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Datasets:
leshy223
/
synthetic_sami_ocr_data

Tasks:
Image-to-Text
Modalities:
Image
Text
Formats:
parquet
Languages:
Southern Sami
Northern Sami
Lule Sami
Size:
100K - 1M
Tags:
OCR
ATR
Sámi
Synthetic
Libraries:
Datasets
Dask
Polars
License:
Dataset card Data Studio Files
xet
Community
1
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lii tavesämmilijn noonâ salmâveisidemärbivyehi,
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lii tavesämmilijn noonâ salmâveisidemärbivyehi,
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vuorddá.
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vuorddá.
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gadotusa Siavak læk rokkadusa bokte
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gadotusa Siavak læk rokkadusa bokte
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familie var opprinnelig svenske reindriftssamer, som slo
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familie var opprinnelig svenske reindriftssamer, som slo
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JIS SATNE VIELIE GOH BIELIEM ÅÅDTJE DEJSTIE
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jis satne vielie goh bieliem åådtje dejstie
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stáhta lea geatnegahttojuvvon čuovvut. Sámediggi várre
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stáhta lea geatnegahttojuvvon čuovvut. Sámediggi várre
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väldim lahâasâttâs já haldâttâs ovdedemhaavâin sehe škovliimist. Pargojuávkku iävtut,
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väldim lahâasâttâs já haldâttâs ovdedemhaavâin sehe škovliimist. Pargojuávkku iävtut,
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kote lii
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kote lii
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26.8.2021 Suomâ ääigi
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26.8.2021 Suomâ ääigi
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Don ik galea læt dastmannel gonagassan. 1 Sam. 8–15.
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Don ik galea læt dastmannel gonagassan. 1 Sam. 8–15.
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maahtoem utnedh .
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maahtoem utnedh .
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gárramijt, vahágijt ja
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gárramijt, vahágijt ja
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dovne julevsaemien jïh nöörjen gielesne jïh gærjesne guvvieh Urheimen
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dovne julevsaemien jïh nöörjen gielesne jïh gærjesne guvvieh Urheimen
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gallis
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gallis
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– Da duosstelis ulmutja gudi li ietjasa vásádusáj
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– Da duosstelis ulmutja gudi li ietjasa vásádusáj
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smj
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kantovrras. 2. Juohkehaččas lea vuoigatvuohta sámástit njálmmálaš
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kantovrras. 2. Juohkehaččas lea vuoigatvuohta sámástit njálmmálaš
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Bidumsámegiela ja
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Bidumsámegiela ja
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boahttevaš boazodoallošiehtadusaide. Dál
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boahttevaš boazodoallošiehtadusaide. Dál
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% ađai nelji viđâdâs aassâmkoloin. Te tun máávsáh
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% ađai nelji viđâdâs aassâmkoloin. Te tun máávsáh
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Paltto (sämitigge) Äššitobdee Elina Helander-Renvall (Laapi ollâopâttuv
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Paltto (sämitigge) Äššitobdee Elina Helander-Renvall (Laapi ollâopâttuv
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faloJtn?3a läfu§ äPM nuofe§ tat, 2ltt' ärro
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faloJtn?3a läfu§ äPM nuofe§ tat, 2ltt' ärro
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ete sierâ
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ete sierâ
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smn
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sïjhth bielie
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sïjhth bielie
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särnidâm gullahkielân jyehi pasepeeivi paijeel love
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särnidâm gullahkielân jyehi pasepeeivi paijeel love
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smn
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paijeel
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paijeel
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biejjiebeetnegekrievemem vuelede 40 prosentese
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biejjiebeetnegekrievemem vuelede 40 prosentese
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edtji daerpiesvoetide
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edtji daerpiesvoetide
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1,315
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TAVESÄMIKIELÂN RUÁVINJAARGÂ
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tavesämikielân Ruávinjaargâ
upper
Monda/Monda-VariableFont_wght.ttf
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mentora sámesijdajs Jåhkåmåhken galggi sijáv
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mentora sámesijdajs Jåhkåmåhken galggi sijáv
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vierhtiedidh saemien 2 mænngan. Learohkh tjoeverieh dam nænnoestidh
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vierhtiedidh saemien 2 mænngan. Learohkh tjoeverieh dam nænnoestidh
