R Under development (unstable) (2025-01-31 r87670) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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> pkgname <- "ExpImage"
> source(file.path(R.home("share"), "R", "examples-header.R"))
> options(warn = 1)
> library('ExpImage')
Loading required package: raster
Loading required package: sp
> 
> base::assign(".oldSearch", base::search(), pos = 'CheckExEnv')
> base::assign(".old_wd", base::getwd(), pos = 'CheckExEnv')
> cleanEx()
> nameEx("Normatiza")
> ### * Normatiza
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: Normatiza
> ### Title: Normatiza a matriz para que os valores variem entre valores
> ###   pre-estabelecidos.
> ### Aliases: Normatiza
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("as_image")
> ### * as_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: as_image
> ### Title: Transform matrix into image (Transformar matriz em imagem).
> ### Aliases: as_image
> 
> ### ** Examples
> 
> m=matrix(sort(runif(10000)),ncol=100,nrow=100)
> m
               [,1]        [,2]       [,3]       [,4]       [,5]       [,6]
  [1,] 0.0001064336 0.009571792 0.01836823 0.02839293 0.03852645 0.04865535
  [2,] 0.0001206559 0.009615549 0.01838357 0.02844420 0.03859708 0.04877452
  [3,] 0.0002003808 0.009773987 0.01850593 0.02847004 0.03876168 0.04889046
  [4,] 0.0005705222 0.009779969 0.01854641 0.02858897 0.03886659 0.04895114
  [5,] 0.0006052661 0.009820487 0.01861949 0.02859402 0.03893545 0.04918383
  [6,] 0.0006563480 0.009857917 0.01862267 0.02898577 0.03910006 0.04925588
  [7,] 0.0006681741 0.009957012 0.01863082 0.02912467 0.03918472 0.04925604
  [8,] 0.0006821274 0.009998357 0.01863224 0.02927731 0.03921922 0.04933831
  [9,] 0.0009185066 0.010130183 0.01866395 0.02937717 0.03924404 0.04947948
 [10,] 0.0010268190 0.010171223 0.01881210 0.02951141 0.03924896 0.04962032
 [11,] 0.0010658456 0.010268549 0.01885332 0.03001168 0.03926231 0.04965358
 [12,] 0.0011619981 0.010498043 0.01889519 0.03006298 0.03941537 0.04969162
 [13,] 0.0011953502 0.010548147 0.01919661 0.03010991 0.03942021 0.04988253
 [14,] 0.0012542957 0.010653143 0.01919943 0.03011934 0.03946596 0.05009188
 [15,] 0.0013146566 0.010680505 0.01951202 0.03025054 0.03951709 0.05014710
 [16,] 0.0013634798 0.010832544 0.01974544 0.03045106 0.03953041 0.05020154
 [17,] 0.0013717595 0.010991664 0.01975170 0.03052955 0.03956531 0.05030902
 [18,] 0.0014372303 0.011036071 0.01978782 0.03055500 0.03969591 0.05033449
 [19,] 0.0014778997 0.011068757 0.01986536 0.03062896 0.03972757 0.05034173
 [20,] 0.0014780960 0.011093436 0.01988525 0.03066162 0.03987649 0.05042044
 [21,] 0.0016422612 0.011149509 0.01996342 0.03075657 0.03995634 0.05043966
 [22,] 0.0018368582 0.011246694 0.02022311 0.03078355 0.03998421 0.05049768
 [23,] 0.0018571168 0.011340193 0.02036438 0.03081807 0.04041906 0.05052364
 [24,] 0.0019328347 0.011344925 0.02058164 0.03088869 0.04046094 0.05059238
 [25,] 0.0019569546 0.011742868 0.02075437 0.03089679 0.04060497 0.05061376
 [26,] 0.0020192326 0.011759735 0.02077916 0.03100088 0.04087185 0.05063991
 [27,] 0.0020577582 0.011828619 0.02083921 0.03100636 0.04094399 0.05065271
 [28,] 0.0021101697 0.011860647 0.02086326 0.03105766 0.04101766 0.05071004
 [29,] 0.0022506486 0.012142946 0.02090613 0.03121758 0.04112538 0.05077116
 [30,] 0.0025872802 0.012162595 0.02092525 0.03166770 0.04116168 0.05078592
 [31,] 0.0026680226 0.012291918 0.02094694 0.03171320 0.04139260 0.05083270
 [32,] 0.0027381571 0.012379170 0.02101184 0.03171505 0.04152843 0.05090840
 [33,] 0.0028211880 0.012450621 0.02118409 0.03178858 0.04156918 0.05091907
 [34,] 0.0028673552 0.012552510 0.02135514 0.03183958 0.04164943 0.05097773
 [35,] 0.0028992682 0.012836308 0.02148275 0.03197108 0.04176587 0.05112578
 [36,] 0.0030512596 0.012981523 0.02150922 0.03211189 0.04182482 0.05114420
 [37,] 0.0030658648 0.013034772 0.02166385 0.03212876 0.04193454 0.05130922
 [38,] 0.0033045474 0.013055456 0.02168563 0.03217435 0.04196837 0.05146589
 [39,] 0.0034356893 0.013077575 0.02178623 0.03227871 0.04203969 0.05148363
 [40,] 0.0035162179 0.013095047 0.02202729 0.03232287 0.04211701 0.05150961
 [41,] 0.0035537207 0.013109717 0.02203656 0.03236525 0.04214201 0.05159532
 [42,] 0.0035770449 0.013173746 0.02220241 0.03247447 0.04237688 0.05162265
 [43,] 0.0037026675 0.013178688 0.02257647 0.03291433 0.04258244 0.05172894
 [44,] 0.0037180225 0.013221192 0.02266803 0.03294523 0.04259474 0.05187354
 [45,] 0.0037491017 0.013266397 0.02269606 0.03297120 0.04265712 0.05194117
 [46,] 0.0038287381 0.013281904 0.02274122 0.03301441 0.04275739 0.05195274
 [47,] 0.0039816040 0.013390333 0.02292849 0.03301442 0.04288589 0.05202307
 [48,] 0.0042672392 0.013392022 0.02313012 0.03328786 0.04292083 0.05204144
 [49,] 0.0043177721 0.013446449 0.02313606 0.03331256 0.04304040 0.05208240
 [50,] 0.0043212187 0.013512481 0.02333120 0.03333230 0.04317233 0.05208858
 [51,] 0.0043565596 0.013840341 0.02340584 0.03345316 0.04321826 0.05214901
 [52,] 0.0047142794 0.013917039 0.02343692 0.03380009 0.04326472 0.05215062
 [53,] 0.0047664454 0.013924516 0.02345508 0.03390987 0.04346557 0.05226842
 [54,] 0.0048401775 0.014217728 0.02362358 0.03391887 0.04369990 0.05236629
 [55,] 0.0048874374 0.014248614 0.02363294 0.03417065 0.04375315 0.05239109
 [56,] 0.0049942438 0.014266614 0.02408761 0.03439618 0.04379311 0.05240839
 [57,] 0.0050495665 0.014523902 0.02408962 0.03441951 0.04423991 0.05246878
 [58,] 0.0051084850 0.014892920 0.02411139 0.03443876 0.04427512 0.05257702
 [59,] 0.0053999615 0.014923914 0.02425149 0.03455832 0.04428458 0.05258214
 [60,] 0.0054691946 0.014984052 0.02434885 0.03457791 0.04436329 0.05265378
 [61,] 0.0054914262 0.014992921 0.02437594 0.03466939 0.04436704 0.05270203
 [62,] 0.0055322107 0.015100698 0.02448215 0.03483500 0.04444707 0.05271992
 [63,] 0.0056423799 0.015129596 0.02454487 0.03483853 0.04466906 0.05273688
 [64,] 0.0056806048 0.015206428 0.02458035 0.03484955 0.04467151 0.05305581
 [65,] 0.0057275428 0.015266650 0.02486069 0.03509723 0.04481163 0.05369401
 [66,] 0.0058164706 0.015417312 0.02486965 0.03511251 0.04488407 0.05393628
 [67,] 0.0059613350 0.015578101 0.02515870 0.03511671 0.04501560 0.05419043
 [68,] 0.0060189085 0.015651956 0.02522373 0.03527777 0.04529761 0.05432263
 [69,] 0.0060825977 0.015838218 0.02536746 0.03549953 0.04536216 0.05432284
 [70,] 0.0061515740 0.015862073 0.02548197 0.03553923 0.04539799 0.05436122
 [71,] 0.0064597253 0.015964475 0.02554655 0.03554058 0.04543482 0.05449391
 [72,] 0.0067186998 0.016245473 0.02558656 0.03586513 0.04549169 0.05450866
 [73,] 0.0067830668 0.016263810 0.02579152 0.03594829 0.04563921 0.05453965
 [74,] 0.0068985063 0.016612211 0.02582438 0.03594922 0.04572472 0.05505696
 [75,] 0.0072597151 0.016653847 0.02589134 0.03607296 0.04588250 0.05509957
 [76,] 0.0072795150 0.016710327 0.02589192 0.03607724 0.04604055 0.05514840
