496433881629,0.5698586106300354,0.2511926591396332,0.2065809667110443,0.0013242514105513692,0.7191918417811394,1.0,0.5477878896610034,0.5436341229238009
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.9116364613990301,0.4356265366077423,0.24881285429000854,0.2984734773635864,0.007039450109004974,0.8613329268991947,1.0,0.9416724216903715,0.785456519377859
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.8231386988671866,0.4277927279472351,0.224237322807312,0.2878873348236084,0.0027156274300068617,0.8368522748351097,0.9343221783638,0.7125865019085679,0.7575982495358116
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.8947368091013533,0.553561806678772,0.23800767958164215,0.3868780732154846,0.005131193436682224,0.7701193541288376,0.991698664923509,0.8647656135425973,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.8414846618714866,0.4451272487640381,0.21738509833812714,0.21961691975593567,0.005094381049275398,0.891022652387619,0.9057712430755298,0.863022415420796,0.5779392625156202
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.7604586984687636,0.4707384705543518,0.13267041742801666,0.3729167580604553,0.0018588616512715816,0.9710577204823494,0.5527934059500694,0.6243975083764854,0.9813598896327772
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.702649330090087,0.3778398633003235,0.16029849648475647,0.44661325216293335,0.0016141319647431374,0.6807495728135109,0.6679104020198187,0.5922053505603527,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.6554004684663309,0.46097445487976074,0.13492952287197113,0.3510313034057617,0.00031255162321031094,0.9405451714992523,0.5622063452998798,0.26404010096042607,0.9237665879098993
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.8230012619314453,0.4891759157180786,0.21386070549488068,0.27418527007102966,0.001857157563790679,0.9713252633810043,0.8910862728953362,0.6241870935557045,0.7215401843974465
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.6772429345465579,0.32535064220428467,0.16394241154193878,0.29684972763061523,0.003930022940039635,0.5167207568883896,0.683093381424745,0.8004846759516044,0.7811834937647769
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.602573691819113,0.3625960946083069,0.20693211257457733,0.20560306310653687,0.0003676803898997605,0.633112795650959,0.8622171357274055,0.29126243419104053,0.5410606923856234
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.7360590490770321,0.5022114515304565,0.13738122582435608,0.31711965799331665,0.0019885075744241476,0.9305892139673233,0.5724217742681503,0.6399077609624287,0.8345254157718859
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.4648751330592361,0.28529566526412964,0.13811016082763672,0.2921530604362488,0.00026479666121304035,0.39154895395040523,0.5754590034484863,0.23779667740630275,0.7688238432532862
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.8049133016519397,0.4476465880870819,0.19417859613895416,0.5627347230911255,0.0014633375685662031,0.898895587772131,0.809077483912309,0.5700855205864311,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.6713688384008736,0.43556979298591614,0.1388402283191681,0.36805039644241333,0.0005855443887412548,0.8611556030809879,0.5785009513298671,0.3767552834013944,0.9685536748484561
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.5506484372543811,0.6144756078720093,0.16258235275745392,0.06982122361660004,0.0015547135844826698,0.579763725399971,0.6774264698227247,0.5837214774609212,0.18374006214894748
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.6041100160693248,0.45493897795677185,0.14019645750522614,0.013147925026714802,0.0015891734510660172,0.921684306114912,0.5841519062717756,0.5886767277921459,0.03459980270188106
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.7031050427669342,0.4581500291824341,0.14369626343250275,0.34553366899490356,0.0007651936030015349,0.9317188411951065,0.5987344309687614,0.43029676711072123,0.9092991289339567
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.5305453795474399,0.36061716079711914,0.1600128561258316,0.03550371155142784,0.0011344437953084707,0.6269286274909973,0.6667202338576317,0.5137443926480977,0.09343081987217852
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.6470495442546956,0.5235108137130737,0.11557435989379883,0.31011852622032166,0.0009877150878310204,0.8640287071466446,0.4815598328908285,0.483831098099623,0.8161013847903201
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.5573886537148018,0.2964869737625122,0.1312144547700882,0.43036088347435,0.0008897316292859614,0.42652179300785076,0.5467268948753675,0.46165618939934555,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.6713137542325004,0.3092658817768097,0.17399290204048157,0.52632075548172,0.0021276024635881186,0.4664558805525304,0.7249704251686733,0.6555434500645567,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.7565717680673133,0.4527081251144409,0.23915113508701324,0.06164640933275223,0.0019511771388351917,0.9147128909826279,0.9964630628625553,0.6355394918664773,0.16222739298092692
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.72620806898064,0.30232295393943787,0.21369117498397827,0.4805850684642792,0.0026034843176603317,0.44475923106074344,0.8903798957665762,0.7026653237297766,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.4302927062891502,0.2578611373901367,0.11351554095745087,0.26962342858314514,0.0005392988678067923,0.30581605434417736,0.4729814206560453,0.3608926521303148,0.7095353383766977
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.8544969694761424,0.5137399435043335,0.272903710603714,0.2453012764453888,0.0032786643132567406,0.8945626765489578,1.0,0.7571948611320479,0.6455296748562863
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.7296261564147445,0.5814797282218933,0.21666400134563446,0.47181329131126404,0.0007124610710889101,0.6828758493065834,0.902766672273477,0.4157335997629055,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0011.png,11,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0011.png,0.6919343159523184,0.5126971006393433,0.11076440662145615,0.36805665493011475,0.0013702674768865108,0.8978215605020523,0.46151836092273396,0.5553872713677694,0.9685701445529336
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.5078178767336159,0.24047045409679413,0.14800973236560822,0.5971057415008545,0.0006247545825317502,0.25147016905248176,0.6167072181900343,0.3894586422434443,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.8566788121880696,0.3972838521003723,0.21543057262897491,0.31016236543655396,0.007904613390564919,0.7415120378136635,0.8976273859540622,0.970017889541712,0.8162167511488262
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.7778795758783926,0.36013343930244446,0.19296599924564362,0.460585355758667,0.0038602144923061132,0.6254169978201389,0.8040249968568485,0.7961879099011858,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.7703438290057437,0.4393177628517151,0.1719665229320526,0.47794777154922485,0.0014897305518388748,0.8728680089116096,0.7165271788835526,0.5741010906687805,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.5346120931962608,0.32668235898017883,0.1604345291852951,0.24328777194023132,0.00044998788507655263,0.5208823718130589,0.6684772049387296,0.32707829340884764,0.6402309787900824
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.7873896881318827,0.36831429600715637,0.19295509159564972,0.5768885016441345,0.003981470130383968,0.6509821750223637,0.8039795483152072,0.8036046845224458,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.7535257534750005,0.3514583110809326,0.2061678171157837,0.31702980399131775,0.003383974079042673,0.5983072221279144,0.8590325713157654,0.7647218870444533,0.8342889578718888
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.5892814420612532,0.6538997888565063,0.19269070029258728,0.010017551481723785,0.004443009849637747,0.45656315982341766,0.8028779178857803,0.829979288443885,0.026361977583483645
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.4695530190393054,0.6301388144493103,0.1491997241973877,0.01777954399585724,0.0009132509003393352,0.5308162048459053,0.6216655174891155,0.4671610451512117,0.046788273673308525
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.862918082682789,0.4042009115219116,0.223291277885437,0.3862045407295227,0.004253116436302662,0.7631278485059738,0.9303803245226543,0.8194625230968022,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.6146944652047452,0.25229376554489136,0.24218730628490448,0.027086559683084488,0.005241296254098415,0.2884180173277856,1.0,0.8699079878944523,0.07128042021864339
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.7231291620990632,0.36052820086479187,0.20815779268741608,0.38499292731285095,0.0010635966900736094,0.6266506277024746,0.867324136197567,0.49974693171620294,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.7508608869554393,0.40931612253189087,0.21477314829826355,0.11391445994377136,0.004171059001237154,0.779112882912159,0.8948881179094315,0.8147774100825257,0.299774894588872
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.6976476591683968,0.4514197111129761,0.11528734862804413,0.4469712972640991,0.0011745275696739554,0.9106865972280502,0.48036395261685055,0.5213299768597062,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.6744626719700663,0.6959607601165771,0.30818822979927063,0.06821224093437195,0.011736618354916573,0.3251226246356964,1.0,1.0,0.17950589719571566
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0012.png,12,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0012.png,0.5618920928029587,0.36674097180366516,0.1596677601337433,0.3316039443016052,0.00013746441982220858,0.6460655368864536,0.6652823338905971,0.150365751066313,0.8726419586884347
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.901039089333058,0.4923376142978668,0.19744431972503662,0.40606826543807983,0.005098136607557535,0.9614449553191662,0.822684665520986,0.8632008123240492,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.6933806681511858,0.4069077670574188,0.14582058787345886,0.2976754605770111,0.002063881605863571,0.7715867720544338,0.6075857828060787,0.6485017216505318,0.7833564752026608
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.5395459549083385,0.32183897495269775,0.110214464366436,0.1911945641040802,0.0025558515917509794,0.5057467967271805,0.45922693486015004,0.6983291878800096,0.5031435897475794
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.723074104012511,0.3421921133995056,0.22335664927959442,0.28294485807418823,0.0020375922322273254,0.569350354373455,0.9306527053316435,0.6455377053394187,0.7445917317741796
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.5367896621620449,0.3666684031486511,0.14386968314647675,0.021912086755037308,0.0018093109829351306,0.6458387598395348,0.5994570131103198,0.6182056893898744,0.057663386197466596
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.6076564844905471,0.39446014165878296,0.11971428990364075,0.2656380236148834,0.0012408719630911946,0.7326879426836967,0.4988095412651698,0.5334004988842591,0.6990474305654827
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.8343826234291025,0.5092136859893799,0.19723199307918549,0.35452017188072205,0.002586779184639454,0.9087072312831879,0.8217999711632729,0.7011531583374119,0.9329478207387422
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.6710300517814379,0.48831427097320557,0.1621699333190918,0.230656698346138,0.0004833596758544445,0.9740179032087326,0.6757080554962158,0.34025426981749035,0.6069913114372053
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.6590352918713756,0.517359733581543,0.1500525325536728,0.12782591581344604,0.001856833929196,0.8832508325576782,0.6252188856403034,0.6241471122582726,0.33638398898275274
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.8748851288948316,0.41417235136032104,0.24328172206878662,0.4486241936683655,0.0031329863704741,0.7942885980010033,1.0,0.7463941979781228,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.7929012096471728,0.35832899808883667,0.2961188554763794,0.23017236590385437,0.005124319810420275,0.6197781190276146,1.0,0.864441044328415,0.6057167523785641
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.5636168949905913,0.29055821895599365,0.15234433114528656,0.36359018087387085,0.0007606055587530136,0.4079944342374803,0.634768046438694,0.4290628438764233,0.9568162654575548
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.36775282343044063,0.1998092383146286,0.12935252487659454,0.5506104230880737,5.827743007102981e-05,0.12440386973321449,0.5389688536524773,0.0749640256589325,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.8159729418601845,0.4391941428184509,0.17043495178222656,0.3373600244522095,0.004481633193790913,0.8724816963076591,0.7101456324259441,0.8320652501411362,0.8877895380321302
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.549960424729375,0.27629488706588745,0.1815863698720932,0.22253744304180145,0.001086855074390769,0.3634215220808984,0.7566098744670551,0.5044291129939537,0.5856248501100039
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.5942974888530487,0.36874687671661377,0.15621457993984222,0.24076762795448303,0.0007759156287647784,0.652333989739418,0.6508940830826759,0.4331568554659721,0.63359902093285
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.5387822689491824,0.2524991035461426,0.18542851507663727,0.3116719424724579,0.0006233080057427287,0.28905969858169567,0.772618812819322,0.3890012687379432,0.8201893222959418
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.7198230709665303,0.3443449139595032,0.16611486673355103,0.4446253180503845,0.003281830810010433,0.5760778561234474,0.6921452780564626,0.7574245228502292,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.5861243864685488,0.4104350805282593,0.17223306000232697,0.053177669644355774,0.0008837472996674478,0.7826096266508102,0.7176377500096958,0.4602359523378687,0.1399412359061994
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.7026045992435812,0.4182705879211426,0.1475747972726822,0.449776828289032,0.0010848540114238858,0.8070955872535706,0.6148949886361759,0.5040297059066293,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.8174458341929662,0.47356078028678894,0.20256386697292328,0.31072568893432617,0.0016019660979509354,0.9798774383962154,0.8440161123871803,0.5904915669881173,0.8176991814061215
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.6525167953097006,0.5464790463447571,0.15615415573120117,0.3283963203430176,0.0005369861610233784,0.7922529801726341,0.6506423155466716,0.3600723205708707,0.864200843007941
