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"bounds": {
"top_left": {
"x": 374,
"y": 588
},
"top_right": {
"x": 381,
"y": 589
},
"bottom_right": {
"x": 381,
"y": 602
},
"bottom_left": {
"x": 374,
"y": 602
},
"width": 7,
"height": 13.5
}
}
]
},
{
"text": "2.50 N",
"bounds": {
"top_left": {
"x": 421,
"y": 588
},
"top_right": {
"x": 470,
"y": 590
},
"bottom_right": {
"x": 469,
"y": 604
},
"bottom_left": {
"x": 420,
"y": 602
},
"width": 49,
"height": 14
},
"words": [
{
"text": "2.50",
"bounds": {
"top_left": {
"x": 422,
"y": 589
},
"top_right": {
"x": 452,
"y": 590
},
"bottom_right": {
"x": 452,
"y": 603
},
"bottom_left": {
"x": 422,
"y": 603
},
"width": 30,
"height": 13.5
}
},
{
"text": "N",
"bounds": {
"top_left": {
"x": 460,
"y": 590
},
"top_right": {
"x": 467,
"y": 590
},
"bottom_right": {
"x": 467,
"y": 604
},
"bottom_left": {
"x": 460,
"y": 604
},
"width": 7,
"height": 14
}
}
]
}
]
},
{
"text": "GV HNY GRMS 007874207253 F 1.28 N",
"chunks": [
{
"text": "GV HNY GRMS",
"bounds": {
"top_left": {
"x": 166,
"y": 599
},
"top_right": {
"x": 258,
"y": 600
},
"bottom_right": {
"x": 257,
"y": 615
},
"bottom_left": {
"x": 166,
"y": 614
},
"width": 91.5,
"height": 15
},
"words": [
{
"text": "GV",
"bounds": {
"top_left": {
"x": 167,
"y": 600
},
"top_right": {
"x": 182,
"y": 600
},
"bottom_right": {
"x": 181,
"y": 615
},
"bottom_left": {
"x": 166,
"y": 615
},
"width": 15,
"height": 15
}
},
{
"text": "HNY",
"bounds": {
"top_left": {
"x": 190,
"y": 600
},
"top_right": {
"x": 216,
"y": 600
},
"bottom_right": {
"x": 215,
"y": 615
},
"bottom_left": {
"x": 189,
"y": 615
},
"width": 26,
"height": 15
}
},
{
"text": "GRMS",
"bounds": {
"top_left": {
"x": 223,
"y": 600
},
"top_right": {
"x": 256,
"y": 601
},
"bottom_right": {
"x": 256,
"y": 616
},
"bottom_left": {
"x": 223,
"y": 616
},
"width": 33,
"height": 15.5
}
}
]
},
{
"text": "007874207253 F",
"bounds": {
"top_left": {
"x": 269,
"y": 601
},
"top_right": {
"x": 382,
"y": 602
},
"bottom_right": {
"x": 382,
"y": 617
},
"bottom_left": {
"x": 269,
"y": 615
},
"width": 113,
"height": 14.5
},
"words": [
{
"text": "007874207253",
"bounds": {
"top_left": {
"x": 272,
"y": 601
},
"top_right": {
"x": 367,
"y": 603
},
"bottom_right": {
"x": 366,
"y": 617
},
"bottom_left": {
"x": 271,
"y": 616
},
"width": 95,
"height": 14.5
}
},
{
"text": "F",
"bounds": {
"top_left": {
"x": 374,
"y": 603
},
"top_right": {
"x": 381,
"y": 603
},
"bottom_right": {
"x": 381,
"y": 617
},
"bottom_left": {
"x": 373,
"y": 617
},
"width": 7.5,
"height": 14
}
}
]
},
{
"text": "1.28 N",
"bounds": {
"top_left": {
"x": 419,
"y": 603
},
"top_right": {
"x": 470,
"y": 604
},
"bottom_right": {
"x": 470,
"y": 618
},
"bottom_left": {
"x": 419,
"y": 617
},
"width": 51,
"height": 14
},
"words": [
{
"text": "1.28",
"bounds": {
"top_left": {
"x": 422,
"y": 604
},
"top_right": {
"x": 452,
"y": 604
},
"bottom_right": {
"x": 452,
"y": 618
},
"bottom_left": {
"x": 422,
"y": 618
},
"width": 30,
"height": 14
}
},
{
"text": "N",
"bounds": {
"top_left": {
"x": 460,
"y": 605
},
"top_right": {
"x": 467,
"y": 605
},
"bottom_right": {
"x": 467,
"y": 618
},
"bottom_left": {
