Figure 1: The Document Information Extraction generally first looks for bar or QR codes in the document (Step 1), then applies OCR (Step 2), looks for keywords (Step 3), applies DocReader (Step 4) and Chargrid (Step 5) and then does the data enrichment with given metadata (Step 6).
Figure 2: OCR Endpoint of the Swagger UI of the Document Information Extraction Service.
First the lines of the document are detected.
{
"results": {
"1": [
{
"word_boxes": [
{
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]
],
"content": "�"
},
{
"bbox": [
[
398,
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],
[
894,
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]
],
"content": "Sights"
}
],
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]
]
},
{
"word_boxes": [
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"content": "Downtown"
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{
"bbox": [
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777,
303
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1219,
447
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],
"content": "Toronto"
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{
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429
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],
"content": "is"
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{
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],
"content": "an"
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{
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[
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],
"content": "easy-to-navigate"
}
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"bbox": [
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{
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"content": "grid,"
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{
"bbox": [
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],
"content": "bounded"
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{
"bbox": [
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"content": "by"
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{
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"content": "hodgepodge"
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{
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468
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"content": "of"
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{
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"word_boxes": [
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"content": "mian,"
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{
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"content": "ethnic"
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{
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"content": "and"
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{
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1206,
613
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[
1644,
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],
"content": "historic"
},
{
"bbox": [
[
1722,
603
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[
2484,
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"content": "neighborhoods"
}
],
"bbox": [
[
66,
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[
2484,
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{
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{
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[
492,
794
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[
623,
953
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"content": "St,"
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{
"bbox": [
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694,
791
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872,
950
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"content": "the"
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{
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"content": "world's"
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{
"bbox": [
[
1404,
777
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[
1863,
940
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],
"content": "longest,"
},
{
"bbox": [
[
1936,
770
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[
2337,
933
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],
"content": "dissects"
},
{
"bbox": [
[
2384,
768
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[
2502,
926
]
],
"content": "the"
}
],
"bbox": [
[
76,
768
],
[
2502,
959
]
]
},
{
"word_boxes": [
{
"bbox": [
[
76,
973
],
[
310,
1113
]
],
"content": "city:"
},
{
"bbox": [
[
384,
969
],
[
583,
1108
]
],
"content": "any"
},
{
"bbox": [
[
643,
958
],
[
1232,
1104
]
],
"content": "downtown"
},
{
"bbox": [
[
1294,
951
],
[
1626,
1093
]
],
"content": "street"
},
{
"bbox": [
[
1686,
946
],
[
1939,
1086
]
],
"content": "with"
},
{
"bbox": [
[
2006,
943
],
[
2136,
1081
]
],
"content": "an"
},
{
"bbox": [
[
2211,
938
],
[
2395,
1078
]
],
"content": "East"
},
{
"bbox": [
[
2437,
937
],
[
2503,
1074
]
],
"content": "or"
}
],
"bbox": [
[
76,
937
],
[
2503,
1113
]
]
},
{
"word_boxes": [
{
"bbox": [
[
86,
1133
],
[
366,
1269
]
],
"content": "West"
},
{
"bbox": [
[
418,
1123
],
[
1063,
1265
]
],
"content": "designation"
},
{
"bbox": [
[
1122,
1118
],
[
1442,
1255
]
],
"content": "refers"
},
{
"bbox": [
[
1493,
1116
],
[
1607,
1250
]
],
"content": "to"
},
{
"bbox": [
[
1661,
1113
],
[
1805,
1248
]
],
"content": "its"
},
{
"bbox": [
[
1862,
1106
],
[
2294,
1245
]
],
"content": "position"
},
{
"bbox": [
[
2339,
1103
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[
2510,
1238
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],
"content": "rela-"
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{
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294,
1429
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"content": "tive"
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{
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455,
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"content": "to"
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{
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517,
1286
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[
866,
1423
]
],
"content": "Yonge."