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.475906712902198,0.27857527136802673,0.16176266968250275,0.2586418390274048,0.0002717165043577552,0.37054772302508365,0.6740111236770948,0.2417743844702756,0.6806364184931705
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.7448647886768397,0.5238845348358154,0.14353224635124207,0.5292755961418152,0.001874864799901843,0.8628608286380768,0.5980510264635086,0.6263649285854561,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.42361614253163604,0.2379615753889084,0.11408873647451401,0.7327514290809631,0.000254342972766608,0.24362992309033882,0.47536973531047505,0.2316649800455675,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.8229937356749648,0.5276996493339539,0.2556387782096863,0.04487079754471779,0.009175095707178116,0.8509385958313942,1.0,1.0,0.11808104617030997
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.8186204181910673,0.5005805492401123,0.19446156919002533,0.2576698660850525,0.003496234305202961,0.935685783624649,0.8102565382917722,0.7725037294881654,0.6780785949606645
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.6206419705199367,0.6099585294723511,0.17693457007408142,0.4085603952407837,0.0003549609100446105,0.5938795953989029,0.7372273753086727,0.2852395172306562,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.7515491505031063,0.408803254365921,0.19457894563674927,0.268169105052948,0.0023318559397011995,0.7775101698935032,0.8107456068197887,0.6768647672412943,0.7057081711919684
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.4916191941412861,0.32793372869491577,0.15197166800498962,0.25718048214912415,0.00016335748659912497,0.5247929021716118,0.6332152833541235,0.17079250843564528,0.6767907424976951
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.785378946669914,0.44530364871025085,0.18246668577194214,0.37700197100639343,0.0014243132900446653,0.8915739022195339,0.7602778573830923,0.56402740514641,0.9921104500168249
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0014.png,14,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0014.png,0.7220782932132207,0.49459734559059143,0.16165126860141754,0.04513781517744064,0.005105002783238888,0.9543832950294018,0.6735469525059065,0.8635266413198172,0.11878372415115959
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.49267767844368904,0.26461225748062134,0.10888151824474335,0.530407726764679,0.0007791270036250353,0.3269133046269418,0.45367299268643063,0.43400715699870906,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.6535987390741125,0.38890165090560913,0.1634555608034134,0.562164306640625,0.00047942387755028903,0.7153176590800285,0.6810648366808891,0.3387359613833489,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.7770498358844099,0.5924196243286133,0.2051314115524292,0.29809170961380005,0.004507353529334068,0.6486886739730835,0.8547142148017883,0.8334447565649513,0.7844518674047369
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.7364499821764017,0.507427453994751,0.2007940262556076,0.24778585135936737,0.0008555855602025986,0.9142892062664032,0.8366417760650318,0.4534419319720413,0.652068029893072
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.6852039982572852,0.5161172151565552,0.2076721489429474,0.035691022872924805,0.001539762131869793,0.8871337026357651,0.8653006205956142,0.5815405585100253,0.0939237444024337
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.7639204222231437,0.3230203092098236,0.25909748673439026,0.39188843965530396,0.0020271935500204563,0.5094384662806988,1.0,0.6443555293557363,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.55172954958825,0.33216267824172974,0.13162927329540253,0.30552881956100464,0.0007302718004211783,0.5380083695054054,0.5484553053975105,0.4207478628468624,0.8040232093710649
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.8992375074204981,0.47605395317077637,0.24727554619312286,0.2988958954811096,0.003047177568078041,0.9876686036586761,1.0,0.7398068176898293,0.78656814600292
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.8105393603618943,0.5278458595275879,0.17563526332378387,0.4416234493255615,0.0030937432311475277,0.8504816889762878,0.7318135971824329,0.7434030980571122,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.5673177064627702,0.2839888632297516,0.2154962718486786,0.038999177515506744,0.0022184662520885468,0.3874651975929738,0.8979011327028275,0.6652535807874247,0.10262941451449144
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.6972677894313167,0.45136356353759766,0.11399919539690018,0.51524418592453,0.0012023432645946741,0.9105111360549927,0.4749966474870841,0.5264618174747747,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.5773141983542143,0.30510616302490234,0.13242319226264954,0.42579060792922974,0.0010796735296025872,0.45345675945281994,0.5517633010943731,0.5029927207602253,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.699472676715646,0.33534538745880127,0.3038898706436157,0.04096516594290733,0.0053672464564442635,0.547954335808754,1.0,0.8756636629295939,0.10780306827080877
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.6687533008226656,0.549109935760498,0.17978478968143463,0.2452004849910736,0.0008339454652741551,0.7840314507484436,0.749103290339311,0.44809285347313543,0.6452644341870358
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.5001676585997658,0.7235910296440125,0.18783149123191833,0.09244005382061005,0.0018966748612001538,0.2387780323624611,0.7826312134663265,0.6290215596877654,0.24326329952792117
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0015.png,15,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0015.png,0.7794252905169496,0.6585040092468262,0.2980923652648926,0.3004041910171509,0.006252675782889128,0.4421749711036682,1.0,0.9127687898742108,0.790537344781976
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.669791365061986,0.3839704096317291,0.15095727145671844,0.3666802942752838,0.0010923427762463689,0.6999075300991535,0.6289886310696602,0.5055211811475511,0.9649481428296942
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.7309898147693907,0.30789387226104736,0.2669786214828491,0.33853423595428467,0.0019451710395514965,0.4621683508157731,1.0,0.6348294971181857,0.8908795683007491
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.7416314075033364,0.5628526210784912,0.15569724142551422,0.2841411828994751,0.004829203709959984,0.741085559129715,0.6487385059396427,0.8500927789309457,0.7477399549986187
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.5527672409555219,0.30994611978530884,0.1987924575805664,0.04623492807149887,0.0015415763482451439,0.46858162432909023,0.8283019065856934,0.5818062087167174,0.12167086334604967
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.6319872787055848,0.6928229331970215,0.16405747830867767,0.3855248689651489,0.00263785058632493,0.33492833375930786,0.683572826286157,0.7057477227677812,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.683221088684577,0.3864246606826782,0.17891882359981537,0.4304468631744385,0.0006239291396923363,0.7075770646333694,0.7454950983325641,0.3891977591791877,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.8626804363835222,0.4085250496864319,0.22069710493087769,0.4125608205795288,0.004179567098617554,0.7766407802700996,0.9195712705453237,0.8152672845555807,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.768739298874748,0.3191677927970886,0.21781431138515472,0.39663171768188477,0.003746184054762125,0.49739935249090206,0.907559630771478,0.789006415584136,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.7654111514188239,0.48503461480140686,0.13741451501846313,0.24301594495773315,0.004084571730345488,0.9842668287456036,0.5725604792435964,0.8097424493128875,0.6395156446256136
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.8500383615145443,0.46861934661865234,0.21266357600688934,0.4016011357307434,0.0015259786741808057,0.9644354581832886,0.886098233362039,0.5795130162037839,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.6339279065090718,0.6159341931343079,0.120671346783638,0.3001565933227539,0.0034333812072873116,0.5752056464552879,0.5027972782651584,0.7681766532305617,0.789885771901984
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.5379116318812451,0.2847849130630493,0.1818782538175583,0.259038507938385,0.0005518654943443835,0.3899528533220292,0.7578260575731596,0.365303664021725,0.6816802840483815
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.7278664289481981,0.49318361282348633,0.13439776003360748,0.25679725408554077,0.0023985039442777634,0.9588012099266052,0.5599906668066978,0.6834461151567115,0.6757822475935283
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.7518577104260051,0.5031198263168335,0.22078515589237213,0.09038673341274261,0.002054859884083271,0.9277505427598953,0.9199381495515506,0.6474885160680603,0.2378598247703753
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.6176375731289576,0.6915732622146606,0.21648606657981873,0.14225973188877106,0.003274590242654085,0.3388335555791855,0.9020252774159114,0.7568990636236543,0.37436771549676595
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0016.png,16,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0016.png,0.6381204072071143,0.40429770946502686,0.2282719761133194,0.08345244824886322,0.0005459538660943508,0.7634303420782089,0.9511332338054975,0.3632383142171727,0.2196117059180611
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.7330340193082298,0.44999629259109497,0.15897077322006226,0.290324866771698,0.001608322374522686,0.9062384143471718,0.6623782217502594,0.5913884295396364,0.764012807293942
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.7493258456548904,0.3934113383293152,0.218108668923378,0.1590171456336975,0.0036135895643383265,0.72941043227911,0.908786120514075,0.7803878156355857,0.4184661727202566
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.7277463575575079,0.5667400360107422,0.19566664099693298,0.2357901781797409,0.002420980017632246,0.7289373874664307,0.8152776708205541,0.6856270789492174,0.620500468894055
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.8442343241537713,0.5667943954467773,0.20920652151107788,0.4415706396102905,0.004956512711942196,0.7287675142288208,0.8716938396294912,0.8563836719851109,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.7572466236647808,0.3393931984901428,0.23652216792106628,0.34284985065460205,0.0019239889224991202,0.5606037452816963,0.9855090330044429,0.6323092912611217,0.902236449091058
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.5058852530493072,0.3131287097930908,0.1750391572713852,0.01810610294342041,0.0013108111452311277,0.4785272181034089,0.729329821964105,0.545523980521338,0.047647639324790554
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.7587574649410238,0.38972359895706177,0.22408561408519745,0.2010810673236847,0.002994079142808914,0.717886246740818,0.9336900586883228,0.7356418711590978,0.5291607034833807
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.7203480477279417,0.6116021871566772,0.22884266078472137,0.2182397097349167,0.002425859682261944,0.5887431651353836,0.9535110866030058,0.6860980734547784,0.5743150256182018
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.7693278962293529,0.39024218916893005,0.21887783706188202,0.2064918577671051,0.0038167431484907866,0.7195068411529064,0.9119909877578418,0.7934744148027691,0.5433996257029081
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.8223124454914866,0.5108766555786133,0.1812843233346939,0.5001590251922607,0.0025589726865291595,0.9035104513168335,0.7553513472278913,0.6986156237122767,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.8081663883209768,0.5444992184638977,0.299907386302948,0.11830835044384003,0.005641008727252483,0.7984399423003197,1.0,0.8877349639279861,0.31133776432589483
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.29199558537059184,0.1553468108177185,0.1307705044746399,0.21876616775989532,0.0001606192090548575,0.0,0.5448771019776663,0.16870955422512265,0.5757004414734087
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.7673766576782413,0.4192410111427307,0.2286262959241867,0.301588773727417,0.0009612302528694272,0.8101281598210335,0.952609566350778,0.4780285586845545,0.7936546677037289
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.7429386403578417,0.4979734420776367,0.18141232430934906,0.3531453609466553,0.0005787754198536277,0.9438329935073853,0.7558846846222878,0.3744954093389354,0.9293298972280402
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.8019134311974198,0.5926350355148315,0.25538361072540283,0.2356218695640564,0.0049897548742592335,0.6480155140161514,1.0,0.858000577079682,0.6200575514843589
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0017.png,17,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0017.png,0.6096563057127198,0.40314289927482605,0.13152976334095,0.3560163378715515,0.0004025343805551529,0.7598215602338314,0.5480406805872917,0.3070594740683449,0.9368850996619776
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.5274350260880056,0.7606945633888245,0.2167380005121231,0.006245528347790241,0.005217238329350948,0.12282948940992355,0.9030750021338463,0.8687933539503565,0.016435600915237478
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.5611384300687533,0.5851519107818604,0.186855286359787,0.06946872174739838,0.0006421997677534819,0.6714002788066864,0.7785636931657791,0.39490949851742585,0.18281242565104835
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.5027399799980116,0.24377702176570892,0.12413065135478973,0.41888266801834106,0.0009527546353638172,0.2618031930178405,0.5172110473116239,0.4761428315966892,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.701852157413254,0.3440812826156616,0.20657773315906525,0.4211845397949219,0.000989489839412272,0.5752540081739426,0.8607405548294386,0.48421515404895854,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.7919807781812807,0.5442374348640442,0.2296043187379837,0.3509364724159241,0.0010982006788253784,0.7992580160498619,0.9566846614082655,0.5066816801712792,0.9235170326734844
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.5913033942804842,0.5401217937469482,0.18515099585056305,0.05190901458263397,0.0006044276524335146,0.8121193945407867,0.7714624827106794,0.3829537224475974,0.13660266995429993
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.5293162970361664,0.36316603422164917,0.11052382737398148,0.3260396122932434,0.0003606978280004114,0.6348938569426537,0.4605159473915895,0.2879740351121374,0.8579989797190616