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sma
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fertejit leat mielde doppe gos mearrádusat dahkkojuvvojit. Min cealkámušain
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fertejit leat mielde doppe gos mearrádusat dahkkojuvvojit. Min cealkámušain
identity
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50
100
100
100
58
2,350
110
2,450
160
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sme
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pana epičielgâ säänih: duuri – duurin,
upper
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100
100
100
64
1,396
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1,496
179
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68
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smn
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grammatihkine reakasåvva. Maana dan voestesgïelem leara mearan
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grammatihkine reakasåvva. Maana dan voestesgïelem leara mearan
identity
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50
50
100
100
100
82
2,470
175
2,570
225
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sma
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Sámedikke webbav oahppamnävvon. Aktan gielav nannip!
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Sámedikke webbav oahppamnävvon. Aktan gielav nannip!
identity
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50
100
100
100
80
2,043
170
2,143
220
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96
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smj
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Daid iskkademiid válddahus
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Daid iskkademiid válddahus
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100
100
100
79
1,150
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1,250
189
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33
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Ut Den virker og udretter
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Ut Den virker og udretter
identity
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100
100
100
57
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912
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Njaarke ælloniehke li badjel guoktalåk jage rahtjam gievrrudagáj
identity
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100
100
100
76
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2,537
209
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smj
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Finnmárkkulága ulbmilparagráfa biddjojuvvot vuođđun, dat
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Finnmárkkulága ulbmilparagráfa biddjojuvvot vuođđun, dat
identity
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50
100
100
100
74
2,031
149
2,131
199
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1,998
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seminárra álggá de gasskabiejvbiebbmo guossoduvvá. Dijstagá
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seminárra álggá de gasskabiejvbiebbmo guossoduvvá. Dijstagá
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50
100
100
100
68
2,348
154
2,448
204
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30
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2,278
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smj
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birra siid.19). Veahki masa dus
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birra siid.19). Veahki masa dus
identity
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50
50
100
100
99
58
781
101
881
151
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sme
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sámi kulturpolitihkkii. Sámi kulturrái bargá viidát ovttasráiid
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sámi kulturpolitihkkii. Sámi kulturrái bargá viidát ovttasráiid
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100
100
74
2,496
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2,596
210
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gohtje hatbrott. Fidnovihkeođastus - regjeringen.no Ráđđehus
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gohtje hatbrott. Fidnovihkeođastus - regjeringen.no Ráđđehus
identity
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50
100
100
100
55
1,250
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1,350
149
line_images/000b70e2-cb6b-4e64-9f82-5802beaf0da9.jpg
augraphy_logs/000b70e2-cb6b-4e64-9f82-5802beaf0da9.json
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sma
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lasseen kulmáin sämikieláin. Eres
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lasseen kulmáin sämikieláin. Eres
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50
100
100
100
67
1,343
126
1,443
176
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augraphy_logs/000b73bc-2801-474d-99cc-cba584a365e1.json
16
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smn
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JAEPIEN 1940. DAATE NÅAMESJEN JARNGE LIJ SAEMIEN
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jaepien 1940. Daate Nåamesjen jarnge lij saemien
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50
50
100
100
100
51
1,726
100
1,826
150
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augraphy_logs/000b8ecf-7813-4672-8394-267be570c41f.json
56
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sma
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puáhtá eres lasseen adeliđ eeji suhânoomâ.
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puáhtá eres lasseen adeliđ eeji suhânoomâ.
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Anton_SC/AntonSC-Regular.ttf
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100
100
65
1,323
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1,423
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augraphy_logs/000bb89a-4791-427a-839d-41d1ea0ee40f.json
