OCR From Photographs
A quick preview of a longer process: running Optical Character Recognition (OCR, essentially converting images of text into actual text) on photographs, many of which do not include any text at all. Below is the result, run on about 25 images:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 |
L 2w §§.§;§s~5 ,L_§;L wvmfigxb we, «usmswm E ugxwfim L L .L L . L. L .%L.v§RwEf% figs»: gfifiz 2&3 3L,..aL.,: a%L.$ §a§£ L L .L L L LL . ,5 wxmacfiaswmm mmow. . LL. LEwz9,.§EE»:§mmnw &¢2.§..E-,~cauu§ Lao ..m L . $L§.3.x;%m£ §. a§,a.i...L«b aw .L.w.»w§L «Q 30.. a,E8L.w3 afivuf in. my QZL L . , L .n.?2a.:L3w.mm..S6wn.:s.w L L . L .. a L.:.&£._.afi.w§.%éamaaxv _ afifi. L . «.m§L...mm,a. L%mmLLw,LLww.Z L wmwr.y.,§:..v L at . mfi.mJL 4.? xv81,_.T.u£zI1III.m:.8.m«u£!Ii§nm11.1iH ....TI.m§«.9I..amua.Da.m..lUuuAu.lmK.u Egg! as an w..nSHea£u..nc£a.T8afia£ul1wulDamu£w§uaau£iaJ1ulz., . §fi£diu1SanSfinanm£.?unhu!uwlBmiu£Im8fl3am:_ T w£~P&MQuum§ai3u£QmuHulmflNflIUuwnlmmDm3NuuflIiixw».iuh.u4w»W.§»., §fiu£&2a.nEnm3fiE»x£ulu3@¢nSmum.!uu4mflu£Im.u3aa§.1n.mI. 2§a§muns£35E§m.§.aB...£maI3i§uwB§a&»aa3£u. uwitwaawmfiau um$nwB%&.:muIu73uvOu£%@m?l.2un§&3u£ ilfva m.mI.&~d. $.elam§%1m5£wNm%E..§uanwvnIi&nfim 355u££o:¢w.uP.U 2:. dnmueum. A w...w...1».w..wa.. «.;«.....a... .. E...m.Lm, Mun.» a4.rdufimvN.mM m .«¢¢.¢.wm.mZ3§.«l%_.4~MoEGuumAufi.nb mumyuuh my mflwwmvwqm ._wrAB..7 fit, ufl W/EH9” fl..A..mm.,..m wuauunm mflumv .u...m«.X?m Bkaamumflm mm mm... uudmfi hufiunnw Wu wwmm5nwWfiaamflmAnunbum..cu«mu¢a.E—onEou ,..¢Hw~.wwL«wwzz....M./J Nfiwm 4 1/umwwwu ,._F..11 «mu «my Gcdmwufl mu emu mama.“ E_§, 3.0 ,.£mT.o$. ..~ ,. wnox, WM ,.»..um WW1, ~u:N5.t»Eu.§.tuan~ omaswé mow afluawwu mam _.,fiZ-,u..£..m .5 Ouwnvmm Iv: V; ‘« . *9? . - I I Q ' 3 . ., V» I3. ' ‘X91 . I K , < ‘D. \:. an -~ ,. 4. \ z staflio 3:. 2.. IL . . ‘.22 . 3 3,33-..».. . ». .=oi_:: 3 .::_..,x.. w lIt.:Iv...|€.A!vt M ...mm.~.n\8.u<: <.:_.:3; . 3<u:E. 5» fr. .|..t'|.\:.c|..s .1 1 . , 3%. 32 535 .4 5.3 .W‘.xIv3eB4o.¢na_.m..., §3~..§ _ 3.”. 3. 2.5.. 3 a......? an ._oE.; ;..\|i19s\stf..\,:;..f .5. 5!: 311%. :..«:S. :2 \.u=.....‘:....§.§. a§.s an n 8 .<uu..2§ .2 .. . ,. ,, ~ |
Source code to come shortly, though it’s a pretty simple automation written in Python and using Tesseract.