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.32881135429198544,0.2679606080055237,0.10405325889587402,0.09524674713611603,0.0002681588230188936,0.3373769000172616,0.4335552453994751,0.23973724192662202,0.2506493345687264
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.48401709014159555,0.31321465969085693,0.10235138982534409,0.5903451442718506,0.00028593913884833455,0.47879581153392803,0.42646412427226704,0.24975643759894797,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.7497123503821691,0.5217852592468262,0.1822250932455063,0.2570897340774536,0.0019762986339628696,0.8694210648536682,0.7592712218562763,0.6384874984070795,0.6765519317827726
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.8603093020178384,0.4828222990036011,0.17146454751491547,0.3768714666366577,0.003912905231118202,0.9911803156137466,0.7144356146454811,0.7994378812813472,0.9917670174648887
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.6689275453660899,0.49466878175735474,0.13417480885982513,0.3098253309726715,0.0005673858104273677,0.9541600570082664,0.5590617035826048,0.3706461777458329,0.8153298183491355
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.6845976240354965,0.29342490434646606,0.21649761497974396,0.2544783353805542,0.0032315305434167385,0.41695282608270656,0.9020733957489332,0.7537511319747222,0.6696798299488268
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.5515584404814073,0.3145527243614197,0.11079806089401245,0.5300061702728271,0.0009373151697218418,0.4829772636294366,0.46165858705838525,0.47267074110024326,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.735421847009936,0.4081607460975647,0.2019743174314499,0.26274245977401733,0.0015729529550299048,0.7755023315548897,0.8415596559643745,0.5863564875839679,0.6914275257210982
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0018.png,18,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0018.png,0.5850395742895304,0.32857680320739746,0.15541428327560425,0.3503539562225342,0.0005884931888431311,0.5268025100231171,0.6475595136483511,0.3777334115588848,0.9219840953224584
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.754086217799101,0.4806838035583496,0.13950765132904053,0.6133281588554382,0.0011747470125555992,0.9978631138801575,0.5812818805376689,0.5213708778950122,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.5238737471738721,0.3813861012458801,0.15772220492362976,0.08222027868032455,0.0005007764557376504,0.6918315663933754,0.6571758538484573,0.34686459175214535,0.2163691544219067
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.7090063149066516,0.3247353136539459,0.2364426553249359,0.6989353895187378,0.0007869044784456491,0.514797855168581,0.9851777305205663,0.4360545567996295,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.5299444007019457,0.3487287163734436,0.16774962842464447,0.12115742266178131,0.0006014780374243855,0.5897772386670113,0.6989567851026853,0.3819955806076503,0.3188353227941613
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.8302624139458757,0.43707728385925293,0.20593030750751495,0.2957208454608917,0.0036906166933476925,0.8658665120601654,0.858042947947979,0.7854306530460062,0.7782127512128729
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.6638430119034886,0.42382070422172546,0.1807899922132492,0.3043328523635864,0.00034735805820673704,0.8244397006928921,0.7532916342218717,0.2815688893526804,0.8008759272725958
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.8322740903244322,0.3492036461830139,0.23632539808750153,0.4227602779865265,0.0045924559235572815,0.5912613943219185,0.9846891586979231,0.837955697673919,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.49783016370285926,0.32152074575424194,0.14801765978336334,0.17539429664611816,0.000561376684345305,0.5047523304820061,0.6167402490973473,0.3685911961907636,0.46156393854241623
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.7557016893010863,0.3780074715614319,0.21937623620033264,0.23636355996131897,0.0029883957467973232,0.6812733486294746,0.9140676508347194,0.7351919368557559,0.6220093683192605
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.631646326560458,0.41959908604621887,0.1433974951505661,0.03301307186484337,0.00366822793148458,0.811247143894434,0.5974895631273588,0.7839753548711914,0.08687650490748255
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.7663876234821072,0.6059151887893677,0.23965834081172943,0.25959116220474243,0.002918113488703966,0.606515035033226,0.9985764200488727,0.72955996540137,0.6831346373809011
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.6887109147196473,0.3580505847930908,0.18587960302829742,0.21208718419075012,0.0031526745297014713,0.6189080774784088,0.7744983459512393,0.7478814494091957,0.5581241689230266
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.5795848264405808,0.3445149064064026,0.1488630324602127,0.3806297779083252,0.0003484373155515641,0.5766090825200081,0.6202626352508863,0.28209324443725003,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.6501918496500859,0.5018806457519531,0.13531097769737244,0.2845851182937622,0.0005281693302094936,0.9316229820251465,0.5637957404057186,0.35692000806157614,0.7489082060362163
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.5229491535368559,0.31096333265304565,0.1533501297235489,0.06971646845340729,0.002067034365609288,0.4717604145407678,0.6389588738481204,0.6488548336806408,0.1834643906668613
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0019.png,19,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0019.png,0.8301971035540783,0.5700551271438599,0.2567411959171295,0.26293596625328064,0.004695931449532509,0.7185777276754379,1.0,0.8433330890269229,0.6919367532981069
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.589652327018466,0.3462028503417969,0.1663162112236023,0.29602617025375366,0.0005406136624515057,0.5818839073181152,0.6929842134316763,0.36135782066818767,0.779016237509878
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,2,0,1,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.8521574947762125,0.4242672324180603,0.24203713238239288,0.3305864930152893,0.0025268220342695713,0.8258351013064384,1.0,0.6956491843550885,0.869964455303393
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,3,0,2,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.6657745843308033,0.37476271390914917,0.14559060335159302,0.5543177127838135,0.001220663427375257,0.6711334809660912,0.6066275139649709,0.5297851434059384,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,4,0,3,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.6328670982991692,0.4675992727279663,0.12815552949905396,0.23358049988746643,0.0005607681814581156,0.9612477272748947,0.5339813729127248,0.3683821573597445,0.6146855260196485
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,5,1,0,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.543310276021975,0.20284998416900635,0.17186301946640015,0.49160513281822205,0.0013571144081652164,0.13390620052814495,0.716095914443334,0.5532385661221255,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.6861760545257476,0.4424625039100647,0.151298388838768,0.5425307154655457,0.00045469129690900445,0.8826953247189522,0.6304099534948667,0.3289778842464079,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,7,1,2,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.6114919930067569,0.5190298557281494,0.165119469165802,0.10441093146800995,0.0006650473806075752,0.8780317008495331,0.6879977881908417,0.40187321970277284,0.27476560912634196
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,8,1,3,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.7524267149206839,0.6192562580108643,0.27952858805656433,0.08354795724153519,0.009028132073581219,0.5648241937160492,1.0,1.0,0.219863045372461
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,9,2,0,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.7143901928813832,0.5092427730560303,0.19194747507572174,0.056271523237228394,0.0027862004935741425,0.9086163341999054,0.7997811461488407,0.7186340215745718,0.14808295588744314
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,10,2,1,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.7741820627846651,0.4214365482330322,0.18114128708839417,0.4445401132106781,0.0017503680428490043,0.8169892132282257,0.754755362868309,0.6106347598228185,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,11,2,2,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.6104409068238793,0.3252027630805969,0.1900467723608017,0.20989099144935608,0.0012820684351027012,0.5162586346268654,0.7918615515033405,0.540612575335024,0.5523447143404108
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,12,2,3,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.8843762984261755,0.4633253812789917,0.22993764281272888,0.2457098364830017,0.0050809611566364765,0.9478918164968491,0.9580735117197037,0.8623839001348359,0.6466048328500045
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,13,3,0,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.7913443506970944,0.4147002398967743,0.2117040902376175,0.48919057846069336,0.0013479535700753331,0.7959382496774197,0.882100375990073,0.5517310519873866,1.0
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,14,3,1,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.6740970508808081,0.40151113271713257,0.20314693450927734,0.20272400975227356,0.0008615495753474534,0.7547222897410393,0.8464455604553223,0.45489624157348235,0.5334842361901936
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,15,3,2,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.7807915132229295,0.4497499465942383,0.1673498898744583,0.28309381008148193,0.0032194943632930517,0.9054685831069946,0.697291207810243,0.7528640773465882,0.7449837107407419
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.9072376066109756,0.4530244469642639,0.20702789723873138,0.5726377367973328,0.0058115217834711075,0.9157013967633247,0.8626162384947141,0.8949692641342557,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.9116318971480539,0.47325778007507324,0.18837468326091766,0.5833568572998047,0.006709013134241104,0.9789305627346039,0.784894513587157,0.9299374970061028,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.7192884382614351,0.5028549432754517,0.14797186851501465,0.06983056664466858,0.006251979153603315,0.9285783022642136,0.6165494521458944,0.9127416583146606,0.18376464906491732
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.9414321175531336,0.44176924228668213,0.2915038764476776,0.32242608070373535,0.016569411382079124,0.8805288821458817,1.0,1.0,0.8484896860624614
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.7033952318524059,0.41508862376213074,0.16504724323749542,0.0201161690056324,0.010562589392066002,0.7971519492566586,0.6876968468228977,1.0,0.05293728685692737
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.8426398285253904,0.4743870496749878,0.1499159187078476,0.32832086086273193,0.006537627428770065,0.9824595302343369,0.6246496612826984,0.9236269250241749,0.8640022654282419
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.7806650745241511,0.39060813188552856,0.1571740061044693,0.5212979316711426,0.005286953411996365,0.7206504121422768,0.6548916921019554,0.8720097730035261,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.5968226582950592,0.40812015533447266,0.13728170096874237,0.27247071266174316,0.0004832566191907972,0.775375485420227,0.5720070873697599,0.3402146311031843,0.7170281912151136
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.7410167763584936,0.3909832239151001,0.13519898056983948,0.33453497290611267,0.005780580919235945,0.7218225747346878,0.5633290857076645,0.8936719977882371,0.8803551918581912
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.9190536325552077,0.473049521446228,0.20476196706295013,0.35123834013938904,0.006544474977999926,0.9782797545194626,0.8531748627622923,0.9238821366310577,0.9243114214194448
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.9488322170723044,0.4315989315509796,0.248799666762352,0.4641268253326416,0.008127662353217602,0.8487466610968113,1.0,0.976832874973044,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.8799134305683936,0.4651832580566406,0.1976875215768814,0.3536776900291443,0.004412890411913395,0.953697681427002,0.8236980065703392,0.8283404387360108,0.9307307632345903
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.8113368996941543,0.46745967864990234,0.13910476863384247,0.37097805738449097,0.004107636399567127,0.9608114957809448,0.5796032026410103,0.8110951332210748,0.9762580457486604
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.5545529907275188,0.31655794382095337,0.12142748385667801,0.015188761055469513,0.016303734853863716,0.4892435744404794,0.5059478494028251,1.0,0.03997042383018293
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.868531068767372,0.4173423647880554,0.21599550545215607,0.27177149057388306,0.011116456240415573,0.8041948899626732,0.899981272717317,1.0,0.715188133089166
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.6307223916339769,0.4268700182437897,0.13489581644535065,0.025649476796388626,0.004040693864226341,0.8339688070118427,0.5620659018556278,0.8071487420059084,0.06749862314839113
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0001.png,1,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0001.png,0.7902129892781813,0.4355955123901367,0.1367034614086151,0.35813868045806885,0.005427463911473751,0.8612359762191772,0.5695977558692297,0.8783693515675809,0.9424702117317602
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.6304812259510906,0.33236002922058105,0.18878239393234253,0.058813244104385376,0.004608551971614361,0.5386250913143158,0.7865933080514272,0.8387998075585464,0.15477169501154045
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.8425815588958561,0.4546288251876831,0.17951244115829468,0.2576083838939667,0.007623513229191303,0.9207150787115097,0.7479685048262279,0.9611558555055605,0.677916799720965
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.8772944478550168,0.4919036030769348,0.17881891131401062,0.3103680908679962,0.007893288508057594,0.9628012403845787,0.745078797141711,0.969666866070631,0.8167581338631479
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.9044754948467016,0.495199054479599,0.17497968673706055,0.4956547021865845,0.012232928536832333,0.9525029547512531,0.7290820280710857,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.9809664762009381,0.4803164303302765,0.2304077297449112,0.3651939034461975,0.00880263838917017,0.999011155217886,0.9600322072704633,0.996391917007948,0.9610365880163092