79
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1,302
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smn
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ålles Divtasvuonan ja oadtjuv moadda
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ålles Divtasvuonan ja oadtjuv moadda
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Mynerve/Mynerve-Regular.ttf
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50
100
100
100
62
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1,401
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augraphy_logs/000c1ce8-1b1f-45f6-9afe-9bb1767164fe.json
20
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1,221
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smj
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Uáppeekodde Puoh Säämi
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Uáppeekodde Puoh Säämi
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Fascinate_Inline/FascinateInline-Regular.ttf
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50
50
100
100
100
60
904
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1,004
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augraphy_logs/000c4df9-31ff-456f-b900-e3667ffce59d.json
0
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smn
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on the green , you might as well
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on the green , you might as well
identity
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100
100
66
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90
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konsultašuvdnačoahkkima daid
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konsultašuvdnačoahkkima daid
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Sankofa_Display/SankofaDisplay-Regular.ttf
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100
100
72
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1,218
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1,035
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sme
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gaskkas skuvlajagi 2008/09. Tabealla 4.17
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gaskkas skuvlajagi 2008/09. Tabealla 4.17
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100
100
96
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1,231
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1,331
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sme
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táárbu mield išediđ tábáhtusâi ornimáid lohtâseijee pargoin. Pargee parga
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100
100
57
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smn
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Pyecceiauto vyeijee kuovlâlij
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Pyecceiauto vyeijee kuovlâlij
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Source_Sans_3/static/SourceSans3-Italic.ttf
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100
100
100
75
1,086
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smn
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minngemes tijjen vielie tsåatskeles sjïdteme beapmoebeetsuve
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minngemes tijjen vielie tsåatskeles sjïdteme beapmoebeetsuve
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100
100
72
1,583
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1,683
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71
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sma
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leah; learohkh gelkieh jïjtsh teeksth joekehts ulmide darjodh
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leah; learohkh gelkieh jïjtsh teeksth joekehts ulmide darjodh
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50
50
100
100
100
60
1,839
119
1,939
169
line_images/000da016-1573-4edd-bcc3-ee7d4794d784.jpg
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1,816
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sma
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doaimma ja ovddideami ruhtadeami. 7.3.2.3 Doarjja
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doaimma ja ovddideami ruhtadeami. 7.3.2.3 Doarjja
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50
50
100
100
100
80
2,109
164
2,209
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28
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2,037
155
sme
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Sortland, Ina-Ristin Danielsen Gundersen, 20 år fra Hell og Ul-Juhan
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Sortland, Ina-Ristin Danielsen Gundersen, 20 år fra Hell og Ul-Juhan
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Montserrat/static/Montserrat-Light.ttf
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(255, 230, 255)
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50
100
100
100
58
1,600
103
1,700
153
line_images/000e768c-4984-4a93-857f-cf662f581287.jpg
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34
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1,534
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sme
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RÄHISTÂLLÂMMAISTER SEKSUAALLŠVUOĐ SÄNIKIRJE
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Rähistâllâmmaister Seksuaallâšvuođâ sänikirje
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100
100
100
54
1,975
134
2,075
184
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87
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1,962
119
smn
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tjïeltine maehtieh viehkiedïrregi bïjre syökedh dutnjien.
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tjïeltine maehtieh viehkiedïrregi bïjre syökedh dutnjien.
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Pirata_One/PirataOne-Regular.ttf
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100
100
100
62
1,172
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1,272