 [77,] 0.0072967708 0.016874162 0.02595143 0.03611687 0.04611323 0.05516429
 [78,] 0.0073172599 0.017007901 0.02621423 0.03619600 0.04628862 0.05535068
 [79,] 0.0074946049 0.017021661 0.02705652 0.03629047 0.04629398 0.05537975
 [80,] 0.0076685955 0.017213095 0.02707409 0.03633969 0.04635811 0.05551719
 [81,] 0.0078519804 0.017243332 0.02718772 0.03634556 0.04644569 0.05552262
 [82,] 0.0078672103 0.017255964 0.02728685 0.03647023 0.04646089 0.05554798
 [83,] 0.0079148202 0.017285816 0.02744901 0.03653912 0.04652877 0.05584488
 [84,] 0.0079228436 0.017327402 0.02747564 0.03656734 0.04654761 0.05585319
 [85,] 0.0080889331 0.017349499 0.02748661 0.03661954 0.04750120 0.05585486
 [86,] 0.0081284554 0.017474827 0.02749625 0.03665578 0.04752457 0.05586208
 [87,] 0.0081477030 0.017514951 0.02749788 0.03673279 0.04770292 0.05589952
 [88,] 0.0081483482 0.017597033 0.02773473 0.03681897 0.04785852 0.05598377
 [89,] 0.0082282349 0.017637369 0.02775582 0.03690575 0.04786555 0.05624094
 [90,] 0.0082462737 0.017669451 0.02776961 0.03697375 0.04795913 0.05624382
 [91,] 0.0085260209 0.017686601 0.02778712 0.03731268 0.04797986 0.05634867
 [92,] 0.0085831475 0.017790885 0.02791593 0.03739129 0.04808933 0.05642579
 [93,] 0.0088506017 0.017957747 0.02813752 0.03754450 0.04812483 0.05644716
 [94,] 0.0088694678 0.018023822 0.02814806 0.03782945 0.04819137 0.05648682
 [95,] 0.0088885867 0.018031656 0.02823712 0.03787995 0.04827793 0.05653292
 [96,] 0.0090924969 0.018092263 0.02825208 0.03790204 0.04848911 0.05653528
 [97,] 0.0091632709 0.018193165 0.02825997 0.03791847 0.04850540 0.05676851
 [98,] 0.0093664746 0.018195662 0.02826749 0.03820284 0.04851307 0.05691070
 [99,] 0.0094371433 0.018199361 0.02837421 0.03823619 0.04860199 0.05697149
[100,] 0.0094397108 0.018270930 0.02837716 0.03847514 0.04861056 0.05720723
             [,7]       [,8]       [,9]      [,10]      [,11]     [,12]
  [1,] 0.05729494 0.06740474 0.07664518 0.08794818 0.09737435 0.1066140
  [2,] 0.05730625 0.06740730 0.07676579 0.08815112 0.09738549 0.1066300
  [3,] 0.05732748 0.06746642 0.07683144 0.08823663 0.09742410 0.1066483
  [4,] 0.05737268 0.06765690 0.07689704 0.08823905 0.09780854 0.1068054
  [5,] 0.05742289 0.06777775 0.07695907 0.08830411 0.09787904 0.1069895
  [6,] 0.05748599 0.06779449 0.07699878 0.08830802 0.09800068 0.1069904
  [7,] 0.05750106 0.06801186 0.07701351 0.08832537 0.09800559 0.1070380
  [8,] 0.05774175 0.06827499 0.07706438 0.08837121 0.09813411 0.1070394
  [9,] 0.05774957 0.06829250 0.07715167 0.08854265 0.09817207 0.1073091
 [10,] 0.05784423 0.06829928 0.07721866 0.08885341 0.09819972 0.1073245
 [11,] 0.05786891 0.06844664 0.07737881 0.08890980 0.09822723 0.1073593
 [12,] 0.05787517 0.06871002 0.07781625 0.08892602 0.09826156 0.1074744
 [13,] 0.05790896 0.06874244 0.07781855 0.08895207 0.09828059 0.1075846
 [14,] 0.05793207 0.06885538 0.07782189 0.08903728 0.09828337 0.1077766
 [15,] 0.05809840 0.06886856 0.07782227 0.08907646 0.09832169 0.1079436
 [16,] 0.05831439 0.06892715 0.07786962 0.08918144 0.09832177 0.1082434
 [17,] 0.05833403 0.06894063 0.07790134 0.08918454 0.09839177 0.1085932
 [18,] 0.05842339 0.06907020 0.07791245 0.08919613 0.09852387 0.1088063
 [19,] 0.05852176 0.06910671 0.07821896 0.08936092 0.09858125 0.1089644
 [20,] 0.05854744 0.06945874 0.07838116 0.08945316 0.09875934 0.1089805
 [21,] 0.05862245 0.06949483 0.07839259 0.08949422 0.09876388 0.1090290
 [22,] 0.05877355 0.06957998 0.07839758 0.08991495 0.09902127 0.1090293
 [23,] 0.05893249 0.06964916 0.07867750 0.08992942 0.09909983 0.1090469
 [24,] 0.05893438 0.06973020 0.07881758 0.08995196 0.09916910 0.1090960
 [25,] 0.05909328 0.06995970 0.07897418 0.09002636 0.09938261 0.1091010
 [26,] 0.05914993 0.07003268 0.07900481 0.09021370 0.09938910 0.1093032
 [27,] 0.05926643 0.07016099 0.07909077 0.09021985 0.09942523 0.1093144
 [28,] 0.05934745 0.07028956 0.07921450 0.09031777 0.09946616 0.1097455
 [29,] 0.05937614 0.07035663 0.07926287 0.09032375 0.09947426 0.1098580
 [30,] 0.05961989 0.07036150 0.07943969 0.09036600 0.09956924 0.1099456
 [31,] 0.05966493 0.07040867 0.07944193 0.09040571 0.09974473 0.1101419
 [32,] 0.05972695 0.07062630 0.07950444 0.09056008 0.09976379 0.1102712
 [33,] 0.05973101 0.07063884 0.07984441 0.09063022 0.09995111 0.1102893
 [34,] 0.05983306 0.07067905 0.07985544 0.09066547 0.09996337 0.1103606
 [35,] 0.05987397 0.07068805 0.07992458 0.09071829 0.09998999 0.1104028
 [36,] 0.05990024 0.07074258 0.07993552 0.09074537 0.10005491 0.1104478
 [37,] 0.06033118 0.07093238 0.07995241 0.09076585 0.10014085 0.1104736
 [38,] 0.06039416 0.07098261 0.08003769 0.09078838 0.10057791 0.1105387
 [39,] 0.06104960 0.07109499 0.08016928 0.09079790 0.10059142 0.1107911
 [40,] 0.06112000 0.07115402 0.08023623 0.09084271 0.10062401 0.1108173
 [41,] 0.06112795 0.07124022 0.08024637 0.09087741 0.10063140 0.1111488
 [42,] 0.06147238 0.07141334 0.08032245 0.09089585 0.10065308 0.1112133
 [43,] 0.06160942 0.07166787 0.08032411 0.09089599 0.10069289 0.1112197
 [44,] 0.06173132 0.07167788 0.08037862 0.09096079 0.10078299 0.1113087
 [45,] 0.06178627 0.07190189 0.08053156 0.09109747 0.10078312 0.1114219
 [46,] 0.06196987 0.07198397 0.08056949 0.09110849 0.10087313 0.1114776
 [47,] 0.06197037 0.07207050 0.08082255 0.09122868 0.10104517 0.1117601
 [48,] 0.06212216 0.07219098 0.08087939 0.09131426 0.10126658 0.1117726
 [49,] 0.06221405 0.07220870 0.08094338 0.09135008 0.10150320 0.1117870
 [50,] 0.06238962 0.07221124 0.08111215 0.09144519 0.10162090 0.1118923
 [51,] 0.06243016 0.07246063 0.08114142 0.09148448 0.10169328 0.1120391
 [52,] 0.06248807 0.07248914 0.08116851 0.09171709 0.10170690 0.1121136
 [53,] 0.06278613 0.07255766 0.08136956 0.09185913 0.10181667 0.1125926
 [54,] 0.06293980 0.07260954 0.08162358 0.09196543 0.10189852 0.1126932
 [55,] 0.06303701 0.07271237 0.08162441 0.09217766 0.10206189 0.1127144
 [56,] 0.06331248 0.07285473 0.08167005 0.09244104 0.10211375 0.1127180
 [57,] 0.06362592 0.07287736 0.08174284 0.09250938 0.10211536 0.1127780
 [58,] 0.06380247 0.07290691 0.08216668 0.09263914 0.10214789 0.1129126
 [59,] 0.06380706 0.07292085 0.08221343 0.09314007 0.10216107 0.1129188
 [60,] 0.06380848 0.07298789 0.08223544 0.09315281 0.10218147 0.1129415
 [61,] 0.06385987 0.07310176 0.08223923 0.09364985 0.10233513 0.1131122
 [62,] 0.06386784 0.07312673 0.08229440 0.09371059 0.10272097 0.1131325
 [63,] 0.06400941 0.07324687 0.08230133 0.09386645 0.10272942 0.1133062
 [64,] 0.06424209 0.07333542 0.08231843 0.09397494 0.10282001 0.1133095
 [65,] 0.06437604 0.07337371 0.08243931 0.09404589 0.10282928 0.1134625
 [66,] 0.06442308 0.07339495 0.08294508 0.09413322 0.10290711 0.1134796
 [67,] 0.06443166 0.07347974 0.08311390 0.09414504 0.10317673 0.1135077
 [68,] 0.06443476 0.07359016 0.08312610 0.09419062 0.10318424 0.1136313