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.7071087435499203,0.4330425262451172,0.16347913444042206,0.06416179239749908,0.005596732720732689,0.8532578945159912,0.6811630601684253,0.8858217353191722,0.1688468220986818
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.8555049569674948,0.449088990688324,0.2006777971982956,0.3323103189468384,0.0040863435715436935,0.9034030959010124,0.8361574883262317,0.8098466231970156,0.8745008393337852
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.7415669932961465,0.2989102005958557,0.16907094419002533,0.5158606767654419,0.012127527967095375,0.4340943768620492,0.7044622674584389,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.8859900348173476,0.45077216625213623,0.19072438776493073,0.5155342817306519,0.005931638181209564,0.9086630195379257,0.7946849490205448,0.8999425769992261,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.7654749847596892,0.40607333183288574,0.1474865823984146,0.5101568698883057,0.003949855454266071,0.7689791619777679,0.6145274266600609,0.8016920326733621,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.5673722327183176,0.5984125137329102,0.151397243142128,0.020615320652723312,0.0028502552304416895,0.6299608945846558,0.6308218464255333,0.7239991353672698,0.054250843822956085
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.7141013479144596,0.46762901544570923,0.1497366726398468,0.06541077792644501,0.0048440187238156796,0.9613406732678413,0.6239028026660284,0.8508330448638606,0.17213362612222372
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.7457764393807502,0.37381619215011597,0.1717122197151184,0.32549604773521423,0.004068453796207905,0.6681756004691124,0.7154675821463268,0.8087928103815037,0.8565685466716164
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.7084868128476377,0.5493718385696411,0.17679990828037262,0.014074400067329407,0.008502026088535786,0.7832130044698715,0.7366662845015526,0.9878693676764269,0.037037894914024753
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.8427606736554911,0.4617164433002472,0.18360716104507446,0.20366114377975464,0.009909335523843765,0.9428638853132725,0.7650298376878103,1.0,0.5359503783677754
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0002.png,2,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0002.png,0.9178483268540156,0.536697268486023,0.22056271135807037,0.36808985471725464,0.014156797900795937,0.8228210359811783,0.9190112973252933,1.0,0.968657512413828
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.9536914945433015,0.498268723487854,0.30504122376441956,0.3060733377933502,0.009919430129230022,0.9429102391004562,1.0,1.0,0.8054561520877638
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.7266573437739036,0.5359104871749878,0.10346105694770813,0.36362937092781067,0.004349157214164734,0.8252797275781631,0.43108773728211724,0.8248367789562083,0.9569193971784491
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.7061203039577924,0.5266486406326294,0.10883384943008423,0.32638436555862427,0.0030483838636428118,0.8542229980230331,0.45347437262535095,0.7399006359605439,0.8589062251542744
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.7895840741209501,0.5018264055252075,0.20512638986110687,0.03487221151590347,0.007571837864816189,0.9317924827337265,0.8546932910879453,0.9594919812937365,0.09176897767343019
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.9323930676415157,0.49939748644828796,0.20283041894435883,0.4333275854587555,0.008512135595083237,0.9393828548491001,0.8451267456014951,0.9881607500253486,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.8487480713247222,0.4462805986404419,0.18289321660995483,0.3283664882183075,0.005658821202814579,0.8946268707513809,0.7620550692081451,0.8885005548974988,0.8641223374165986
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.7565190136365337,0.5335605144500732,0.13098092377185822,0.3108885884284973,0.005489956587553024,0.8326233923435211,0.5457538490494093,0.8811466463033072,0.8181278642855192
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.8773888449712125,0.4858204126358032,0.18043741583824158,0.3711032271385193,0.004694167524576187,0.9818112105131149,0.7518225659926733,0.8432423841749788,0.9765874398382086
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.911135788358636,0.46730929613113403,0.20176656544208527,0.3590331971645355,0.006346751004457474,0.9603415504097939,0.8406940226753553,0.9164059438936246,0.9448242030645672
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.8144658939226678,0.5640316009521484,0.17852573096752167,0.30422383546829224,0.009316966868937016,0.7374012470245361,0.7438572123646736,1.0,0.8005890407060322
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.7078882067920497,0.35600370168685913,0.12722991406917572,0.35334473848342896,0.0059937662445008755,0.6125115677714348,0.5301246419548988,0.9024766305227635,0.929854574956392
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.8690387486617965,0.47725147008895874,0.1504698097705841,0.6051380634307861,0.006824813317507505,0.9914108440279961,0.6269575407107671,0.9341129329606703,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.7498135830352671,0.5311260223388672,0.14735093712806702,0.2371155023574829,0.005460228770971298,0.84023118019104,0.6139622380336126,0.8798293318123019,0.6239881640986392
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.8355375508359855,0.409909188747406,0.19638465344905853,0.4088955521583557,0.004317310638725758,0.7809662148356438,0.8182693893710773,0.8230674782958767,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.6865378049167581,0.5553699135780334,0.14904765784740448,0.24349263310432434,0.002564128255471587,0.7644690200686455,0.6210319076975187,0.6990880540776496,0.640770087116643
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0003.png,3,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0003.png,0.7776005223325867,0.3858782649040222,0.15233322978019714,0.36954575777053833,0.00639363843947649,0.7058695778250694,0.6347217907508215,0.9181991452963226,0.9724888362382588
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.751717228955762,0.4057711362838745,0.15115566551685333,0.2785658836364746,0.005684683099389076,0.7680348008871078,0.6298152729868889,0.8896079582745552,0.733068114832828
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.8777861785151743,0.4648604989051819,0.16930532455444336,0.40875375270843506,0.006477939430624247,0.9526890590786934,0.7054388523101807,0.921391220394048,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.8876508531209669,0.5201554894447327,0.20319196581840515,0.30731022357940674,0.011419958434998989,0.8745140954852104,0.8466331909100215,1.0,0.8087111146826493
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.7079242838738254,0.46224045753479004,0.14711743593215942,0.3013780117034912,0.0010017311433330178,0.9445014297962189,0.6129893163839977,0.48684822159984514,0.7931000307986611
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.7192835657353446,0.3992374539375305,0.16077767312526703,0.3582368791103363,0.0017490917816758156,0.7476170435547829,0.6699069713552793,0.6104682675066675,0.9427286292377272
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.8414871148192152,0.46537327766418457,0.15654537081718445,0.39580249786376953,0.004594666883349419,0.9542914927005768,0.6522723784049352,0.8380718139502463,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.7882313431032064,0.3851439952850342,0.1550694853067398,0.4065999686717987,0.006801780313253403,0.7035749852657318,0.6461228554447492,0.9332879635602486,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.7816518509291351,0.47819840908050537,0.19116143882274628,0.12679964303970337,0.003567876061424613,0.9943700283765793,0.7965059950947762,0.7773462128566458,0.3336832711571141
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.8471137948138149,0.4735890030860901,0.2496320754289627,0.007914397865533829,0.013905524276196957,0.9799656346440315,1.0,1.0,0.02082736280403639
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.9088907594743527,0.5216933488845825,0.20587143301963806,0.35628542304039,0.010535245761275291,0.8697082847356796,0.8577976375818253,1.0,0.9375932185273421
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.9232369151554609,0.4883054494857788,0.18905481696128845,0.366585373878479,0.00988788716495037,0.9740454703569412,0.7877284040053686,1.0,0.9646983523117868
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.7969719933448098,0.3662157654762268,0.19133475422859192,0.4213753938674927,0.004987785592675209,0.6444242671132088,0.797228142619133,0.8579050817004292,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.5753192979551361,0.5942530632019043,0.14895622432231903,0.021611548960208893,0.0031919418834149837,0.6429591774940491,0.6206509346763294,0.7508215588578657,0.05687249726370761
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.8111403674137487,0.4501085877418518,0.25330835580825806,0.029312465339899063,0.00619141198694706,0.9065893366932869,1.0,0.9103714256126844,0.0771380666839449
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.8729110772931653,0.4482382833957672,0.18137820065021515,0.46612393856048584,0.00602794298902154,0.9007446356117725,0.7557425027092298,0.9038597431874587,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0004.png,4,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0004.png,0.5888805252214239,0.6784073710441589,0.1568884402513504,0.10217706114053726,0.00739689264446497,0.3799769654870033,0.6537018343806267,0.9537753392436912,0.2688870030014138
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.7075234999925205,0.32262033224105835,0.15193438529968262,0.5581142902374268,0.00504356250166893,0.5081885382533073,0.6330599387486776,0.8605958275677,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.7701049625045512,0.5432980060577393,0.14001405239105225,0.36417579650878906,0.00468368548899889,0.8021937310695648,0.5833918849627178,0.8427026952392723,0.9583573592336554
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.8785445677214547,0.4341217279434204,0.19101892411708832,0.3363805413246155,0.011151997372508049,0.8566303998231888,0.7959121838212013,1.0,0.8852119508542512
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.6503917992804622,0.3763148784637451,0.11481962352991104,0.3270104229450226,0.002573625883087516,0.6759839951992035,0.478415098041296,0.6999560384779507,0.8605537445921647
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.8383769623150951,0.39000558853149414,0.189178004860878,0.34522801637649536,0.014195497147738934,0.7187674641609192,0.788241686920325,1.0,0.9084947799381456
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.7800974337479498,0.5595617294311523,0.18316693603992462,0.30911609530448914,0.004172032233327627,0.7513695955276489,0.7631955668330193,0.8148334949413831,0.8134634086960241
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.7971830388100948,0.46023017168045044,0.1789522022008896,0.19412867724895477,0.005064303055405617,0.9382192865014076,0.74563417583704,0.8615890363569451,0.5108649401288283
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.8397108393533159,0.48148584365844727,0.13454072177410126,0.3850395977497101,0.005734128877520561,0.9953567385673523,0.5605863407254219,0.8917116622619345,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.811642204952828,0.4740508794784546,0.15674322843551636,0.24152350425720215,0.0060266852378845215,0.9814089983701706,0.6530967851479849,0.9038089781307855,0.6355881690979004
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.888365919652738,0.49271297454833984,0.20480704307556152,0.23883134126663208,0.01040099747478962,0.960271954536438,0.8533626794815063,1.0,0.6285035296490318
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.726495551012229,0.5586234927177429,0.13965901732444763,0.34385189414024353,0.003311986569315195,0.7543015852570534,0.5819125721851985,0.759601171738882,0.9048734056322199
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.8400304105193177,0.4717482924461365,0.1704636961221695,0.2562922239303589,0.006823756266385317,0.9742134138941765,0.7102654005090396,0.934075132271792,0.6744532208693654
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.9148354340344668,0.4920879900455475,0.180934339761734,0.42669612169265747,0.009165910072624683,0.9622250311076641,0.7538930823405584,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.8263135050336518,0.327253133058548,0.30818116664886475,0.30674052238464355,0.008707558736205101,0.5226660408079624,1.0,0.9937276305577201,0.8072119010122198
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.890989962494687,0.4554205536842346,0.2528993785381317,0.1622174233198166,0.015306985005736351,0.9231892302632332,1.0,1.0,0.4268879561047805
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0005.png,5,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0005.png,0.7909312176123338,0.5113800764083862,0.12112748622894287,0.3675304651260376,0.005823063664138317,0.901937261223793,0.504697859287262,0.8954514651107465,0.9671854345422042
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.8884573838428447,0.44965916872024536,0.20923547446727753,0.26690584421157837,0.018853653222322464,0.9051849022507668,0.8718144769469898,1.0,0.7023838005567852
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.5424075909532144,0.5810010433197021,0.11326755583286285,0.01616492122411728,0.003269416745752096,0.6843717396259308,0.47194814930359524,0.7565229372698733,0.042539266379255994
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.9199470886522805,0.4832928776741028,0.1857834905385971,0.4970867931842804,0.0076880743727087975,0.9897097572684288,0.7740978772441547,0.9632191931940217,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.79763440980382,0.49713900685310364,0.1525484025478363,0.28422439098358154,0.00469512352719903,0.9464406035840511,0.6356183439493179,0.8432915479906348,0.747958923641004
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.8936389699578285,0.5909118056297302,0.23809503018856049,0.38532236218452454,0.015070254914462566,0.653400607407093,0.9920626257856687,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.8748202401360399,0.48604580760002136,0.1775204986333847,0.27508848905563354,0.00958376843482256,0.9811068512499332,0.7396687443057697,1.0,0.7239170764621935
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.8148307377442228,0.48512446880340576,0.1678411066532135,0.4708274006843567,0.001983568537980318,0.983986034989357,0.6993379443883896,0.6393341757235952,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.797819862632375,0.5439020395278931,0.17033889889717102,0.2401711493730545,0.011211000382900238,0.8003061264753342,0.709745412071546,1.0,0.6320293404554066