166
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1,140
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sma
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sämmilâšsiärvádâhân. Kiirjijd kalga toimâttiđ
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sämmilâšsiärvádâhân. Kiirjijd kalga toimâttiđ
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100
100
100
68
1,924
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2,024
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84
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1,908
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Tjaaleldh govlesadteme Lïerehtimmien
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Tjaaleldh govlesadteme Lïerehtimmien
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Monda/static/Monda-Regular.ttf
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50
100
100
100
95
1,912
188
2,012
238
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1,887
155
sma
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Dál ožžot ovcci giellaguovddáža
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Dál ožžot ovcci giellaguovddáža
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Anton/Anton-Regular.ttf
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100
62
888
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988
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kirjettum reivân Suomâ aalmugtiätuvuáhádâhân merkkejum
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kirjettum reivân Suomâ aalmugtiätuvuáhádâhân merkkejum
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Kalnia_Glaze/static/KalniaGlaze_Expanded-SemiBold.ttf
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100
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ráđádâllâđ. Maid te täälgis koolgâi
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ráđádâllâđ. Maid te täälgis koolgâi
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vel 15 miljovnna kruvnno rávdnjevuogádaga ođasmahttimii.
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vel 15 miljovnna kruvnno rávdnjevuogádaga ođasmahttimii.
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ja mii leat hui duhtavaččat go
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ja mii leat hui duhtavaččat go
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söndagen i advent, juldagen med flera, kan predikan utlägga särskilt
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čállojuvvo beavdegirji, masa árvalusat, mearkkašumit,
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čállojuvvo beavdegirji, masa árvalusat, mearkkašumit,
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74
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Dán guoradallama ájggom lij sáme
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Dán guoradallama ájggom lij sáme
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100
100
68
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1,255
190
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båhti tjuovvovasj infrastruktuvrradagu
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båhti tjuovvovasj infrastruktuvrradagu
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100
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66
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2,300
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sáme giela ja kulturmáhtudagá birra barggo- ja álkkádusháldadusán, ja oajvvádij moadda
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sáme giela ja kulturmáhtudagá birra barggo- ja álkkádusháldadusán, ja oajvvádij moadda
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ædnam sisa. Olbmuk rog- ge daggo, ja ragjegædge, masa ruossa. lær Cuppum
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ædnam sisa. Olbmuk rog- ge daggo, ja ragjegædge, masa ruossa. lær Cuppum
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almetjigujmie aktene dejstie siebrien 200
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almetjigujmie aktene dejstie siebrien 200
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100
100
70
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kr studenth/honnööre 100
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fealadæmman aaj loejhtes-revytjïertide nuepieh saemien revybarkoem øøvtiedidh
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fealadæmman aaj loejhtes-revytjïertide nuepieh saemien revybarkoem øøvtiedidh
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92
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GALGA! UVSASJ LIJ
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galga! Uvsasj lij
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100
100
64
415
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515
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osku ja etihkka studerenráhkkanahtti
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osku ja etihkka studerenráhkkanahtti
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100
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77
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Jis tun lah algâttâm tuu uápuid nuvt kuhes ääigi tassaaš, ete jieh
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Jis tun lah algâttâm tuu uápuid nuvt kuhes ääigi tassaaš, ete jieh
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100
100
74
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och Voernese). Arbetsgrupp är representanterna från kommunen. Den
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och Voernese). Arbetsgrupp är representanterna från kommunen. Den
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Aarbortesne 2003 (Guvvie: Svein Lund) Saemien
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Aarbortesne 2003 (Guvvie: Svein Lund) Saemien
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Regijovnale evtiedimmieråajvarimmieh / sjïehteladteme jieliemasse
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Regijovnale evtiedimmieråajvarimmieh / sjïehteladteme jieliemasse
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le sierraláhkáj boanndá