 [69,] 0.06445754 0.07363795 0.08350816 0.09425378 0.10325043 0.1136517
 [70,] 0.06456192 0.07396390 0.08354486 0.09434470 0.10325188 0.1137158
 [71,] 0.06458218 0.07407391 0.08369814 0.09439027 0.10338958 0.1137167
 [72,] 0.06490054 0.07419950 0.08388960 0.09456393 0.10359530 0.1137759
 [73,] 0.06494922 0.07424379 0.08424691 0.09470967 0.10362963 0.1138490
 [74,] 0.06494992 0.07439791 0.08433047 0.09485786 0.10364550 0.1139907
 [75,] 0.06506744 0.07451498 0.08453311 0.09489760 0.10378454 0.1140161
 [76,] 0.06516364 0.07455983 0.08468041 0.09504998 0.10402443 0.1143600
 [77,] 0.06524824 0.07458383 0.08491773 0.09512225 0.10402937 0.1144751
 [78,] 0.06538929 0.07465596 0.08492106 0.09515213 0.10407935 0.1145014
 [79,] 0.06544711 0.07469530 0.08493542 0.09516487 0.10425507 0.1145597
 [80,] 0.06557821 0.07481681 0.08508976 0.09519437 0.10433632 0.1146016
 [81,] 0.06580196 0.07510495 0.08510921 0.09531515 0.10443179 0.1147859
 [82,] 0.06585441 0.07521088 0.08531101 0.09536375 0.10451286 0.1150467
 [83,] 0.06596663 0.07527575 0.08569740 0.09537672 0.10463539 0.1152690
 [84,] 0.06611048 0.07536466 0.08576187 0.09560594 0.10465279 0.1153423
 [85,] 0.06612216 0.07537496 0.08595180 0.09566556 0.10468662 0.1153547
 [86,] 0.06617483 0.07549401 0.08595192 0.09573974 0.10498764 0.1154262
 [87,] 0.06629701 0.07551073 0.08602733 0.09574764 0.10505014 0.1154712
 [88,] 0.06632476 0.07552557 0.08613583 0.09587903 0.10515787 0.1155253
 [89,] 0.06638635 0.07572298 0.08616865 0.09609910 0.10517901 0.1155487
 [90,] 0.06640603 0.07574408 0.08629090 0.09610413 0.10522010 0.1155603
 [91,] 0.06647208 0.07575449 0.08639538 0.09612580 0.10522635 0.1157880
 [92,] 0.06649306 0.07575899 0.08654001 0.09622307 0.10556219 0.1157920
 [93,] 0.06657605 0.07580315 0.08659821 0.09671919 0.10569117 0.1158990
 [94,] 0.06664776 0.07581713 0.08679346 0.09686129 0.10585032 0.1161049
 [95,] 0.06671415 0.07587497 0.08701906 0.09687472 0.10586849 0.1165686
 [96,] 0.06684511 0.07635945 0.08731592 0.09690157 0.10587278 0.1165936
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[100,] 0.06729615 0.07658663 0.08794006 0.09737155 0.10653014 0.1171976
           [,13]     [,14]     [,15]     [,16]     [,17]     [,18]     [,19]
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           [,20]     [,21]     [,22]     [,23]     [,24]     [,25]     [,26]
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           [,27]     [,28]     [,29]     [,30]     [,31]     [,32]     [,33]
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           [,34]     [,35]     [,36]     [,37]     [,38]     [,39]     [,40]
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           [,48]     [,49]     [,50]     [,51]     [,52]     [,53]     [,54]
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 [60,] 0.9002146 0.9091987 0.9196310 0.9296145 0.9394947 0.9494696 0.9575916
 [61,] 0.9006177 0.9094046 0.9196421 0.9297432 0.9395845 0.9495680 0.9576365
 [62,] 0.9006298 0.9095206 0.9197699 0.9297516 0.9397632 0.9495808 0.9577662
 [63,] 0.9006846 0.9098278 0.9198953 0.9297922 0.9397714 0.9495870 0.9577868
 [64,] 0.9007490 0.9098338 0.9199018 0.9298606 0.9397820 0.9497079 0.9579960
 [65,] 0.9009008 0.9099553 0.9202161 0.9299194 0.9399169 0.9499202 0.9580972
 [66,] 0.9009332 0.9100609 0.9205178 0.9300927 0.9399618 0.9499438 0.9581020
 [67,] 0.9009393 0.9101575 0.9205915 0.9302022 0.9399730 0.9499907 0.9582138
 [68,] 0.9009785 0.9101771 0.9206375 0.9302877 0.9400302 0.9500088 0.9584166
 [69,] 0.9010626 0.9102067 0.9207627 0.9304062 0.9400362 0.9501329 0.9584294
 [70,] 0.9012503 0.9103328 0.9207682 0.9305919 0.9401047 0.9503260 0.9585264
 [71,] 0.9012693 0.9103703 0.9208275 0.9306072 0.9401522 0.9503439 0.9585848
 [72,] 0.9012720 0.9103754 0.9209408 0.9306845 0.9403087 0.9503646 0.9587667
 [73,] 0.9015762 0.9104086 0.9212285 0.9306993 0.9403779 0.9506157 0.9587859
 [74,] 0.9016953 0.9104573 0.9213235 0.9308173 0.9404440 0.9507692 0.9589703
 [75,] 0.9019065 0.9105345 0.9213256 0.9308759 0.9404640 0.9509192 0.9592029
 [76,] 0.9019143 0.9106164 0.9213623 0.9309412 0.9404821 0.9509435 0.9592409
 [77,] 0.9019199 0.9110898 0.9214179 0.9309553 0.9405140 0.9509510 0.9593199
 [78,] 0.9019728 0.9111221 0.9215666 0.9312215 0.9406498 0.9510600 0.9593820
 [79,] 0.9021466 0.9112220 0.9216768 0.9313862 0.9413571 0.9511395 0.9594752
 [80,] 0.9022011 0.9112338 0.9217332 0.9314313 0.9414891 0.9512714 0.9594827
 [81,] 0.9022377 0.9112625 0.9217582 0.9316607 0.9415096 0.9514056 0.9596734
 [82,] 0.9023471 0.9114167 0.9219067 0.9318321 0.9416020 0.9514603 0.9599686
 [83,] 0.9023853 0.9116347 0.9219315 0.9318757 0.9416312 0.9515306 0.9600077
 [84,] 0.9024549 0.9116513 0.9220654 0.9319800 0.9417252 0.9515674 0.9600311
 [85,] 0.9025374 0.9117862 0.9221363 0.9320120 0.9420181 0.9518416 0.9600516
 [86,] 0.9025807 0.9118517 0.9221674 0.9321220 0.9420749 0.9520057 0.9600930
 [87,] 0.9026046 0.9119543 0.9222311 0.9321886 0.9420786 0.9520505 0.9601033
 [88,] 0.9026424 0.9119599 0.9222862 0.9323185 0.9422571 0.9520901 0.9601162
 [89,] 0.9026428 0.9120945 0.9223468 0.9323498 0.9424083 0.9521083 0.9602276
 [90,] 0.9028900 0.9121875 0.9223545 0.9325689 0.9425053 0.9522093 0.9602672
 [91,] 0.9029448 0.9121952 0.9225008 0.9325719 0.9425855 0.9522379 0.9603550
 [92,] 0.9029472 0.9123875 0.9228356 0.9326367 0.9427048 0.9523031 0.9604023
 [93,] 0.9029687 0.9125274 0.9228915 0.9326815 0.9427612 0.9523188 0.9604746
 [94,] 0.9030621 0.9127048 0.9229488 0.9327543 0.9428503 0.9523500 0.9604926
 [95,] 0.9030816 0.9128759 0.9230512 0.9328057 0.9429571 0.9523516 0.9605610
 [96,] 0.9031641 0.9129157 0.9231490 0.9328087 0.9430324 0.9524562 0.9605946
 [97,] 0.9034657 0.9129363 0.9231742 0.9328098 0.9433259 0.9524607 0.9606067
 [98,] 0.9035073 0.9130742 0.9232541 0.9329098 0.9434250 0.9525185 0.9606097
 [99,] 0.9037013 0.9131599 0.9233384 0.9329688 0.9434747 0.9525283 0.9606180
[100,] 0.9038772 0.9132312 0.9233615 0.9330719 0.9435650 0.9525541 0.9607017
           [,97]     [,98]     [,99]    [,100]
  [1,] 0.9608613 0.9711031 0.9799999 0.9894998
  [2,] 0.9610963 0.9711491 0.9802584 0.9895250
  [3,] 0.9610992 0.9712261 0.9802716 0.9897059
  [4,] 0.9614099 0.9712753 0.9803410 0.9898656
  [5,] 0.9614593 0.9712854 0.9803511 0.9901022
  [6,] 0.9615425 0.9715694 0.9803648 0.9904718
  [7,] 0.9615772 0.9720656 0.9806011 0.9904768
  [8,] 0.9615994 0.9721345 0.9806370 0.9906005
  [9,] 0.9617647 0.9724179 0.9806570 0.9906273
 [10,] 0.9618436 0.9724476 0.9806840 0.9906600
 [11,] 0.9618534 0.9725149 0.9807422 0.9909104
 [12,] 0.9619488 0.9725565 0.9807701 0.9909494
 [13,] 0.9621726 0.9726032 0.9808341 0.9909710
 [14,] 0.9623333 0.9726805 0.9809503 0.9910030
 [15,] 0.9625866 0.9727702 0.9810181 0.9910526
 [16,] 0.9625894 0.9729072 0.9811891 0.9910992
 [17,] 0.9627907 0.9729691 0.9812666 0.9911768
 [18,] 0.9628420 0.9730821 0.9813158 0.9912099
 [19,] 0.9629545 0.9732139 0.9813181 0.9913126