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.8381420406071763,0.38817107677459717,0.19225603342056274,0.33924275636672974,0.009868860244750977,0.7130346149206161,0.8010668059190115,1.0,0.8927440957019204
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.8582291157476377,0.43478697538375854,0.16556254029273987,0.4932303726673126,0.008055641315877438,0.8587092980742455,0.6898439178864162,0.9746526038377571,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.8232310895245083,0.4738370180130005,0.12807868421077728,0.3554766774177551,0.006293745711445808,0.9807406812906265,0.533661184211572,0.9143631551515713,0.9354649405730397
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.8282308311292355,0.48941248655319214,0.15173371136188507,0.4112844169139862,0.003754726145416498,0.9705859795212746,0.6322237973411878,0.7895515922819869,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.8399940205578029,0.5373072028160095,0.18343955278396606,0.3080950975418091,0.007943334989249706,0.8209149911999702,0.764331469933192,0.9712143853843498,0.8107765724784449
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.6663175725832784,0.37575361132621765,0.13051962852478027,0.5184023380279541,0.001697147381491959,0.6742300353944302,0.5438317855199178,0.6035961052358961,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.6062260132684663,0.2930038571357727,0.10691956430673599,0.3616059422492981,0.00427300576120615,0.4156370535492898,0.4454981846114,0.8205850163610929,0.9515945848665739
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0006.png,6,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0006.png,0.8229765754788053,0.4177233874797821,0.15528073906898499,0.42389506101608276,0.0072549739852547646,0.8053855858743191,0.6470030794541042,0.9490399035211134,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.7181384994452124,0.31943070888519287,0.14263805747032166,0.40797895193099976,0.007634199224412441,0.49822096526622783,0.5943252394596736,0.9614985521097674,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.8478331998343883,0.5331958532333374,0.180244579911232,0.53031986951828,0.005684364587068558,0.8337629586458206,0.7510190829634666,0.8895943494064086,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.9324784831090485,0.4094802737236023,0.2649616003036499,0.38844987750053406,0.008730137720704079,0.7796258553862572,1.0,0.9943629059726856,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.6096716730115982,0.2992134690284729,0.11796226352453232,0.3512931764125824,0.003491076175123453,0.4350420907139779,0.49150943135221803,0.7721514291260382,0.9244557274015326
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.8223307981891066,0.42776134610176086,0.29406997561454773,0.05397149175405502,0.014682739041745663,0.8367542065680027,1.0,1.0,0.14203024145803952
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.9140250849488534,0.5122768878936768,0.2016274780035019,0.36036747694015503,0.011847620829939842,0.8991347253322601,0.840114491681258,1.0,0.9483354656319869
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.9180771350860596,0.48781657218933105,0.18032413721084595,0.4911941885948181,0.00930072646588087,0.9755732119083405,0.7513505717118582,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.9374442373713449,0.48250946402549744,0.21537818014621735,0.5147197842597961,0.005516034550964832,0.9921579249203205,0.8974090839425723,0.8822965388499081,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.7860941951616304,0.38020795583724976,0.17712736129760742,0.34638020396232605,0.005601859651505947,0.6881498619914055,0.7380306720733643,0.886044028249336,0.9115268525324369
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.868548129333967,0.40274500846862793,0.21631170809268951,0.31362342834472656,0.008476955816149712,0.7585781514644623,0.9012987837195396,0.9871453082549713,0.8253248114334909
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.9170337303688652,0.543903648853302,0.2270985096693039,0.362444669008255,0.012053943239152431,0.8003010973334312,0.9462437902887663,1.0,0.9538017605480394
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.765771490363299,0.4606860280036926,0.1381261646747589,0.33797234296798706,0.002700167940929532,0.9396438375115395,0.5755256861448288,0.7112419915371537,0.8894009025473344
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.8089450322475654,0.429851233959198,0.16050851345062256,0.3250102698802948,0.006134443450719118,0.8432851061224937,0.6687854727109274,0.9081213240528488,0.8552901838955126
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.7632670428910165,0.4325971007347107,0.1387975960969925,0.3940131366252899,0.003009276930242777,0.8518659397959709,0.5783233170708021,0.7368410633239384,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.6310432369302732,0.2640632390975952,0.15765050053596497,0.2662172019481659,0.006583734415471554,0.32519762217998516,0.6568770855665207,0.9253403479808132,0.7005715840741208
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0007.png,7,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0007.png,0.6948630072001871,0.33744144439697266,0.13102002441883087,0.5216690301895142,0.0050093019381165504,0.5545045137405396,0.5459167684117954,0.8589464902179466,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.8578294727559153,0.3566327393054962,0.24090887606143951,0.31283190846443176,0.010827157646417618,0.6144773103296757,1.0,1.0,0.8232418643800836
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.9062446802854538,0.41842663288116455,0.21117576956748962,0.5985947847366333,0.014399413019418716,0.8075832277536392,0.8798990398645401,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.830003917554375,0.4168418049812317,0.1585189402103424,0.43012213706970215,0.007720976136624813,0.802630640566349,0.6604955842097601,0.9642642004861689,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.7277176810031172,0.5425536632537842,0.20449933409690857,0.04221971705555916,0.004954543896019459,0.8045198023319244,0.8520805587371191,0.8562875795892602,0.11110451856726095
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.8718254566192627,0.4160996079444885,0.18538565933704376,0.40254637598991394,0.012268205173313618,0.8003112748265266,0.7724402472376823,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.7404042784705271,0.44251206517219543,0.13541799783706665,0.31520071625709534,0.0028918397147208452,0.8828502036631107,0.5642416576544445,0.7274215388424707,0.8294755690976193
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.7926763694929448,0.35941803455352783,0.18378563225269318,0.31917446851730347,0.008972741663455963,0.6231813579797745,0.7657734677195549,1.0,0.8399328118876407
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.8511700443923473,0.42353320121765137,0.16328613460063934,0.54993736743927,0.009047940373420715,0.8235412538051605,0.6803588941693306,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.9835371665656567,0.483590304851532,0.2652520537376404,0.346821129322052,0.009857337921857834,0.9887802973389626,1.0,1.0,0.9126871824264526
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.8313710134730616,0.35413259267807007,0.2063194364309311,0.535241961479187,0.007772427052259445,0.606664352118969,0.8596643184622129,0.9658896491948282,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.8246953509217139,0.422816663980484,0.19060008227825165,0.4336584806442261,0.0033205871004611254,0.8213020749390125,0.7941670094927152,0.7602185023687822,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.7477972348932284,0.43886902928352356,0.11274916678667068,0.3504166603088379,0.004413885995745659,0.8714657165110111,0.4697881949444612,0.8283947821808131,0.9221491060758892
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.7676579830016416,0.3923119306564331,0.1518050581216812,0.44908827543258667,0.004639924503862858,0.7259747833013535,0.6325210755070051,0.8404369014365359,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.7482811951208406,0.4355027973651886,0.1117275282740593,0.44914543628692627,0.003944254480302334,0.8609462417662144,0.4655313678085804,0.8013516489936086,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.9661234380884615,0.47174549102783203,0.2849469780921936,0.42810940742492676,0.005822984501719475,0.9742046594619751,1.0,0.8954481609994762,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.8949746314436198,0.3679729402065277,0.27674049139022827,0.4891512989997864,0.010152001865208149,0.6499154381453991,1.0,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.8200183843348151,0.4506993293762207,0.1702098548412323,0.38663724064826965,0.003035563975572586,0.9084354043006897,0.7092077285051346,0.7389017779722711,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.7428060335911393,0.3004440665245056,0.1944645643234253,0.32973453402519226,0.007331442553550005,0.43888770788908016,0.8102690180142721,0.9516025885039153,0.8677224579610322
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.9174913689494133,0.46987205743789673,0.1815890520811081,0.41412973403930664,0.012643668800592422,0.9683501794934273,0.7566210503379505,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.8970126920280906,0.4145393967628479,0.21817629039287567,0.6078044772148132,0.007067584432661533,0.7954356148838997,0.909067876636982,0.9426465782873044,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.8587507868744532,0.38062766194343567,0.20873036980628967,0.4191056787967682,0.0077125681564211845,0.6894614435732365,0.8697098741928737,0.9639975661784804,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.7221774383361201,0.4957490563392639,0.13767169415950775,0.28004205226898193,0.0018016818212345243,0.9507841989398003,0.573632058997949,0.6172385823418417,0.7369527691288998
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.7535079380139714,0.33035600185394287,0.20295388996601105,0.296772837638855,0.005737125873565674,0.5323625057935715,0.8456412081917127,0.8918386042648266,0.7809811516811973
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.9408562304132185,0.46214669942855835,0.23004117608070374,0.33930355310440063,0.007119272835552692,0.9442084357142448,0.9585049003362656,0.9444264661221557,0.8929040871168438
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.9571427084505558,0.4932240843772888,0.21563223004341125,0.4287053942680359,0.01311987079679966,0.9586747363209724,0.8984676251808803,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.7850668812464726,0.37262359261512756,0.15030664205551147,0.3745507001876831,0.01575438305735588,0.6644487269222736,0.6262776752312978,1.0,0.9856597373360082
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.8073081995703673,0.5828477144241333,0.17797638475894928,0.33251887559890747,0.010230002924799919,0.6786008924245834,0.7415682698289554,1.0,0.8750496726287038
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.6022668950316687,0.5781677961349487,0.128550186753273,0.07408773899078369,0.004217946901917458,0.6932256370782852,0.5356257781386375,0.8174652413546036,0.19496773418627286
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.8587818834930658,0.3847428858280182,0.19846834242343903,0.5150179266929626,0.009994670748710632,0.7023215182125568,0.8269514267643293,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.9715768993578436,0.46528637409210205,0.23166707158088684,0.4172598123550415,0.008339861407876015,0.9540199190378189,0.9652794649203619,0.9831483366815578,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.6447668988382608,0.5440042614936829,0.15740476548671722,0.06123896688222885,0.0029906013514846563,0.7999866828322411,0.6558531895279884,0.7353666429172484,0.1611551760058654
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0009.png,9,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0009.png,0.6264041364138251,0.3067668080329895,0.11905036866664886,0.41130155324935913,0.0033173896372318268,0.4586462751030923,0.49604320277770364,0.7599891721983453,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.9316919521281594,0.46314090490341187,0.2222105711698532,0.30332648754119873,0.018684761598706245,0.9473153278231621,0.9258773798743885,1.0,0.7982275987926283
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.8362612498826102,0.4938051700592041,0.22587327659130096,0.04271706938743591,0.015329504385590553,0.9568588435649872,0.941138652463754,1.0,0.1124133404932524
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.7165602362825156,0.44519293308258057,0.2061324268579483,0.016990389674901962,0.0030403914861381054,0.8912279158830643,0.858885111908118,0.7392783807150094,0.0447115517760578
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.7544185508750695,0.38513433933258057,0.18245159089565277,0.3918326199054718,0.0021797525696456432,0.7035448104143143,0.7602149620652199,0.661162476524837,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.6353039675322418,0.38145485520362854,0.1089044138789177,0.33215081691741943,0.0020047901198267937,0.6920464225113392,0.45376839116215706,0.6417894354301092,0.8740810971511037
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.7871885440680236,0.3831210136413574,0.15443271398544312,0.5156314373016357,0.006988164037466049,0.6972531676292419,0.643469641606013,0.9398868051897886,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.6827521596496043,0.2784041464328766,0.15173983573913574,0.33458614349365234,0.009204437956213951,0.37001295760273945,0.6322493155797323,1.0,0.8804898512990851
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.7846924976592785,0.4086574912071228,0.23411597311496735,0.02262553758919239,0.013685686513781548,0.7770546600222588,0.975483221312364,1.0,0.059540888392611555
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.9533158849336598,0.462105929851532,0.23926198482513428,0.30656903982162476,0.016961678862571716,0.9440810307860374,0.9969249367713928,1.0,0.8067606311095388
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.9361020717769861,0.4754411280155182,0.19230081140995026,0.3937605917453766,0.011753564700484276,0.9857535250484943,0.8012533808747928,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.8594096478365186,0.36091628670692444,0.24943320453166962,0.44628000259399414,0.005559524521231651,0.6278633959591389,1.0,0.8842025161951075,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.8705840738196122,0.5035823583602905,0.21619310975074768,0.1835429072380066,0.009106960147619247,0.9263051301240921,0.9008046239614487,1.0,0.4830076506263331