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{
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[
928,
1280
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[
1287,
1418
]
],
"content": "Unlike"
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{
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1343,
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1412
]
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"content": "New"
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{
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1954,
1407
]
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"content": "York,"
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{
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[
2004,
1266
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[
2280,
1402
]
],
"content": "there"
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{
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[
2321,
1264
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[
2390,
1398
]
],
"content": "is"
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{
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[
2429,
1263
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[
2517,
1396
]
],
"content": "no"
}
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[
85,
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],
[
2517,
1429
]
]
},
{
"word_boxes": [
{
"bbox": [
[
92,
1447
],
[
699,
1578
]
],
"content": "distinction"
},
{
"bbox": [
[
793,
1441
],
[
1251,
1570
]
],
"content": "between"
},
{
"bbox": [
[
1338,
1437
],
[
1526,
1563
]
],
"content": "the"
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{
"bbox": [
[
1614,
1430
],
[
2193,
1560
]
],
"content": "directions"
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{
"bbox": [
[
2266,
1428
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[
2353,
1552
]
],
"content": "of"
},
{
"bbox": [
[
2419,
1426
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[
2522,
1551
]
],
"content": "av"
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[
92,
1426
],
[
2522,
1578
]
]
},
{
"word_boxes": [
{
"bbox": [
[
97,
1618
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[
426,
1758
]
],
"content": "enues"
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{
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[
474,
1615
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[
675,
1753
]
],
"content": "and"
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[
721,
1609
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[
1114,
1750
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],
"content": "streets:"
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{
"bbox": [
[
1162,
1602
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[
1635,
1744
]
],
"content": "Spadina"
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{
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[
1692,
1598
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[
1902,
1737
]
],
"content": "Ave"
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{
"bbox": [
[
1979,
1594
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[
2201,
1733
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],
"content": "runs"
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{
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[
2242,
1590
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[
2531,
1729
]
],
"content": "north-"
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],
"bbox": [
[
97,
1590
],
[
2531,
1758
]
]
},
{
"word_boxes": [
{
"bbox": [
[
101,
1774
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[
452,
1914
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],
"content": "south,"
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{
"bbox": [
[
541,
1771
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[
719,
1909
]
],
"content": "but"
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{
"bbox": [
[
810,
1764
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[
1305,
1906
]
],
"content": "Danforth"
},
{
"bbox": [
[
1395,
1761
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[
1612,
1900
]
],
"content": "Ave"
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{
"bbox": [
[
1729,
1757
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[
1976,
1896
]
],
"content": "runs"
},
{
"bbox": [
[
2057,
1750
],
[
2535,
1892
]
],
"content": "east-west"
}
],
"bbox": [
[
101,
1750
],
[
2535,
1914
]
]
},
{
"word_boxes": [
{
"bbox": [
[
114,
1927
],
[
507,
2071
]
],
"content": "There's"
},
{
"bbox": [
[
570,
1925
],
[
775,
2069
]
],
"content": "also"
},
{
"bbox": [
[
835,
1925
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[
888,
2068
]
],
"content": "a"
},
{
"bbox": [
[
949,
1923
],
[
1263,
2067
]
],
"content": "street"
},
{
"bbox": [
[
1329,
1921
],
[
1662,
2066
]
],
"content": "called"
},
{
"bbox": [
[
1742,
1919
],
[
2171,
2064
]
],
"content": "Avenue"
},
{
"bbox": [
[
2235,
1918
],
[
2389,
2061
]
],
"content": "Rd."
},
{
"bbox": [
[
2435,
1917
],
[
2539,
2061
]
],
"content": "Go"
}
],
"bbox": [
[
114,
1917
],
[
2538,
2071
]
]
},
{
"word_boxes": [
{
"bbox": [
[
131,
2084
],
[
485,
2218
]
],
"content": "figure!"
}
],
"bbox": [
[
131,
2084
],
[
485,
2218
]
]
}
]
}
}
OCR Output of the image above using the DOX API
Figure 3: Network Structure of DocReader's Encoder and Spatial Aware Memory.
Figure 4: Network Architecture of DocReader's Decoder with Attention Layer.
Figure 5: Attention weights projected back onto input document.
Figure 6: Network Architecture of Chargrid.
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