 [20,] 0.9629742 0.9732158 0.9813444 0.9914216
 [21,] 0.9630998 0.9733833 0.9815083 0.9914391
 [22,] 0.9631105 0.9735905 0.9815635 0.9914525
 [23,] 0.9633120 0.9736903 0.9816434 0.9915142
 [24,] 0.9638878 0.9737177 0.9816809 0.9915890
 [25,] 0.9639448 0.9737267 0.9817141 0.9916906
 [26,] 0.9639909 0.9738509 0.9817424 0.9916951
 [27,] 0.9639995 0.9739576 0.9819678 0.9917768
 [28,] 0.9640785 0.9740018 0.9820503 0.9918298
 [29,] 0.9642003 0.9740243 0.9824060 0.9918386
 [30,] 0.9642057 0.9742981 0.9824078 0.9918686
 [31,] 0.9643170 0.9743598 0.9824740 0.9919061
 [32,] 0.9645478 0.9744285 0.9825073 0.9920251
 [33,] 0.9645700 0.9745852 0.9826049 0.9921143
 [34,] 0.9646737 0.9747925 0.9827652 0.9921433
 [35,] 0.9648443 0.9752267 0.9830759 0.9921828
 [36,] 0.9648762 0.9752889 0.9831415 0.9923852
 [37,] 0.9648791 0.9753530 0.9836039 0.9926841
 [38,] 0.9649668 0.9756573 0.9837608 0.9927881
 [39,] 0.9650213 0.9756708 0.9839163 0.9930873
 [40,] 0.9651476 0.9757386 0.9840374 0.9933931
 [41,] 0.9652637 0.9757642 0.9842927 0.9934979
 [42,] 0.9654467 0.9757709 0.9843104 0.9935353
 [43,] 0.9655767 0.9757892 0.9843289 0.9936444
 [44,] 0.9656945 0.9758264 0.9847049 0.9937492
 [45,] 0.9658849 0.9759389 0.9848203 0.9937637
 [46,] 0.9659125 0.9760747 0.9848797 0.9937790
 [47,] 0.9659603 0.9761276 0.9849631 0.9939139
 [48,] 0.9661973 0.9761594 0.9850814 0.9939623
 [49,] 0.9662458 0.9761707 0.9850910 0.9940665
 [50,] 0.9663505 0.9762746 0.9850952 0.9941502
 [51,] 0.9663549 0.9764042 0.9851356 0.9942048
 [52,] 0.9664131 0.9765029 0.9851438 0.9945299
 [53,] 0.9664196 0.9765187 0.9852897 0.9945709
 [54,] 0.9664397 0.9765924 0.9853163 0.9947705
 [55,] 0.9665274 0.9766210 0.9854021 0.9948227
 [56,] 0.9668923 0.9766614 0.9855716 0.9948426
 [57,] 0.9669111 0.9766805 0.9856649 0.9948433
 [58,] 0.9670100 0.9768259 0.9856845 0.9951824
 [59,] 0.9671484 0.9768321 0.9857181 0.9952325
 [60,] 0.9671542 0.9768850 0.9857289 0.9952811
 [61,] 0.9671970 0.9768876 0.9858351 0.9953547
 [62,] 0.9673186 0.9769778 0.9858462 0.9953564
 [63,] 0.9673653 0.9769813 0.9860918 0.9954256
 [64,] 0.9675708 0.9770933 0.9861368 0.9955881
 [65,] 0.9677712 0.9771867 0.9863116 0.9955972
 [66,] 0.9678374 0.9772035 0.9863148 0.9957663
 [67,] 0.9680193 0.9773425 0.9863253 0.9957824
 [68,] 0.9681479 0.9774780 0.9864102 0.9958294
 [69,] 0.9682410 0.9775122 0.9864804 0.9959410
 [70,] 0.9682778 0.9775569 0.9865135 0.9959655
 [71,] 0.9686339 0.9775747 0.9865280 0.9960774
 [72,] 0.9687122 0.9776807 0.9868603 0.9961111
 [73,] 0.9687947 0.9777097 0.9868936 0.9961893
 [74,] 0.9688019 0.9779291 0.9871018 0.9962621
 [75,] 0.9688175 0.9779529 0.9871116 0.9962718
 [76,] 0.9689147 0.9780547 0.9871334 0.9963618
 [77,] 0.9689296 0.9781739 0.9872202 0.9963633
 [78,] 0.9690545 0.9782337 0.9873317 0.9966795
 [79,] 0.9692088 0.9782737 0.9873347 0.9967656
 [80,] 0.9692778 0.9783781 0.9876274 0.9967941
 [81,] 0.9694380 0.9785352 0.9877549 0.9968608
 [82,] 0.9695282 0.9785541 0.9877929 0.9968996
 [83,] 0.9696952 0.9785582 0.9878313 0.9972936
 [84,] 0.9697254 0.9785804 0.9878352 0.9973059
 [85,] 0.9699211 0.9786532 0.9880437 0.9975382
 [86,] 0.9700246 0.9786717 0.9880961 0.9976566
 [87,] 0.9700397 0.9787065 0.9881189 0.9977456
 [88,] 0.9700732 0.9787859 0.9883418 0.9978961
 [89,] 0.9701267 0.9788196 0.9884439 0.9982455
 [90,] 0.9701622 0.9789188 0.9885093 0.9982478
 [91,] 0.9702849 0.9790359 0.9885451 0.9982637
 [92,] 0.9703465 0.9791300 0.9886092 0.9984705
 [93,] 0.9704149 0.9794520 0.9887503 0.9987511
 [94,] 0.9704517 0.9794688 0.9888336 0.9988133
 [95,] 0.9705328 0.9797600 0.9888563 0.9988775
 [96,] 0.9707088 0.9797722 0.9889709 0.9989099
 [97,] 0.9707949 0.9798027 0.9890256 0.9991947
 [98,] 0.9708816 0.9798350 0.9890401 0.9994554
 [99,] 0.9709436 0.9799319 0.9891501 0.9998635
[100,] 0.9709971 0.9799576 0.9893155 0.9999306
> info_image(m)
                     
Class1         matrix
Class2          array
Length1           100
Length2           100
MegaPixels       0.01
Mode          numeric
SizeMemory.MB  0.0765
> im=as_image(m)
> im
Image 
  colorMode    : Grayscale 
  storage.mode : double 
  dim          : 100 100 
  frames.total : 1 
  frames.render: 1 

imageData(object)[1:5,1:6]
             [,1]        [,2]       [,3]       [,4]       [,5]       [,6]
[1,] 0.0001064336 0.009571792 0.01836823 0.02839293 0.03852645 0.04865535
[2,] 0.0001206559 0.009615549 0.01838357 0.02844420 0.03859708 0.04877452
[3,] 0.0002003808 0.009773987 0.01850593 0.02847004 0.03876168 0.04889046
[4,] 0.0005705222 0.009779969 0.01854641 0.02858897 0.03886659 0.04895114
[5,] 0.0006052661 0.009820487 0.01861949 0.02859402 0.03893545 0.04918383
> info_image(im)
                     
Class           Image
Length1           100
Length2           100
MegaPixels       0.01
Mode          numeric
SizeMemory.MB 0.07709
> plot_image(m)
nativeRaster.c:60:21: runtime error: signed integer overflow: 16777216 * 255 cannot be represented in type 'int'
    #0 0x7f2540c340bf in nativeRaster /tmp/RtmppTM9FY/R.INSTALL28bd4c6c7eeb08/EBImage/src/nativeRaster.c:60
    #1 0x71e70c in R_doDotCall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:754
    #2 0x8bd404 in bcEval_loop /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:8672
    #3 0x878b1f in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7505
    #4 0x8c4e5c in bcEval_loop /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7979
    #5 0x878b1f in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7505
    #6 0x83f862 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1167
    #7 0x84a832 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:2393
    #8 0x83e1da in applyClosure_core /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:2306
    #9 0xa5401b in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:2328
    #10 0xa5401b in applyMethod /data/gannet/ripley/R/svn/R-devel/src/main/objects.c:120
    #11 0xa581d7 in dispatchMethod /data/gannet/ripley/R/svn/R-devel/src/main/objects.c:473
    #12 0xf4f99d in Rf_usemethod.isra.0 /data/gannet/ripley/R/svn/R-devel/src/main/objects.c:513
    #13 0xa59e46 in do_usemethod /data/gannet/ripley/R/svn/R-devel/src/main/objects.c:579
    #14 0x8b49cd in bcEval_loop /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:8142
    #15 0x878b1f in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7505
    #16 0x83f862 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1167
    #17 0x84a832 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:2393
    #18 0x83e1da in applyClosure_core /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:2306
    #19 0x83fee6 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:2328
    #20 0x83fee6 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1280
    #21 0x9c9d99 in Rf_ReplIteration /data/gannet/ripley/R/svn/R-devel/src/main/main.c:265