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.8898332814907813,0.49297034740448,0.17341305315494537,0.3887375295162201,0.007017411291599274,0.9594676643610001,0.7225543881456058,0.9409066629551981,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.7507977860676607,0.4421009421348572,0.16425229609012604,0.3041188418865204,0.002022879896685481,0.8815654441714287,0.6843845670421919,0.6438634857303186,0.8003127418066326
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.861679406269971,0.45241543650627136,0.17910058796405792,0.38011497259140015,0.004921246320009232,0.913798239082098,0.7462524498502414,0.8546567983610766,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0010.png,10,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0010.png,0.851069178362064,0.395182728767395,0.23430998623371124,0.3024459183216095,0.0053139738738536835,0.7349460273981094,0.9762916093071302,0.8732453625783748,0.7959103113726566
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.8150182591137793,0.4300612807273865,0.2012411504983902,0.23933394253253937,0.005098999477922916,0.8439415022730827,0.8385047937432926,0.8632417824998787,0.6298261645593142
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.567511856040738,0.2784450650215149,0.12670008838176727,0.2576598823070526,0.0036924059968441725,0.37014082819223415,0.5279170349240303,0.7855465953070356,0.6780523218606648
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.6365915862482319,0.5922831296920776,0.08095132559537888,0.3849925994873047,0.0033549717627465725,0.6491152197122574,0.3372971899807453,0.762671453361324,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.9557315949350595,0.4665307104587555,0.21468724310398102,0.3871467709541321,0.01106947846710682,0.9579084701836109,0.894530179599921,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.6630120269093387,0.5909801125526428,0.1772090196609497,0.019194001331925392,0.007339530624449253,0.6531871482729912,0.7383709152539571,0.9518721135125032,0.05051052982085629
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.759279356697286,0.41999003291130066,0.19927017390727997,0.07469053566455841,0.0072203692980110645,0.8124688528478146,0.8302923912803333,0.9478715091018534,0.19655404122252212
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.8259643635075342,0.44743263721466064,0.24041514098644257,0.0164572075009346,0.011462138034403324,0.8982269912958145,1.0,1.0,0.04330844079193316
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.9654331909590645,0.5166597962379456,0.2601720690727234,0.379497766494751,0.009406311437487602,0.8854381367564201,1.0,1.0,0.9986783328809236
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.8087891925676537,0.41896116733551025,0.19532984495162964,0.22636893391609192,0.006710141897201538,0.8092536479234695,0.8138743539651235,0.9299785355052104,0.5957077208318209
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.8723431497812272,0.6161673069000244,0.25088974833488464,0.44107890129089355,0.015555943362414837,0.5744771659374237,1.0,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.902430422800152,0.49903982877731323,0.2022586166858673,0.2975577116012573,0.012624170631170273,0.9405005350708961,0.8427442361911138,1.0,0.7830466094769929
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.8566085423686003,0.5279251337051392,0.19167496263980865,0.2835931181907654,0.009432444348931313,0.8502339571714401,0.7986456776658695,1.0,0.7462976794493825
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.9167166218161583,0.5052434802055359,0.19230590760707855,0.4406413435935974,0.010759645141661167,0.9211141243577003,0.801274615029494,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.7332594111351545,0.35893142223358154,0.15458421409130096,0.3551349639892578,0.004895415157079697,0.6216606944799423,0.6441008920470874,0.8533843238830381,0.9345656947085732
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.8619380719959736,0.5050806999206543,0.1483609825372696,0.4822181761264801,0.009327592328190804,0.9216228127479553,0.6181707605719566,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0011.png,11,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0011.png,0.763304197082394,0.6085044145584106,0.1783471703529358,0.28080257773399353,0.014795580878853798,0.5984237045049667,0.7431132098038992,1.0,0.7389541519315619
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.7158460548313181,0.397758424282074,0.1910116821527481,0.027980558574199677,0.007986839860677719,0.7429950758814812,0.7958820089697838,0.9725518881760709,0.07363304887947283
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.9387205943465232,0.4146353006362915,0.2460840493440628,0.48197445273399353,0.016116084530949593,0.795735314488411,1.0,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.7778074048745092,0.5069218873977661,0.12979258596897125,0.32808905839920044,0.004732152447104454,0.9158691018819809,0.5408024415373802,0.8451884120276448,0.8633922589452643
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.7244336965262637,0.40517404675483704,0.2190302014350891,0.019041884690523148,0.004889964126050472,0.7661688961088657,0.9126258393128713,0.8531149698770916,0.05011022286979776
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.8636746160262206,0.47610896825790405,0.14643068611621857,0.7238438129425049,0.0069098807871341705,0.9878405258059502,0.6101278588175774,0.9371364025566497,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.8681429023413282,0.47012829780578613,0.15831895172595978,0.32806396484375,0.009349946863949299,0.9691509306430817,0.6596622988581657,1.0,0.8633262232730263
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.7536923471477148,0.5303459167480469,0.11438284069299698,0.4298040270805359,0.0044739628210663795,0.8426690101623535,0.4765951695541541,0.8316523729310502,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.7794650786113853,0.48692944645881653,0.19055089354515076,0.06873984634876251,0.005521905142813921,0.9783454798161983,0.7939620564381282,0.8825546714423036,0.18089433249674344
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.8002301176699335,0.4839397370815277,0.13295488059520721,0.2905888855457306,0.0057431962341070175,0.9876883216202259,0.5539786691466968,0.8920955256345889,0.7647075935413963
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.6416018173452989,0.3573581278324127,0.0971079096198082,0.45106086134910583,0.003059644717723131,0.6167441494762897,0.4046162900825342,0.7407747419106067,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.7302155502281252,0.40242958068847656,0.20257100462913513,0.08602330088615417,0.00509538222104311,0.7575924396514893,0.8440458526213964,0.8630699856279528,0.22637710759514257
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.8919718374170396,0.4909346401691437,0.1829661875963211,0.3153865933418274,0.008791543543338776,0.965829249471426,0.7623591149846713,0.9960824807284825,0.8299647193205983
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.6881742365541984,0.5913218259811401,0.10964275151491165,0.4025637209415436,0.004297134466469288,0.6521192938089371,0.45684479797879857,0.8219400360715108,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.9243399069958896,0.4931982755661011,0.22578468918800354,0.4697073698043823,0.004226100631058216,0.9587553888559341,0.9407695382833481,0.8179297154164198,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.7163034117498465,0.45544472336769104,0.16119147837162018,0.026964709162712097,0.006150629371404648,0.9232647605240345,0.6716311598817508,0.9087626859397405,0.07095976095450551
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0012.png,12,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0012.png,0.7900618837822942,0.5382877588272095,0.15630966424942017,0.48000404238700867,0.003877816488966346,0.8178507536649704,0.6512902677059174,0.7972783094841118,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.843622784695209,0.4460427165031433,0.19060862064361572,0.4360131621360779,0.003164730966091156,0.8938834890723228,0.7942025860150655,0.7487878486759701,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.8530858941376209,0.592255175113678,0.2125052809715271,0.36149024963378906,0.011180900037288666,0.6492025777697563,0.8854386707146963,1.0,0.9512901306152344
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.7295526614400535,0.30937492847442627,0.16713692247867584,0.4565824270248413,0.006504006218165159,0.4667966514825822,0.6964038436611494,0.922370051587736,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.8402884434908628,0.34234514832496643,0.21547189354896545,0.5588728189468384,0.011818223632872105,0.5698285885155201,0.8977995564540228,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.8848915930837393,0.3572176992893219,0.2689514458179474,0.4199599027633667,0.009353730827569962,0.6163053102791309,1.0,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.9490443464956785,0.46286529302597046,0.23512785136699677,0.30703574419021606,0.01412055641412735,0.9464540407061577,0.9796993806958199,1.0,0.8079888005005685
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.7436631292051705,0.5985981225967407,0.2016238123178482,0.18397708237171173,0.006461880635470152,0.6293808668851852,0.8400992179910343,0.9207862849086214,0.48415021676766246
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.27824470352082153,0.7856162786483765,0.09011327475309372,0.013086659833788872,0.0015830990159884095,0.04494912922382355,0.3754719781378905,0.5878103381432469,0.034438578509970716
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.8600906051828257,0.5038070678710938,0.1652703583240509,0.3225787281990051,0.008715537376701832,0.925602912902832,0.6886264930168788,0.9939522996292207,0.8488913899973819
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.8061984225290415,0.5071687698364258,0.15667252242565155,0.3790510892868042,0.003112172707915306,0.9150975942611694,0.6528021767735481,0.7448122449479723,0.9975028665442216
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.7468581363673962,0.5641802549362183,0.17713198065757751,0.25274860858917236,0.004233876243233681,0.7369367033243179,0.738049919406573,0.8183718477885592,0.6651279173399273
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.7940011328063342,0.3370037078857422,0.1865503191947937,0.5364981889724731,0.008216256275773048,0.5531365871429443,0.7772929966449738,0.9794890306798354,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.8412809632718563,0.3839397430419922,0.1850699633359909,0.6466249823570251,0.009766172617673874,0.6998116970062256,0.7711248472332954,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.8293791332221887,0.3835112452507019,0.1854138821363449,0.5246545076370239,0.007351785898208618,0.6984726414084435,0.7725578422347705,0.9522799525168982,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.6318264134533996,0.3000733256340027,0.09789157658815384,0.5086930990219116,0.006247645244002342,0.4377291426062585,0.40788156911730766,0.9125727997453189,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0013.png,13,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0013.png,0.8530633766204119,0.3916539251804352,0.1887102574110031,0.4534149765968323,0.010742193087935448,0.7239185161888599,0.786292739212513,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.7805764975034436,0.49535948038101196,0.12522120773792267,0.34557345509529114,0.004057674668729305,0.9520016238093376,0.5217550322413445,0.8081557052340752,0.9094038291981346
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.8115707012395226,0.3908045291900635,0.18456260859966278,0.44036346673965454,0.004988769069314003,0.7212641537189484,0.7690108691652616,0.8579527774970385,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.7546108777407563,0.3149700164794922,0.17627683281898499,0.4901430606842041,0.007462111301720142,0.4842813014984132,0.7344868034124374,0.9559217850700042,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.8348472186858512,0.5052899122238159,0.1425306797027588,0.4295963644981384,0.0064827632158994675,0.9209690243005753,0.5938778320948284,0.9215726470689206,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.9116570405579624,0.4579988121986389,0.19427739083766937,0.40064263343811035,0.007517970632761717,0.9312462881207466,0.8094891284902891,0.9577456622986068,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.7831956819188084,0.4145781397819519,0.18005575239658356,0.3199993968009949,0.0034972601570189,0.7955566868185997,0.7502323016524315,0.7725737360347411,0.8421036757920918
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.8497177962522485,0.528252363204956,0.17157141864299774,0.4179542660713196,0.006493085995316505,0.8492113649845123,0.7148809110124906,0.9219604538125904,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.8477325943624341,0.5478042960166931,0.18221351504325867,0.377159059047699,0.006951847113668919,0.788111574947834,0.7592229793469112,0.9386146085365172,0.9925238395992079
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.8293601733246289,0.5703660845756531,0.22234542667865753,0.2892942428588867,0.005642659030854702,0.7176059857010841,0.9264392778277397,0.8878059936025265,0.7613006391023335
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.8754360514517048,0.47541603446006775,0.16772903501987457,0.3482781648635864,0.006721084006130695,0.9856751076877117,0.6988709792494774,0.9303760095923187,0.9165214864831221
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.8031599724763319,0.3450366258621216,0.2989216148853302,0.20187661051750183,0.016666218638420105,0.5782394558191299,1.0,1.0,0.5312542382039522
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.6114059155028135,0.29910266399383545,0.12111715227365494,0.3780674338340759,0.002819701097905636,0.4346958249807359,0.504654801140229,0.7214543309280816,0.9949142995633576
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.5813320235069901,0.279643177986145,0.13355864584445953,0.3075016736984253,0.0028423594776540995,0.3738849312067033,0.5564943576852481,0.7233439888864207,0.8092149307853297
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.8970121815800667,0.4527817368507385,0.17802344262599945,0.6306769847869873,0.00922947097569704,0.9149429276585579,0.7417643442749977,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.6383918591053747,0.40350714325904846,0.18181803822517395,0.02632799744606018,0.002464060438796878,0.7609598226845264,0.7575751592715582,0.6897549357909446,0.06928420380542152