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le sierraláhkáj boanndá
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100
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821
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lågåduvvat: Juogu A Hærrá, åhpada mijáv biejvijdimme låhkåt, vaj vijses vájmojt oadtjop.
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lågåduvvat: Juogu A Hærrá, åhpada mijáv biejvijdimme låhkåt, vaj vijses vájmojt oadtjop.
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aaij öuåvuvå kietådållämoornig
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aaij öuåvuvå kietådållämoornig
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gosa son jes datto, son satta
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gosa son jes datto, son satta
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SIJJIENOMMI BIJRE SAEMIEN-GIELESNE
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sijjienommi bijre saemien-gielesne
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korrâsávt já kyeli kirdá koške enâmân.
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korrâsávt já kyeli kirdá koške enâmân.
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77
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New Zealand, 67 CCPR General Comment 12 (21), UN Doc. A/39/40
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New Zealand, 67 CCPR General Comment 12 (21), UN Doc. A/39/40
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DM_Serif_Display/DMSerifDisplay-Italic.ttf
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99
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vájves vidjurav tjielggit. Psykologa máhttá aj
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vájves vidjurav tjielggit. Psykologa máhttá aj
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73
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šaddet geavahit dohkketmeahttun guhkes áiggi skuvlasáhtosteapmái. Dán
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šaddet geavahit dohkketmeahttun guhkes áiggi skuvlasáhtosteapmái. Dán
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99
75
2,317
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tan jafen 1601 (Spcffete finne). Soft e Id
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tan jafen 1601 (Spcffete finne). Soft e Id
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55
917
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1,017
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tjaeliehtimmien åejvieh nubpene rïjhkesne
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tjaeliehtimmien åejvieh nubpene rïjhkesne
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M_PLUS_1p/MPLUS1p-Black.ttf
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61
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1,072
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pryövenassh 5., 8. jïh
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pryövenassh 5., 8. jïh
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637
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Facebook Redaktør: Geir Johnsen | Webansvarlig:
3b5aa703-9d57-42a5-a205-f94147f6f337
Facebook Redaktør: Geir Johnsen | Webansvarlig:
identity
Protest_Guerrilla/ProtestGuerrilla-Regular.ttf
92
(16, 22, 11)
(183, 235, 247)
50
50
100
100
100
64
2,010
154
2,110
204
line_images/00157fbf-2a6e-4751-8dd0-1194eb94db93.jpg
augraphy_logs/00157fbf-2a6e-4751-8dd0-1194eb94db93.json
5
39
1,915
129
sma
00158a69-b7ff-4d17-8adc-dadfb27ee94c
gierddis sijájn gudi dav dárbahi Oahppe doarjju ja bælos sijáv gudi
9a931935-5bc2-4288-af42-f9c0d93fe046
gierddis sijájn gudi dav dárbahi Oahppe doarjju ja bælos sijáv gudi
identity
Mynerve/Mynerve-Regular.ttf
72
(47, 47, 46)
(255, 223, 134)
50
50
100
100
100
57
2,052
151
2,152
201
line_images/00158a69-b7ff-4d17-8adc-dadfb27ee94c.jpg
augraphy_logs/00158a69-b7ff-4d17-8adc-dadfb27ee94c.json
29
51
1,975
145
smj
00158ac0-0b62-440f-805d-3c314dd9b10e
GÅLMMÅ VUODOSUODJEPARAGRÁFA VADDI RIJKALASJ UNNEPLÅGOJDA RIEKTÁV DIEDEDIB-MÁJ, KULTUVRA
b22ed4ba-fd40-4345-a251-93041ffee5a5
gålmmå vuodosuodjeparagráfa vaddi rijkalasj unneplågojda riektáv diededib-máj, kultuvra
upper
Ribeye_Marrow/RibeyeMarrow-Regular.ttf
70
(252, 228, 255)
(58, 48, 28)
50
50
100
100
100
50
4,366
132
4,466
182
line_images/00158ac0-0b62-440f-805d-3c314dd9b10e.jpg
augraphy_logs/00158ac0-0b62-440f-805d-3c314dd9b10e.json
97
60
4,363
142
smj
0015a633-0f74-46db-9ed6-66511df9efd7
akti oadtjot ja de moadda máno
53227b67-fd98-44e5-8957-2c303cece208
akti oadtjot ja de moadda máno
identity
Noto_Sans_Mono/static/NotoSansMono_Condensed-Bold.ttf
74
(1, 32, 36)
(230, 220, 255)
50
50
100
100
100
72
1,277
149
1,377
199
line_images/0015a633-0f74-46db-9ed6-66511df9efd7.jpg
augraphy_logs/0015a633-0f74-46db-9ed6-66511df9efd7.json
30
65
1,207
142
smj
0015bd53-0124-4b30-bae0-e1c4588d3504
tovna sjugniesåvva baakoej
cbbd6fbe-eb75-4efc-9c25-6afca4d73207
tovna sjugniesåvva baakoej
identity
Splash/Splash-Regular.ttf
82
(51, 49, 50)
(234, 217, 223)
50
50
100
100
94
74
977
174
1,077
224
line_images/0015bd53-0124-4b30-bae0-e1c4588d3504.jpg
augraphy_logs/0015bd53-0124-4b30-bae0-e1c4588d3504.json
36
42
919
142
sma
00167d52-6a66-4d7c-b3b2-048106717628
jienebh
b3242423-7fce-4cf4-8494-b50bbfc7b101
jienebh
identity
Ubuntu/Ubuntu-Medium.ttf
59
(76, 45, 34)
(185, 219, 255)
50
50
100
100
95
60
304
116
404
166
line_images/00167d52-6a66-4d7c-b3b2-048106717628.jpg
augraphy_logs/00167d52-6a66-4d7c-b3b2-048106717628.json
16
10
225
66
smj
00168608-4b1d-4eb4-9410-d65646a8c9f5
jakseme? Mejnie leam væjkele? Maam tjoerem bueriedidh?
35c81362-2286-4c06-b15c-9404eb4b5369
jakseme? Mejnie leam væjkele? Maam tjoerem bueriedidh?
identity
Mansalva/Mansalva-Regular.ttf
79
(29, 60, 51)
(167, 247, 158)
50
50
100
100
100
72
2,112
168
2,212
218
line_images/00168608-4b1d-4eb4-9410-d65646a8c9f5.jpg
augraphy_logs/00168608-4b1d-4eb4-9410-d65646a8c9f5.json
41
63
2,053
159
sma
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Synthetic text images for North, South, Lule and Inari Sámi