    #22 0x9c9d99 in R_ReplConsole /data/gannet/ripley/R/svn/R-devel/src/main/main.c:317
    #23 0x9cb29b in run_Rmainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1219
    #24 0x9d5812 in Rf_mainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1226
    #25 0x4293ff in main /data/gannet/ripley/R/svn/R-devel/src/main/Rmain.c:29
    #26 0x7f255a22950f in __libc_start_call_main (/lib64/libc.so.6+0x2950f) (BuildId: 8257ee907646e9b057197533d1e4ac8ede7a9c5c)
    #27 0x7f255a2295c8 in __libc_start_main_alias_2 (/lib64/libc.so.6+0x295c8) (BuildId: 8257ee907646e9b057197533d1e4ac8ede7a9c5c)
    #28 0x429de4 in _start (/data/gannet/ripley/R/gcc-SAN3/bin/exec/R+0x429de4) (BuildId: a84d18346db10b9f6a24beeffd63f6e34190cf95)

> 
> 
> 
> cleanEx()
> nameEx("calibration_palette")
> ### * calibration_palette
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: calibration_palette
> ### Title: Function to create a color palette for image color calibration
> ###   (Funcao para criar uma paleta de cores para calibracao das cores de
> ###   imagens).
> ### Aliases: calibration_palette
> 
> ### ** Examples
> 
> im=calibration_palette(n=4,px = 500)
> im=calibration_palette(n=3,px = 100)
> 
> 
> 
> cleanEx()
> nameEx("clustering_Kmeans")
> ### * clustering_Kmeans
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: clustering_Kmeans
> ### Title: Image segmentation by clustering using the Kmeans method
> ###   (Segmentacao de imagens pela clusterização pelo metodo Kmeans).
> ### Aliases: clustering_Kmeans
> 
> ### ** Examples
> 
> #Carregando imagens de exemplo
> end=example_image(13)
> im=read_image(end,plot=TRUE)
> seg1=clustering_Kmeans(im,bands = "all",ncluster = 2,col = c("green","red"))
> seg2=clustering_Kmeans(im,bands = c(1,2,3),ncluster = 3,col = c("green","red","blue"))
> seg3=clustering_Kmeans(im,bands = c(1,2,3),ncluster = 4,col = "rand")
> 
> 
> 
> cleanEx()
> nameEx("color_pallete")
> ### * color_pallete
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: color_pallete
> ### Title: Creates a color palette from an image (Criar uma paleta de cores
> ###   a partir de uma imagem).
> ### Aliases: color_pallete
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("compare_image")
> ### * compare_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: compare_image
> ### Title: Function to compare image sizes (Funcao para comparar os
> ###   tamanhos das imagens).
> ### Aliases: compare_image
> 
> ### ** Examples
> 
> #Carregando imagens de exemplo
> im1=read_image(example_image(1))
> im2=read_image(example_image(2))
> im3=read_image(example_image(3))
> 
> #Comparando o tamanho das imagens
> compare_image(list(im1,im2,im3))
$Images_size
  rows cols bands
1 2304 1728     3
2  800 1067     3
3  584  780     3

$Same_size
[1] FALSE

> 
> 
> 
> cleanEx()
> nameEx("contour_image")
> ### * contour_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: contour_image
> ### Title: Contorno da imagem segmentada (Outline of the segmented image.)
> ### Aliases: contour_image
> 
> ### ** Examples
> 
> end=example_image(3)
> im=read_image(end,TRUE)
> b=gray_scale(im = im,method = "g",plot = TRUE)
> m=segmentation(b,threshold = "otsu",selectHigher = FALSE,fillHull = TRUE,plot=TRUE)
[1] "The threshold by Otsu method is (O valor do limiar pelo metodo otsu e): 0.5957"
> contour_image(m)
Image 
  colorMode    : Grayscale 
  storage.mode : double 
  dim          : 584 780 
  frames.total : 1 
  frames.render: 1 

imageData(object)[1:5,1:6]
     [,1] [,2] [,3] [,4] [,5] [,6]
[1,]    0    0    0    0    0    0
[2,]    0    0    0    0    0    0
[3,]    0    0    0    0    0    0
[4,]    0    0    0    0    0    0
[5,]    0    0    0    0    0    0
> 
> 
> 
> 
> 
> cleanEx()
> nameEx("convert_color")
> ### * convert_color
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: convert_color
> ### Title: Convert colors (Converter cores).
> ### Aliases: convert_color
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("create_png")
> ### * create_png
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: create_png
> ### Title: Create a png image with a transparent background (Criar uma
> ###   imagem png com o fundo transparente)
> ### Aliases: create_png
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("crop_image")
> ### * crop_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: crop_image
> ### Title: Esta funcao corta a imagem retirando as laterais nao desejadas.
> ###   (This function removes unwanted sides from the images.)
> ### Aliases: crop_image
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D im=read_image(example_image(2),plot=TRUE)
> ##D im2=crop_image(im)
> ## End(Not run)
> 
> 
> 
> 
> 
> cleanEx()
> nameEx("dilate_image")
> ### * dilate_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: dilate_image
> ### Title: Funcao para acrescentar bordas nos objetos.
> ### Aliases: dilate_image
> 
> ### ** Examples
> 
> #Abrindo uma imagem de exemplo
> im=read_image(example_image(10),plot=TRUE)
> b=gray_scale(im,method = "b",plot=TRUE)
> raiz=segmentation(b,threshold = 0.7,selectHigher = TRUE,plot=TRUE)
> raiz2=dilate_image(raiz,n = 4,plot = TRUE)
> raiz3=dilate_image(raiz,n = 8,plot = TRUE)
> 
> 
> 
> 
> 
> cleanEx()
> nameEx("edit_image")
> ### * edit_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: edit_image
> ### Title: This function changes the brightness, contrast and makes the
> ###   gamma adjustment in the image (Esta funcao permite mudar o brilho,
> ###   contraste e fazer um ajuste gamma na imagem).
> ### Aliases: edit_image
> 
> ### ** Examples
> 
> 
> 
> 
> 
> 
> cleanEx()
> nameEx("edit_imageGUI")
> ### * edit_imageGUI
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: edit_imageGUI
> ### Title: This function changes the brightness, contrast and makes the
> ###   gamma adjustment in the image (Esta funcao permite mudar o brilho,
> ###   contraste e fazer um ajuste gamma na imagem).
> ### Aliases: edit_imageGUI
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D #library(ExpImage)
> ##D #Carregar imagem de exemplo
> ##D im=read_image(example_image(2),plot=TRUE)
> ##D 
> ##D ##Editar imagem
> ##D im2=edit_imageGUI(im)
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("erode_image")
> ### * erode_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: erode_image
> ### Title: Funcao para eliminar as bordas dos objetos.
> ### Aliases: erode_image
> 
> ### ** Examples
> 
> #Abrindo uma imagem de exemplo
> im=read_image(example_image(10),plot=TRUE)
> b=gray_scale(im,method = "b",plot=TRUE)
> raiz=segmentation(b,threshold = 0.62,selectHigher = TRUE,plot=TRUE)
> raiz2=erode_image(raiz,n = 1,plot = TRUE)
> 
> 
> 
> 
> cleanEx()
> nameEx("example_image")
> ### * example_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: example_image
> ### Title: Images used as an example (Banco de imagens utilizadas como
> ###   exemplo).