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0014.png,14,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0014.png,0.8100685693414514,0.3897586762905121,0.17422953248023987,0.3983655273914337,0.0061195967718958855,0.7179958634078503,0.7259563853343328,0.9075315788751861,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.7531626727458968,0.36451369524002075,0.15716034173965454,0.3906942903995514,0.0050295512191951275,0.6391052976250648,0.6548347572485607,0.8599226251352363,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.8558606616787459,0.47998446226119995,0.15786714851856232,0.41584277153015137,0.004520841874182224,0.9999514445662498,0.6577797854940097,0.8341651706426719,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.7269447186931878,0.3516874313354492,0.2197750359773636,0.4817739427089691,0.0010169134475290775,0.5990232229232788,0.9157293165723484,0.4900758273779987,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.8546108287016478,0.5095452070236206,0.20612335205078125,0.2846146821975708,0.004811981692910194,0.9076712280511856,0.8588473002115886,0.8492294774214139,0.748986005783081
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.7799806835576515,0.443111777305603,0.13125254213809967,0.5569332838058472,0.003954778891056776,0.8847243040800095,0.546885592242082,0.8019908586440961,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.8395220767706633,0.4117112457752228,0.16283422708511353,0.4288371801376343,0.009580913931131363,0.7865976430475712,0.678475946187973,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.8496681485185789,0.49299055337905884,0.25172892212867737,0.04769085347652435,0.007971653714776039,0.9594045206904411,1.0,0.9720858216512737,0.12550224599085355
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.7035404018017976,0.412480890750885,0.11283215880393982,0.2936195135116577,0.004623625427484512,0.7890027835965157,0.47013399501641595,0.8395877146953706,0.7726829302938361
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.8972006485925356,0.5154476761817932,0.2248903065919876,0.334020733833313,0.0052406624890863895,0.8892260119318962,0.9370429441332817,0.8698786884077503,0.8790019311402973
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.7692721901848919,0.5759490728378296,0.16087286174297333,0.34940776228904724,0.005482954904437065,0.7001591473817825,0.6703035905957222,0.8808370083943823,0.9194941112869665
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.813525316996492,0.44119101762771606,0.13355450332164764,0.37842822074890137,0.0068312836810946465,0.8787219300866127,0.5564770971735319,0.9343441919860559,0.9958637388128984
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.9533576257526875,0.4510265588760376,0.22441618144512177,0.39836180210113525,0.00955219380557537,0.9094579964876175,0.9350674226880074,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.7707626793366871,0.527869462966919,0.17080965638160706,0.3755146265029907,0.0017887844005599618,0.8504079282283783,0.7117069015900295,0.6155950902441472,0.9881963855341861
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.7182628997854772,0.24694395065307617,0.2194398045539856,0.6423986554145813,0.004823611117899418,0.27169984579086315,0.9143325189749401,0.8498127614229448,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.789276619090148,0.34370309114456177,0.20826925337314606,0.48268985748291016,0.004386099521070719,0.5740721598267555,0.867788555721442,0.826873617702755,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0015.png,15,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0015.png,0.7051714816375783,0.38240617513656616,0.18909160792827606,0.02609632909297943,0.010261263698339462,0.6950192973017693,0.7878816997011503,1.0,0.06867455024468272
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.7801536326345644,0.45335298776626587,0.19793348014354706,0.01955316960811615,0.013701657764613628,0.9167280867695808,0.8247228339314461,1.0,0.0514557094950425
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.8445020968780705,0.4707901179790497,0.14413464069366455,0.3115190863609314,0.013069191947579384,0.9712191186845303,0.600561002890269,1.0,0.8197870693708721
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.6878062608426095,0.3866174817085266,0.19492429494857788,0.10360478609800339,0.0033624463248997927,0.7081796303391457,0.8121845622857412,0.7632015078553052,0.27264417394211415
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.6389193837510914,0.4596977233886719,0.12902195751667023,0.012631891295313835,0.003412984311580658,0.9365553855895996,0.5375914896527927,0.7667561931945783,0.0332418191981943
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.8216232769191266,0.3050840497016907,0.2284855842590332,0.3820759356021881,0.015298811718821526,0.45338765531778347,0.9520232677459717,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.7096776374076542,0.5780296921730042,0.19735117256641388,0.012391820549964905,0.012805609032511711,0.693657211959362,0.8222965523600578,1.0,0.03261005407885501
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.8407918077372092,0.620857834815979,0.24256296455860138,0.35614013671875,0.006684855557978153,0.5598192662000656,1.0,0.929057579847574,0.9372108861019737
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.8991474531989166,0.4658392667770386,0.24270987510681152,0.3388429880142212,0.00273983390070498,0.9557477086782455,1.0,0.7146773181487912,0.8916920737216347
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.5958681341978838,0.6486636400222778,0.14591249823570251,0.15401607751846313,0.004693643189966679,0.4729261249303818,0.6079687426487606,0.843215415404254,0.40530546715385035
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.8129371797175784,0.5317171812057495,0.2578273415565491,0.028935827314853668,0.00998673401772976,0.8383838087320328,1.0,1.0,0.07614691398645702
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.5651608628931603,0.6833639740943909,0.16268715262413025,0.0062209744937717915,0.012641256675124168,0.36448758095502853,0.677863135933876,1.0,0.016370985509925766
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.877409378066659,0.39324894547462463,0.2069907933473587,0.41296687722206116,0.013196568936109543,0.728902954608202,0.862461638947328,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.7032346452533137,0.39415043592453003,0.18804651498794556,0.032015345990657806,0.007109512109309435,0.7317201122641563,0.7835271457831066,0.9440913250555009,0.08425091050173107
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.7165740866450822,0.26834478974342346,0.18711236119270325,0.40012964606285095,0.006559509783983231,0.33857746794819843,0.7796348383029302,0.924441579078974,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.5664347354941224,0.2962338328361511,0.09687282145023346,0.4931526184082031,0.0022690289188176394,0.42573072761297237,0.40363675604263943,0.6704979615897552,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0016.png,16,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0016.png,0.7396954286610681,0.5592689514160156,0.17220357060432434,0.1704862117767334,0.006597068160772324,0.7522845268249512,0.7175148775180181,0.9258336739957619,0.4486479257282458
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.8442183920524334,0.48688799142837524,0.15965047478675842,0.5003736019134521,0.003995539154857397,0.9784750267863274,0.6652103116114935,0.8044511621323487,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.6410519987720096,0.4011753797531128,0.1851675808429718,0.020025700330734253,0.0025999138597398996,0.7536730617284775,0.7715315868457159,0.7023428899610052,0.05269921139666909
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.86377886967814,0.5184291005134583,0.19683726131916046,0.5097706913948059,0.004175588022917509,0.879909060895443,0.8201552554965019,0.8150382990422259,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.758978031212746,0.3221725821495056,0.17948639392852783,0.3638976812362671,0.007457105442881584,0.506789319217205,0.7478599747021993,0.9557576859851721,0.957625476937545
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.9038423381941882,0.409789115190506,0.23749284446239471,0.31109076738357544,0.014844270423054695,0.7805909849703312,0.9895535185933113,1.0,0.8186599141673038
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.9634627433234912,0.47291696071624756,0.23459888994693756,0.3239399790763855,0.0087862154468894,0.9778655022382736,0.9774953747789066,0.9959337433843193,0.8524736291483829
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.9587230589240789,0.47054538130760193,0.2140694111585617,0.4209824800491333,0.013771463185548782,0.970454316586256,0.8919558798273405,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.47707103936026096,0.37434113025665283,0.0729745477437973,0.24355140328407288,0.0005230667302384973,0.6698160320520401,0.3040606155991554,0.35507733296896815,0.6409247454844023
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.6473111374152174,0.27569398283958435,0.1519845426082611,0.2707657217979431,0.007837953045964241,0.3615436963737012,0.6332689275344213,0.9679445770796333,0.7125413731524819
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.8116120765595167,0.5236519575119019,0.14505447447299957,0.47546645998954773,0.005574851296842098,0.8635876327753067,0.6043936436374983,0.8848707745427008,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.8127743720471664,0.444951593875885,0.16335873305797577,0.45281827449798584,0.0033983970060944557,0.8904737308621407,0.6806613877415657,0.7657353458642178,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.6712224901360864,0.3072311580181122,0.13959455490112305,0.4694788157939911,0.004532766528427601,0.4600973688066007,0.5816439787546794,0.8348003434708092,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.8597688288354238,0.39560994505882263,0.20252938568592072,0.5092368125915527,0.007074663415551186,0.7362810783088207,0.843872440358003,0.9428910929415066,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.9041264336093214,0.4977225661277771,0.18159882724285126,0.46509695053100586,0.008066127076745033,0.9446169808506966,0.7566617801785469,0.9749712212021933,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.7938350441206685,0.3075231909751892,0.20913930237293243,0.4482620358467102,0.008114363066852093,0.4610099717974664,0.8714137598872185,0.9764316984610523,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0017.png,17,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0017.png,0.7612275901320376,0.4324954152107239,0.20078690350055695,0.1060132086277008,0.004862003494054079,0.8515481725335121,0.8366120979189873,0.8517287592045708,0.2789821279676337
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.6608368756922062,0.22072871029376984,0.1651599407196045,0.40084564685821533,0.008569758385419846,0.18977721966803085,0.6881664196650188,0.989815135569165,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.8468255383795813,0.33724701404571533,0.22844411432743073,0.3675900101661682,0.014804944396018982,0.5538969188928604,0.9518504763642948,1.0,0.9673421320162321
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.665890697917889,0.6605539321899414,0.16458719968795776,0.281404972076416,0.005316935013979673,0.4357689619064331,0.6857799986998241,0.8733803988233908,0.7405394002010948
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.8004285773722115,0.42226481437683105,0.13724349439144135,0.6330792307853699,0.006766077131032944,0.819577544927597,0.5718478932976723,0.9320037836185229,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.6232161501415286,0.6281447410583496,0.17022386193275452,0.027113670483231544,0.0074181510135531425,0.5370476841926575,0.7092660913864772,0.9544770112134189,0.0713517644295567
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.8030673289741919,0.41276875138282776,0.16799092292785645,0.28648263216018677,0.007971818558871746,0.7899023480713367,0.6999621788660686,0.9720908854242182,0.7539016635794389
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.9916329786181449,0.471075177192688,0.24396774172782898,0.457231342792511,0.012744851410388947,0.97210992872715,1.0,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.8295583172373873,0.39070284366607666,0.17669259011745453,0.5697683691978455,0.007892250083386898,0.7209463864564896,0.7362191254893939,0.9696346546144888,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.814958595368014,0.40864747762680054,0.1892300248146057,0.28821277618408203,0.006606536917388439,0.7770233675837517,0.7884584367275238,0.9261834117973434,0.7584546741686369
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.7675276328846306,0.40161049365997314,0.1523541361093521,0.46607843041419983,0.003959886729717255,0.7550327926874161,0.6348089004556339,0.8023004997668624,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.5200068490660519,0.256272554397583,0.07324738055467606,0.3423658013343811,0.004126410931348801,0.300851732492447,0.30519741897781694,0.812190833445605,0.9009626350904766
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.7481858869803213,0.5221759080886841,0.11329855769872665,0.4596588611602783,0.0036749073769897223,0.8682002872228622,0.4720773237446944,0.7844104147602172,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.8341397816919324,0.46161893010139465,0.21556951105594635,0.23363739252090454,0.003300016513094306,0.9425591565668583,0.8982062960664432,0.7587394375221289,0.6148352434760646
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.674450934023086,0.593754768371582,0.16519565880298615,0.15953929722309113,0.004757953807711601,0.6445163488388062,0.6883152450124423,0.8465016699607018,0.4198402558502398
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.8466502315333896,0.36832594871520996,0.2587817907333374,0.47484612464904785,0.0040110088884830475,0.6510185897350311,1.0,0.805378618451521,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.8780793850537953,0.5441845655441284,0.1914602518081665,0.3823481798171997,0.008778149262070656,0.7994232326745987,0.7977510492006938,0.9957084019648305,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.7743748755831468,0.5691772699356079,0.17154815793037415,0.2369765341281891,0.016300462186336517,0.7213210314512253,0.714783991376559,1.0,0.6236224582320765
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.8619959031812633,0.4507926404476166,0.16111496090888977,0.40773117542266846,0.007341461256146431,0.9087270013988018,0.6713123371203741,0.9519364065020419,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.7066250439198589,0.5716242790222168,0.18737395107746124,0.05050738900899887,0.0073877498507499695,0.7136741280555725,0.7807247961560886,0.953472957663865,0.1329141816026286