This dataset contains synthetic line images meant for fitting OCR models for North, South, Lule and Inari Sámi. Clean line images are created using Pillow and they are subsequently distorted using Augraphy [1].

Text sources

The text in this dataset comes from Giellatekno's corpus. Specifically, we used the data files of the converted/-directories of [2][3][4][5] (commit hashes 32f4af263cefae6ab9182638e2451ff151757adc, 00dac0e9e74b4a89214ad7d34de27b83362b3f3a, 4303edf80ae5eee2a036663c7b38756a0aa2a189, 7e3437ce8c7dc7692ccbd2505412c03e9e617be6).

Splits

The dataset is split randomly by file so 71 % of the files (307387 lines) are in the training split, 9 % of the files (40765 lines) are in the validation split and 20 % of the files (84534 lines) are in the test split. Each split has a unique set of typefaces and text/background colors.

Language distribution

The language distribution for the different languages are

Language Code Num train lines Num val lines Num test lines
sma 76971 10992 21981
sme 76949 10992 21990
smj 76970 9081 20465
smn 76497 9700 20098

Code

The code to create this dataset is available on our GitHub Repo (commit hash 90341bc19d6368c7848dcc2459065058486a89ea).

Referencing the dataset

If you use this dataset in your research, then please cite both "Enstad T, Trosterud T, Røsok MI, Beyer Y, Roald M. Comparative analysis of optical character recognition methods for Sámi texts from the National Library of Norway. Accepted for publication in Proceedings of the 25th Nordic Conference on Computational Linguistics (NoDaLiDa) 2025." (see the paper repository) and the SIKOR dataset the Sámi text is from: "SIKOR UiT The Arctic University of Norway and the Norwegian Saami Parliament's Saami text collection, http://gtweb.uit.no/korp, Version 01.12.2021 [Data set]." Also note that the SIKOR dataset to get Sámi text for the images is (CC-BY 3.0) licensed.

Dataset license

The dataset is licensed with a CC-BY 3.0 license.

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Size of downloaded dataset files:
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Number of rows:
432,686