> ### Aliases: example_image
> 
> ### ** Examples
> 
> example_image(1)
[1] "/data/gannet/ripley/R/packages/tests-gcc-SAN/ExpImage.Rcheck/ExpImage/images/Feijao.jpg"
> example_image(2)
[1] "/data/gannet/ripley/R/packages/tests-gcc-SAN/ExpImage.Rcheck/ExpImage/images/Ovos1.jpg"
> 
> 
> 
> cleanEx()
> nameEx("exclude_object")
> ### * exclude_object
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: exclude_object
> ### Title: Exlude objects in an image by encircling them or using a mask
> ###   (Excluir objetos em uma imagem circundado-os ou usando uma mascara).
> ### Aliases: exclude_object
> 
> ### ** Examples
> 
> 
> # Abrindo a imagem
> im=read_image(example_image(3),plot=TRUE)
> 
> #Obtendo a escalad e cinza
> m=gray_scale(im,method = "r/rgb",plot=TRUE)
> 
> #Obtendo a mascara
> seg=segmentation(m,treshold = 0.50,selectHigher = TRUE,fillHull = TRUE,plot=TRUE)
> 
> #Excluindo o objeto
> exclude_object(im,mask=seg,valueTarget = 0,color=c(r=0.95,g=0.94,b=0.94))
Image 
  colorMode    : Color 
  storage.mode : double 
  dim          : 584 780 3 
  frames.total : 3 
  frames.render: 1 

imageData(object)[1:5,1:6,1]
          [,1]      [,2]      [,3]      [,4]      [,5]      [,6]
[1,] 0.8549020 0.8627451 0.8666667 0.8705882 0.8588235 0.8549020
[2,] 0.8470588 0.8549020 0.8627451 0.8549020 0.8470588 0.8470588
[3,] 0.8666667 0.8745098 0.8823529 0.8823529 0.8705882 0.8666667
[4,] 0.8431373 0.8509804 0.8588235 0.8509804 0.8431373 0.8431373
[5,] 0.8588235 0.8666667 0.8784314 0.8784314 0.8666667 0.8627451
> ## Not run: 
> ##D #dilatando o objeto e excluindo-o
> ##D seg2=dilate_image(seg,n=5)
> ##D exclude_object(im,mask=seg2,valueTarget = 0,color=c(r=0.95,g=0.94,b=0.94))
> ##D 
> ##D 
> ##D exclude_object(im,mask=seg2,valueTarget = 1,color=c(r=0.95,g=0.94,b=0.94))
> ##D 
> ##D 
> ##D  # Segmentar e excluir clicando sobre a imagem.
> ##D exclude_object(im,valueTarget = 1,color=c(r=0.95,g=0.94,b=0.94))
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("extract_pixels")
> ### * extract_pixels
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: extract_pixels
> ### Title: Function to exclude pixels from the background or foreground in
> ###   an image (Funcao para excluir em uma imagem os pixels correspondente
> ###   ao background ou foreground)
> ### Aliases: extract_pixels
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("gray_scale")
> ### * gray_scale
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: gray_scale
> ### Title: Function to get a grayscale image from a color image (Funcao
> ###   para a obtencao de uma imagem em escala de cinza a partir de uma
> ###   imagem colorida)
> ### Aliases: gray_scale
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("histogram_image")
> ### * histogram_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: histogram_image
> ### Title: Create a histogram from image bands (Criar um histrograma a
> ###   partir das bandas das imagens)
> ### Aliases: histogram_image
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende do upload de imagens do github
> ##D #(It depends uploading images from github).
> ##D 
> ##D #' ########################################################
> ##D ###' Abrindo o endereco de bandas de imagens de satelite
> ##D ########################################################
> ##D end1=example_image(14) #Banda de azul
> ##D end2=example_image(15) #Banda de verde
> ##D end3=example_image(16) #Banda de vermelho
> ##D end4=example_image(17) #Banda de IR
> ##D end5=example_image(18) #Banda de SWIR
> ##D ########################################################
> ##D ###' Abrindo bandas de imagens de satelite
> ##D ########################################################
> ##D B1=read_image(end1,plot=TRUE)
> ##D B2=read_image(end2,plot=TRUE)
> ##D B3=read_image(end3,plot=TRUE)
> ##D B4=read_image(end4,plot=TRUE)
> ##D B5=read_image(end5,plot=TRUE)
> ##D 
> ##D ########################################################
> ##D ###' Juntando as bandas em uma imagem
> ##D ########################################################
> ##D im=join_bands(imgs = list(B1,B2,B3,B4,B5))
> ##D tif_info(im)
> ##D histogram_image(im)
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("index_bands")
> ### * index_bands
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: index_bands
> ### Title: Estimation of vegetation indices (Estimacao de indices de
> ###   vegetacao).
> ### Aliases: index_bands
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende do upload de imagens do github
> ##D #(It depends uploading images from github).
> ##D 
> ##D 
> ##D #' ########################################################
> ##D ###' Abrindo o endereco de bandas de imagens de satelite
> ##D ########################################################
> ##D end1=example_image(14) #Banda de azul
> ##D end2=example_image(15) #Banda de verde
> ##D end3=example_image(16) #Banda de vermelho
> ##D end4=example_image(17) #Banda de IR
> ##D end5=example_image(18) #Banda de SWIR
> ##D 
> ##D ########################################################
> ##D ###' Abrindo bandas de imagens de satelite
> ##D ########################################################
> ##D B1=read_image(end1,plot=TRUE)
> ##D B2=read_image(end2,plot=TRUE)
> ##D B3=read_image(end3,plot=TRUE)
> ##D B4=read_image(end4,plot=TRUE)
> ##D B5=read_image(end5,plot=TRUE)
> ##D 
> ##D ########################################################
> ##D ###' Juntando as bandas em uma imagem
> ##D ########################################################
> ##D im=join_bands(imgs = list(B1,B2,B3,B4,B5))
> ##D tif_info(im)
> ##D 
> ##D ##########################################################
> ##D #### Mostrando a imagem colorida
> ##D ##########################################################
> ##D plot_image(im,r=3,g=2,b=1,rasterRGB = TRUE)
> ##D 
> ##D ########################################################
> ##D ###' Calculando o NDVI
> ##D ########################################################
> ##D NDVI=index_bands(index="NDVI",red =im[[3]],nir = im[[4]])
> ##D plot_image(im=NDVI,col=8,axis=TRUE,title="NDVI")
> ##D 
> ##D ########################################################
> ##D ###' Calculando o NDWI
> ##D ########################################################
> ##D NDWI=index_bands(index="NDWI",green =im[[2]],swir = im[[5]])
> ##D plot_image(im=NDWI,col=8,axis=TRUE,title="NDWI")
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("info_image")
> ### * info_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: info_image
> ### Title: Image information (Informacoes sobre as imagens).
> ### Aliases: info_image
> 
> ### ** Examples
> 
> #Carregar imagem de exemplo
> im=read_image(example_image(1),plot=TRUE)
> info_image(im)
                       
Class             Image
Length1            2304
Length2            1728
Length3               3
MegaPixels    11.943936
Mode            numeric
SizeMemory.MB   91.1258
> 
> 
> 
> cleanEx()
> nameEx("join_bands")
> ### * join_bands
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: join_bands
> ### Title: Function to compare image sizes (Funcao para comparar os
> ###   tamanhos das imagens).
> ### Aliases: join_bands
> 
> ### ** Examples
> 
> ###############################################
> #Carregando imagens de exemplo
> im1=read_image(example_image(2),plot=TRUE)
> r=gray_scale(im = im1,method = "r",normalize=FALSE)
> g=gray_scale(im = im1,method = "g",normalize=FALSE)
> b=gray_scale(im = im1,method = "b",normalize=FALSE)
> 
> im2=join_bands(imgs = list(r,g,b))
> plot_image(im2)
> 
> ## Not run: 
> ##D # Not run: Depende do upload de imagens do github
> ##D #(It depends uploading images from github).