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.5056347468934457,0.22614547610282898,0.09118492156267166,0.549953281879425,0.0027854307554662228,0.20670461282134067,0.3799371731777986,0.7185688443748154,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.6227453587840699,0.4331698417663574,0.09616827219724655,0.3962051272392273,0.0006131107220426202,0.8536557555198669,0.400701134155194,0.38575316752620664,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.8396480940282345,0.3269829750061035,0.22648124396800995,0.4687620997428894,0.01470126025378704,0.5218217968940735,0.9436718498667082,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.7099210181013608,0.31649407744407654,0.16886259615421295,0.4748417139053345,0.004063806030899286,0.4890439920127393,0.703594150642554,0.8085183012190911,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.8099728170084275,0.35479500889778137,0.19246485829353333,0.38528430461883545,0.007197186350822449,0.6087344028055668,0.8019369095563889,0.9470856931993631,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.8545190396680131,0.47948700189590454,0.13741663098335266,0.4840865731239319,0.006791440770030022,0.9983968809247017,0.5725692957639694,0.9329167466456473,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.8397022318094969,0.34533509612083435,0.21276046335697174,0.5063046216964722,0.009771408513188362,0.5791721753776073,0.8865019306540489,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.790564654718459,0.5082401037216187,0.21723245084285736,0.013210451230406761,0.007622961420565844,0.9117496758699417,0.905135211845239,0.9611381464097138,0.034764345343175684
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.6134575094655182,0.31865814328193665,0.09847656637430191,0.4015432596206665,0.0034090199042111635,0.49580669775605213,0.4103190265595913,0.7664791686833007,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.6539911699843112,0.5120658278465271,0.14365725219249725,0.023638959974050522,0.003616808447986841,0.8997942879796028,0.5985718841354053,0.7806005997559976,0.06220778940539611
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.8337498741309814,0.38103026151657104,0.20580703020095825,0.35122478008270264,0.006508420221507549,0.6907195672392845,0.8575292925039928,0.9225354225961467,0.9242757370597438
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.888482208297846,0.53099524974823,0.19411543011665344,0.4020345211029053,0.008053380995988846,0.8406398445367813,0.8088142921527227,0.974583869163979,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0019.png,19,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0019.png,0.6482220436817949,0.37397441267967224,0.13799653947353363,0.28632599115371704,0.0020630434155464172,0.6686700396239758,0.5749855811397235,0.6484077595680293,0.7534894504045185
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,1,0,0,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.8964344077792606,0.4967292845249176,0.2178792655467987,0.22741487622261047,0.010392201133072376,0.9477209858596325,0.9078302731116613,1.0,0.5984602005858171
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,2,0,1,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.7477494503518469,0.3490465581417084,0.1692298799753189,0.2760850787162781,0.010202908888459206,0.5907704941928387,0.7051244998971622,1.0,0.7265396808323107
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,3,0,2,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.8461171741282683,0.45089292526245117,0.1624472588300705,0.3305509686470032,0.00757088977843523,0.9090403914451599,0.6768635784586271,0.9594613505543131,0.8698709701236925
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,4,0,3,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.8527149935240242,0.43802428245544434,0.2156882882118225,0.26951342821121216,0.005120911635458469,0.8688258826732635,0.8987012008825939,0.8642799556008389,0.7092458637137162
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,5,1,0,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.782702446741304,0.34150466322898865,0.20672714710235596,0.6069340705871582,0.004201602190732956,0.5672020725905895,0.8613631129264832,0.8165315643447286,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,6,1,1,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.6019026508833238,0.4371374249458313,0.12076646089553833,0.006374691613018513,0.003241011407226324,0.8660544529557228,0.503193587064743,0.754447652961865,0.01677550424478556
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.9943782195448875,0.4740034341812134,0.24226152896881104,0.5552682280540466,0.011902406811714172,0.9812607318162918,1.0,1.0,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,8,1,3,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.8351591751228237,0.4067757725715637,0.22853095829486847,0.24988508224487305,0.005419593304395676,0.7711742892861366,0.9522123262286186,0.8780173688553681,0.6575923216970343
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.7196681389088123,0.3361770510673523,0.1668766885995865,0.4398764967918396,0.00366286002099514,0.5505532845854759,0.6953195358316104,0.7836251711347457,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,10,2,1,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.8628471709974193,0.4437311291694641,0.21354557573795319,0.3641795516014099,0.0031100288033485413,0.8866597786545753,0.8897732322414716,0.7446487262806156,0.9583672410563419
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,11,2,2,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.5654179924064291,0.41548284888267517,0.06326419860124588,0.41734370589256287,0.0006179199554026127,0.7983839027583599,0.2636008275051912,0.38729029330945514,1.0
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,12,2,3,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.5551017851929729,0.2972780466079712,0.1138349249958992,0.20973512530326843,0.004009346477687359,0.4289938956499101,0.47431218748291337,0.8052791168494484,0.551934540271759
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,13,3,0,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.7427720903309117,0.49463269114494324,0.18332000076770782,0.007203459739685059,0.005884123034775257,0.9542728401720524,0.7638333365321159,0.8979870654791423,0.018956472999171206
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,14,3,1,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.9437301296936838,0.428253710269928,0.2368381768465042,0.37035953998565674,0.0142231285572052,0.8382928445935249,0.9868257368604343,1.0,0.9746303683833072
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,15,3,2,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.6189949802472814,0.6584123373031616,0.11095558851957321,0.36505600810050964,0.004154894035309553,0.44246144592761993,0.4623149521648884,0.8138440199615212,0.960673705527657
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,16,3,3,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.8894035668581899,0.45796364545822144,0.17688898742198944,0.5253802537918091,0.007458568550646305,0.931136392056942,0.7370374475916227,0.9558056598544821,1.0
|
||||
|
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|
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@@ -0,0 +1,10 @@
|
||||
run,architecture,grid,grid_index,tile_index,row,col,source_path,score,mean,std,saturation,sharpness,exposure_score,contrast_score,detail_score,color_score,rank,tile_path
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0020.png,20,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0020.png,0.9943782195448875,0.4740034341812134,0.24226152896881104,0.5552682280540466,0.011902406811714172,0.9812607318162918,1.0,1.0,1.0,1,outputs\samples\final_showcase\top_tiles\p5_ddpm\rank_01_grid_0020_tile_07.png
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0018.png,18,7,1,2,outputs\samples\final_comparison\p5_ddpm\grid_0018.png,0.9916329786181449,0.471075177192688,0.24396774172782898,0.457231342792511,0.012744851410388947,0.97210992872715,1.0,1.0,1.0,2,outputs\samples\final_showcase\top_tiles\p5_ddpm\rank_02_grid_0018_tile_07.png
|
||||
p5_ddpm,DDPM - cosine v-pred wider,grid_0008.png,8,9,2,0,outputs\samples\final_comparison\p5_ddpm\grid_0008.png,0.9835371665656567,0.483590304851532,0.2652520537376404,0.346821129322052,0.009857337921857834,0.9887802973389626,1.0,1.0,0.9126871824264526,3,outputs\samples\final_showcase\top_tiles\p5_ddpm\rank_03_grid_0008_tile_09.png
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0012.png,12,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0012.png,0.9931557374587933,0.4784943461418152,0.26595890522003174,0.5266944169998169,0.008175451308488846,0.9952948316931725,1.0,0.9782691518033664,1.0,1,outputs\samples\final_showcase\top_tiles\p5_gan\rank_01_grid_0012_tile_06.png
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0013.png,13,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0013.png,0.9891186870634555,0.4683932662010193,0.25315365195274353,0.42203789949417114,0.012284314259886742,0.9637289568781853,1.0,1.0,1.0,2,outputs\samples\final_showcase\top_tiles\p5_gan\rank_02_grid_0013_tile_06.png
|
||||
p5_gan,GAN - WGAN-GP + SN + Attn,grid_0020.png,20,6,1,1,outputs\samples\final_comparison\p5_gan\grid_0020.png,0.9824905775487424,0.49867671728134155,0.2486007660627365,0.3911525011062622,0.02533857524394989,0.9416352584958076,1.0,1.0,1.0,3,outputs\samples\final_showcase\top_tiles\p5_gan\rank_03_grid_0020_tile_06.png
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0010.png,10,6,1,1,outputs\samples\final_comparison\p5_vae\grid_0010.png,0.9116364613990301,0.4356265366077423,0.24881285429000854,0.2984734773635864,0.007039450109004974,0.8613329268991947,1.0,0.9416724216903715,0.785456519377859,1,outputs\samples\final_showcase\top_tiles\p5_vae\rank_01_grid_0010_tile_06.png
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0020.png,20,16,3,3,outputs\samples\final_comparison\p5_vae\grid_0020.png,0.9072376066109756,0.4530244469642639,0.20702789723873138,0.5726377367973328,0.0058115217834711075,0.9157013967633247,0.8626162384947141,0.8949692641342557,1.0,2,outputs\samples\final_showcase\top_tiles\p5_vae\rank_02_grid_0020_tile_16.png
|
||||
p5_vae,VAE - perceptual + PatchGAN,grid_0013.png,13,1,0,0,outputs\samples\final_comparison\p5_vae\grid_0013.png,0.901039089333058,0.4923376142978668,0.19744431972503662,0.40606826543807983,0.005098136607557535,0.9614449553191662,0.822684665520986,0.8632008123240492,1.0,3,outputs\samples\final_showcase\top_tiles\p5_vae\rank_03_grid_0013_tile_01.png
|
||||
|
@@ -0,0 +1,191 @@
|
||||
[
|
||||
{
|
||||
"run":"p5_ddpm",
|
||||
"architecture":"DDPM - cosine v-pred wider",
|
||||
"grid":"grid_0020.png",
|
||||
"grid_index":20,
|
||||
"tile_index":7,
|
||||
"row":1,
|
||||
"col":2,
|
||||
"source_path":"outputs\\samples\\final_comparison\\p5_ddpm\\grid_0020.png",
|
||||
"score":0.9943782195,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"rank":1,
|
||||
"tile_path":"outputs\\samples\\final_showcase\\top_tiles\\p5_ddpm\\rank_01_grid_0020_tile_07.png"
|
||||
},
|
||||
{
|
||||
"run":"p5_ddpm",
|
||||
"architecture":"DDPM - cosine v-pred wider",
|
||||
"grid":"grid_0018.png",
|
||||
"grid_index":18,
|
||||
"tile_index":7,
|
||||
"row":1,
|
||||
"col":2,
|
||||
"source_path":"outputs\\samples\\final_comparison\\p5_ddpm\\grid_0018.png",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"rank":2,
|
||||
"tile_path":"outputs\\samples\\final_showcase\\top_tiles\\p5_ddpm\\rank_02_grid_0018_tile_07.png"
|
||||
},
|
||||
{
|
||||
"run":"p5_ddpm",
|
||||
"architecture":"DDPM - cosine v-pred wider",
|
||||
"grid":"grid_0008.png",
|
||||
"grid_index":8,
|
||||
"tile_index":9,
|
||||
"row":2,
|
||||
"col":0,
|
||||
"source_path":"outputs\\samples\\final_comparison\\p5_ddpm\\grid_0008.png",
|
||||
"score":0.9835371666,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"detail_score":1.0,
|
||||
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|
||||
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|
||||
"tile_path":"outputs\\samples\\final_showcase\\top_tiles\\p5_ddpm\\rank_03_grid_0008_tile_09.png"
|
||||
},
|
||||
{
|
||||
"run":"p5_gan",
|
||||
"architecture":"GAN - WGAN-GP + SN + Attn",
|
||||
"grid":"grid_0012.png",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"source_path":"outputs\\samples\\final_comparison\\p5_gan\\grid_0012.png",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
{
|
||||
"run":"p5_gan",
|
||||
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|
||||
"grid":"grid_0013.png",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"source_path":"outputs\\samples\\final_comparison\\p5_gan\\grid_0013.png",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
{
|
||||
"run":"p5_gan",
|
||||
"architecture":"GAN - WGAN-GP + SN + Attn",
|
||||
"grid":"grid_0020.png",
|
||||
"grid_index":20,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"tile_path":"outputs\\samples\\final_showcase\\top_tiles\\p5_gan\\rank_03_grid_0020_tile_06.png"
|
||||
},
|
||||
{
|
||||
"run":"p5_vae",
|
||||
"architecture":"VAE - perceptual + PatchGAN",
|
||||
"grid":"grid_0010.png",
|
||||
"grid_index":10,
|
||||
"tile_index":6,
|
||||
"row":1,
|
||||
"col":1,
|
||||
"source_path":"outputs\\samples\\final_comparison\\p5_vae\\grid_0010.png",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
{
|
||||
"run":"p5_vae",
|
||||
"architecture":"VAE - perceptual + PatchGAN",
|
||||
"grid":"grid_0020.png",
|
||||
"grid_index":20,
|
||||
"tile_index":16,
|
||||
"row":3,
|
||||
"col":3,
|
||||
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|
||||
"score":0.9072376066,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"tile_path":"outputs\\samples\\final_showcase\\top_tiles\\p5_vae\\rank_02_grid_0020_tile_16.png"
|
||||
},
|
||||
{
|
||||
"run":"p5_vae",
|
||||
"architecture":"VAE - perceptual + PatchGAN",
|
||||
"grid":"grid_0013.png",
|
||||
"grid_index":13,
|
||||
"tile_index":1,
|
||||
"row":0,
|
||||
"col":0,
|
||||
"source_path":"outputs\\samples\\final_comparison\\p5_vae\\grid_0013.png",
|
||||
"score":0.9010390893,
|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"tile_path":"outputs\\samples\\final_showcase\\top_tiles\\p5_vae\\rank_03_grid_0013_tile_01.png"
|
||||
}
|
||||
]
|
||||
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Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user