> ##D 
> ##D 
> ##D 
> ##D #########################################################
> ##D #########################################################
> ##D #' #' ########################################################
> ##D ###' Abrindo o endereco de bandas de imagens de satelite
> ##D ########################################################
> ##D end1=example_image(14) #Banda de azul
> ##D end2=example_image(15) #Banda de verde
> ##D end3=example_image(16) #Banda de vermelho
> ##D end4=example_image(17) #Banda de IR
> ##D end5=example_image(18) #Banda de SWIR
> ##D 
> ##D ########################################################
> ##D ###' Abrindo bandas de imagens de satelite
> ##D ########################################################
> ##D B1=read_image(end1,plot=TRUE)
> ##D B2=read_image(end2,plot=TRUE)
> ##D B3=read_image(end3,plot=TRUE)
> ##D B4=read_image(end4,plot=TRUE)
> ##D B5=read_image(end5,plot=TRUE)
> ##D 
> ##D ########################################################
> ##D ###' Juntando as bandas em uma imagem
> ##D ########################################################
> ##D im=join_bands(imgs = list(B1,B2,B3,B4,B5))
> ##D tif_info(im)
> ##D plot_image(im,r=3,g=2,b=1,rasterRGB=TRUE)
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("join_image")
> ### * join_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: join_image
> ### Title: Join images(Juntar imagens)
> ### Aliases: join_image
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("linearize_image")
> ### * linearize_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: linearize_image
> ### Title: Image linearization (Linearizacao da imagem).
> ### Aliases: linearize_image
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("mask_pixels")
> ### * mask_pixels
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: mask_pixels
> ### Title: Creates a mask over the background or foreground (Cria uma
> ###   mascara sobre o background ou foreground)
> ### Aliases: mask_pixels
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("measure_image")
> ### * measure_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: measure_image
> ### Title: Function to obtain measurements associated with objects in
> ###   binary images (Funcao para obter medidas associadas aos objetos em
> ###   imagens binarias).
> ### Aliases: measure_image
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("normalize_image")
> ### * normalize_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: normalize_image
> ### Title: Create a histogram from image bands (Criar um histrograma a
> ###   partir das bandas das imagens)
> ### Aliases: normalize_image
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("pick_circle")
> ### * pick_circle
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: pick_circle
> ### Title: Segmentation with the shape of a circle by clicking on the image
> ###   (Segmentacao com o formato de um circulo clicando em na imagem)
> ### Aliases: pick_circle
> 
> ### ** Examples
> 
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D im=read_image("https://raw.githubusercontent.com/AlcineiAzevedo/Files_ExpImage/main/PlacaPetri.jpg",
> ##D plot=TRUE)
> ##D seg=pick_circle(im)
> ##D im2=extract_pixels(im,target = seg,plot=TRUE)
> ##D 
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("pick_color")
> ### * pick_color
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: pick_color
> ### Title: Selecionar os valores de RGB em pixels (Selecting RGB values in
> ###   pixels).
> ### Aliases: pick_color
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D #library(ExpImage)
> ##D #library(EBImage)
> ##D #Carregar imagem de exemplo
> ##D im=read_image(example_image(2),plot=TRUE)
> ##D pick_color(im)
> ## End(Not run)
> 
> 
> 
> 
> cleanEx()
> nameEx("pick_count")
> ### * pick_count
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: pick_count
> ### Title: Count objects (Contar objetos).
> ### Aliases: pick_count
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D 
> ##D im=read_image(example_image(3),plot=TRUE)
> ##D pick_count(im)
> ## End(Not run)
> 
> 
> 
> 
> cleanEx()
> nameEx("pick_length")
> ### * pick_length
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: pick_length
> ### Title: Measure objects in the image on click (Medir objetos na imagem
> ###   ao clicar).
> ### Aliases: pick_length
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D 
> ##D im=read_image(example_image(3),plot=TRUE)
> ##D dpi=pick_resolution(im,centimeters=8.5)
> ##D dpi$dpi
> ##D pick_length(im,dpi = dpi$dpi)
> ##D 
> ## End(Not run)
> 
> 
> 
> 
> cleanEx()
> nameEx("pick_palette")
> ### * pick_palette
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: pick_palette
> ### Title: Obter uma paleta de cores com cliques (Get a color palette with
> ###   clicks ).
> ### Aliases: pick_palette
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D 
> ##D #library(ExpImage)
> ##D #library(EBImage)
> ##D #Carregar imagem de exemplo
> ##D im=read_image(example_image(2),plot=TRUE)
> ##D pick_palette(im)
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("pick_resolution")
> ### * pick_resolution
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: pick_resolution
> ### Title: Get the dpi resolution on an image (Obter a resolução em dpi em
> ###   uma imagem).
> ### Aliases: pick_resolution
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D im=read_image(example_image(3),plot=TRUE)
> ##D dpi=pick_resolution(im,centimeters=8.5)
> ##D dpi$dpi
> ##D pick_length(im,dpi = dpi$dpi)
> ##D 
> ## End(Not run)
> 
> 
> 
> 
> cleanEx()
> nameEx("pick_segmentation")
> ### * pick_segmentation
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: pick_segmentation
> ### Title: Segmenting objects manually (Segmentação de objetos manualmente)
> ### Aliases: pick_segmentation
> 
> ### ** Examples
> 
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D 
> ##D require(ExpImage)
> ##D im=read_image(example_image(3),plot=TRUE)
> ##D mask=pick_segmentation(im)
> ##D im2=extract_pixels(im,mask,plot = TRUE,valueTarget = 1)
> ##D crop_image(im2,segmentation = mask,plot=TRUE)
> ##D im3=extract_pixels(im,mask,plot = TRUE,valueTarget = 0)
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("plot_image")
> ### * plot_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: plot_image
> ### Title: Esta funcao plota imagens. (This function plot the images.)
> ### Aliases: plot_image
> 
> ### ** Examples
> 
> 
> #library(ExpImage)
> #library(EBImage)
> #Carregar imagem de exemplo
> im=read_image(example_image(2),plot=FALSE)
> im=resize_image(im,w = 300,plot = FALSE)
> plot_image(im)
> 
> #Representado imagens em escalas de cinza
> im2 = gray_scale(im,"r")
> plot_image(im2)
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D #Utilizando uma paleta de cores para a melhor visualizacao
> ##D plot_image(im2,col=2)
> ##D plot_image(im2,col=3,axis=TRUE)
> ##D 
> ##D 
> ##D 
> ##D 
> ##D 
> ##D 
> ##D #########################################################
> ##D #########################################################
> ##D #' #' ########################################################
> ##D ###' Abrindo o endereco de bandas de imagens de satelite
> ##D ########################################################
> ##D end1=example_image(14) #Banda de azul
> ##D end2=example_image(15) #Banda de verde
> ##D end3=example_image(16) #Banda de vermelho
> ##D end4=example_image(17) #Banda de IR
> ##D end5=example_image(18) #Banda de SWIR
> ##D 
> ##D ########################################################
> ##D ###' Abrindo bandas de imagens de satelite
> ##D ########################################################
> ##D B1=read_image(end1,plot=TRUE)
> ##D B2=read_image(end2,plot=TRUE)
> ##D B3=read_image(end3,plot=TRUE)
> ##D B4=read_image(end4,plot=TRUE)
> ##D B5=read_image(end5,plot=TRUE)
> ##D 
> ##D ########################################################
> ##D ###' Juntando as bandas em uma imagem
> ##D ########################################################
> ##D im=join_bands(imgs = list(B1,B2,B3,B4,B5))
> ##D tif_info(im)
> ##D plot_image(im,r=3,g=2,b=1,rasterRGB=TRUE)
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("plot_indexes")
> ### * plot_indexes
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: plot_indexes
> ### Title: Function to plot multiple indices (funcao para plotar varios
> ###   indices)
> ### Aliases: plot_indexes
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D 
> ##D #Carregar imagem de exemplo
> ##D im=read_image(example_image(2),plot=TRUE)
> ##D plot_indexes(im)
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("plot_meansures")
> ### * plot_meansures
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: plot_meansures
> ### Title: Funcao para sobrepor informacoes sobre os objetos da imagem
> ### Aliases: plot_meansures
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("predict_RF")
> ### * predict_RF
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: predict_RF
> ### Title: Pixel classification by Random Forest methodology (Classificacao
> ###   de pixels pela metodologia Random Forest)
> ### Aliases: predict_RF
> 
> ### ** Examples
> 
> 
> 
> 
> 
> cleanEx()
> nameEx("predict_logit")
> ### * predict_logit
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: predict_logit
> ### Title: Segmentacao a partir de modelo logit (Segmentation from the
> ###   logit model)
> ### Aliases: predict_logit
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("read_image")
> ### * read_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: read_image
> ### Title: Function to import an image (Funcao para importa uma imagem).
> ### Aliases: read_image
> 
> ### ** Examples
> 
> #Carregar imagem de exemplo
> End=example_image(1)
> im=read_image(End,plot=TRUE)
> 
> 
> 
> 
> cleanEx()
> nameEx("resize_image")
> ### * resize_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: resize_image
> ### Title: Function to change image size (Funcao para mudar o tamanho da
> ###   imagem)
> ### Aliases: resize_image
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("rotate_image")
> ### * rotate_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: rotate_image
> ### Title: Esta funcao rotaciona a imagem. (This function rotates the image
> ###   .)
> ### Aliases: rotate_image
> 
> ### ** Examples
> 
> #library(ExpImage)
> #Carregar imagem de exemplo
> im=read_image(example_image(2),plot=TRUE)
> 
> ##rotacionar a imagem
> im2=rotate_image(im,angle=80)
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D im2=rotate_image(im,angle=60,BGcolor=c(1,1,1))
> ##D 
> ##D im2=rotate_image(im)
> ##D 
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("segmentation")
> ### * segmentation
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: segmentation
> ### Title: Image segmentation function (Funcao para a segmentacao de
> ###   imagens).
> ### Aliases: segmentation
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("segmentation_RF")
> ### * segmentation_RF
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: segmentation_RF
> ### Title: Image segmentation by Random Forest (Segmentacao de imagens por
> ###   Random Forest).
> ### Aliases: segmentation_RF
> 
> ### ** Examples
> 
> 
> 
> 
> 
> cleanEx()
> nameEx("segmentation_logit")
> ### * segmentation_logit
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: segmentation_logit
> ### Title: Funcao para a segmentacao de imagens.
> ### Aliases: segmentation_logit
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("segmentation_logitGUI")
> ### * segmentation_logitGUI
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: segmentation_logitGUI
> ### Title: Funcao para a segmentacao de imagens.
> ### Aliases: segmentation_logitGUI
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D im=read_image(example_image(7),plot=TRUE)
> ##D segmentation_logitGUI(im)
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("segmentation_steps")
> ### * segmentation_steps
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: segmentation_steps
> ### Title: Image segmentation function (Funcao para a segmentacao de
> ###   imagens).
> ### Aliases: segmentation_steps
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("shape_file.BorderExtract")
> ### * shape_file.BorderExtract
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: shape_file.BorderExtract
> ### Title: Excluir as bordas do objetos/parcelas do shapefile
> ### Aliases: shape_file.BorderExtract
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D end=example_image(13)
> ##D im=read_image(end,plot=TRUE)
> ##D A=shape_file.create(im,rows=5,cols=5,rectangular=F,Matrix=NULL,SelectSeveral = F)
> ##D B=shape_file.BorderExtract(im,A,p.rows = .9,p.cols = .9)
> ##D shape_file.plot(im,ShapeFile = B)
> ##D shape_file.split(im =im,shapefile = B,path = getwd(),namesFile = "TEST",type = ".jpg")
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("shape_file.create")
> ### * shape_file.create
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: shape_file.create
> ### Title: Funcao para criar as coordenadas dos objetos/parcelas na imagem
> ### Aliases: shape_file.create
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D end=example_image(13)
> ##D im=read_image(end,plot=TRUE)
> ##D A=shape_file.create(im,rows=5,cols=5,rectangular=F,Matrix=NULL,SelectSeveral = F)
> ##D B=shape_file.BorderExtract(im,A,p.rows = .9,p.cols = .9)
> ##D shape_file.plot(im,ShapeFile = B)
> ##D shape_file.split(im =im,shapefile = B,path = getwd(),namesFile = "TEST",type = ".jpg")
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("shape_file.plot")
> ### * shape_file.plot
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: shape_file.plot
> ### Title: Plotar os objetos/parcelas do shapefile na imagem
> ### Aliases: shape_file.plot
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D end=example_image(13)
> ##D im=read_image(end,plot=TRUE)
> ##D A=shape_file.create(im,rows=5,cols=5,rectangular=F,Matrix=NULL,SelectSeveral = F)
> ##D B=shape_file.BorderExtract(im,A,p.rows = .9,p.cols = .9)
> ##D shape_file.plot(im,ShapeFile = B)
> ##D shape_file.split(im =im,shapefile = B,path = getwd(),namesFile = "TEST",type = ".jpg")
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("shape_file.split")
> ### * shape_file.split
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: shape_file.split
> ### Title: Divide a imagem em objetos/parcelas de acordo com o shapefile
> ### Aliases: shape_file.split
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende da interacao com uma interface grafica
> ##D #(It depends on interaction with a graphical interface).
> ##D 
> ##D end=example_image(13)
> ##D im=read_image(end,plot=TRUE)
> ##D A=shape_file.create(im,rows=5,cols=5,rectangular=F,Matrix=NULL,SelectSeveral = F)
> ##D B=shape_file.BorderExtract(im,A,p.rows = .9,p.cols = .9)
> ##D shape_file.plot(im,ShapeFile = B)
> ##D shape_file.split(im =im,shapefile = B,path = getwd(),namesFile = "TEST",type = ".jpg")
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("skeletonize_image")
> ### * skeletonize_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: skeletonize_image
> ### Title: Function for skeletonization in images (Esta funcao faz a
> ###   skeletonizacao em imagens).
> ### Aliases: skeletonize_image
> 
> ### ** Examples
> 
> im=read_image(example_image(10),plot=TRUE)
> im2=segmentation(im@.Data[,,1],plot = TRUE)
[1] "The threshold by Otsu method is (O valor do limiar pelo metodo otsu e): 0.5684"
> T1=skeletonize_image(im2,plot = TRUE)
> T2=thinning_image(im2,plot = TRUE)
[1] "a"
[1] "b"
> 
> 
> 
> cleanEx()
> nameEx("split_image")
> ### * split_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: split_image
> ### Title: This function splits the image into several others (Esta funcao
> ###   divide a imagem em varias outras de acordo com os objetos que contem)
> ### Aliases: split_image
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("square_image")
> ### * square_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: square_image
> ### Title: Transform the square image (Transforme a imagem quadrada).
> ### Aliases: square_image
> 
> ### ** Examples
> 
> im=read_image(example_image(10),plot=TRUE)
> square_image(im,r=0,g=0,b=1,plot=TRUE)
Image 
  colorMode    : Color 
  storage.mode : double 
  dim          : 1147 1147 3 
  frames.total : 3 
  frames.render: 1 

imageData(object)[1:5,1:6,1]
     [,1] [,2] [,3] [,4] [,5] [,6]
[1,]    0    0    0    0    0    0
[2,]    0    0    0    0    0    0
[3,]    0    0    0    0    0    0
[4,]    0    0    0    0    0    0
[5,]    0    0    0    0    0    0
> 
> 
> 
> 
> cleanEx()
> nameEx("summary_color")
> ### * summary_color
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: summary_color
> ### Title: Summarize the colors present in the segmented area of an image
> ###   (Sumarizar as cores presentes na area segmentada de uma imagem).
> ### Aliases: summary_color
> 
> ### ** Examples
> 
> 
> 
> 
> cleanEx()
> nameEx("thinning_image")
> ### * thinning_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: thinning_image
> ### Title: This function makes the thinning images(Esta funcao faz o
> ###   thinning em imagens).
> ### Aliases: thinning_image
> 
> ### ** Examples
> 
> im=read_image(example_image(10),plot=TRUE)
> im2=segmentation(im@.Data[,,1],plot = TRUE)
[1] "The threshold by Otsu method is (O valor do limiar pelo metodo otsu e): 0.5684"
> T1=skeletonize_image(im2,plot = TRUE)
> T2=thinning_image(im2,plot = TRUE)
[1] "a"
[1] "b"
> 
> 
> 
> cleanEx()
> nameEx("tif_info")
> ### * tif_info
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: tif_info
> ### Title: Image information in tif format (Informacoes das imagens no
> ###   formato tif).
> ### Aliases: tif_info
> 
> ### ** Examples
> 
> ## Not run: 
> ##D # Not run: Depende do upload de imagens do github
> ##D #(It depends uploading images from github).
> ##D 
> ##D ########################################################
> ##D ###' Abrindo o endereco de bandas de imagens de satelite
> ##D ########################################################
> ##D end1=example_image(14) #Banda de azul
> ##D 
> ##D ########################################################
> ##D ###' Abrindo bandas de imagens de satelite
> ##D B1=read_image(end1,plot=TRUE)
> ##D ########################################################
> ##D ###' Informacao das bandas de imagens de satelite
> ##D  tif_info(B1)
> ## End(Not run)
> 
> 
> 
> cleanEx()
> nameEx("write_image")
> ### * write_image
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: write_image
> ### Title: Function to save an image (Funcao para salvar uma imagem).
> ### Aliases: write_image
> 
> ### ** Examples
> 
> ## Not run: 
> ##D #Carregar imagem de exemplo
> ##D im=read_image(example_image(1),plot=TRUE)
> ##D im2=resize_image(im,w=1000,plot=TRUE)
> ##D im3=crop_image(im2,w =200:650,h=100:450,plot = TRUE)
> ##D imb=edit_image(im3,brightness = 0.1,contrast = 1.7,gamma  = 1.2)
> ##D write_image(x = imb,files = "Test.jpg")
> ## End(Not run)
> 
> 
> 
> ### * <FOOTER>
> ###
> cleanEx()
> options(digits = 7L)
> base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
Time elapsed:  113.731 7.57 123.858 0 0 
> grDevices::dev.off()
null device 
          1 
> ###
> ### Local variables: ***
> ### mode: outline-minor ***
> ### outline-regexp: "\\(> \\)?### [*]+" ***
> ### End: ***
> quit('no')