"x": 460,
"y": 618
},
"width": 7,
"height": 13
}
}
]
}
]
},
{
"text": "SUBTOTAL 139.44",
"chunks": [
{
"text": "SUBTOTAL",
"bounds": {
"top_left": {
"x": 309,
"y": 616
},
"top_right": {
"x": 374,
"y": 617
},
"bottom_right": {
"x": 374,
"y": 631
},
"bottom_left": {
"x": 309,
"y": 630
},
"width": 65,
"height": 14
},
"words": [
{
"text": "SUBTOTAL",
"bounds": {
"top_left": {
"x": 311,
"y": 616
},
"top_right": {
"x": 372,
"y": 618
},
"bottom_right": {
"x": 372,
"y": 631
},
"bottom_left": {
"x": 310,
"y": 630
},
"width": 61.5,
"height": 13.5
}
}
]
},
{
"text": "139.44",
"bounds": {
"top_left": {
"x": 404,
"y": 617
},
"top_right": {
"x": 454,
"y": 618
},
"bottom_right": {
"x": 454,
"y": 632
},
"bottom_left": {
"x": 404,
"y": 632
},
"width": 50,
"height": 14.5
},
"words": [
{
"text": "139.44",
"bounds": {
"top_left": {
"x": 406,
"y": 618
},
"top_right": {
"x": 453,
"y": 619
},
"bottom_right": {
"x": 453,
"y": 632
},
"bottom_left": {
"x": 406,
"y": 632
},
"width": 47,
"height": 13.5
}
}
]
}
]
},
{
"text": "TAX 1 7.000 % 4.58",
"chunks": [
{
"text": "TAX 1",
"bounds": {
"top_left": {
"x": 238,
"y": 630
},
"top_right": {
"x": 278,
"y": 631
},
"bottom_right": {
"x": 278,
"y": 644
},
"bottom_left": {
"x": 238,
"y": 644
},
"width": 40,
"height": 13.5
},
"words": [
{
"text": "TAX",
"bounds": {
"top_left": {
"x": 239,
"y": 630
},
"top_right": {
"x": 263,
"y": 630
},
"bottom_right": {
"x": 263,
"y": 644
},
"bottom_left": {
"x": 239,
"y": 643
},
"width": 24,
"height": 13.5
}
},
{
"text": "1",
"bounds": {
"top_left": {
"x": 272,
"y": 630
},
"top_right": {
"x": 277,
"y": 630
},
"bottom_right": {
"x": 277,
"y": 644
},
"bottom_left": {
"x": 271,
"y": 644
},
"width": 5.5,
"height": 14
}
}
]
},
{
"text": "7.000 %",
"bounds": {
"top_left": {
"x": 301,
"y": 630
},
"top_right": {
"x": 358,
"y": 631
},
"bottom_right": {
"x": 358,
"y": 645
},
"bottom_left": {
"x": 301,
"y": 644
},
"width": 57,
"height": 14
},
"words": [
{
"text": "7.000",
"bounds": {
"top_left": {
"x": 304,
"y": 630
},
"top_right": {
"x": 341,
"y": 632
},
"bottom_right": {
"x": 341,
"y": 646
},
"bottom_left": {
"x": 303,
"y": 645
},
"width": 37.5,
"height": 14.5
}
},
{
"text": "%",
"bounds": {
"top_left": {
"x": 350,
"y": 632
},
"top_right": {
"x": 358,
"y": 632
},
"bottom_right": {
"x": 358,
"y": 646
},
"bottom_left": {
"x": 349,
"y": 646
},
"width": 8.5,
"height": 14
}
}
]
},
{
"text": "4.58",
"bounds": {
"top_left": {
"x": 418,
"y": 633
},
"top_right": {
"x": 454,
"y": 634
},
"bottom_right": {
"x": 453,
"y": 647
},
"bottom_left": {
"x": 418,
"y": 647
},
"width": 35.5,
"height": 13.5
},
"words": [
{
"text": "4.58",
"bounds": {
"top_left": {
"x": 422,
"y": 633
},
"top_right": {
"x": 453,
"y": 633
},
"bottom_right": {
"x": 453,
"y": 647
},
"bottom_left": {
"x": 422,
"y": 647
},
"width": 31,
"height": 14
}
}
]
}
]
},
{
"text": "TOTAL 144.02",
"chunks": [
{
"text": "TOTAL",
"bounds": {
"top_left": {
"x": 333,
"y": 645
},
"top_right": {
"x": 371,
"y": 647
},
"bottom_right": {
"x": 370,
"y": 660
},
"bottom_left": {
"x": 333,
"y": 659
},
"width": 37.5,
"height": 13.5
},
"words": [
{
"text": "TOTAL",
"bounds": {
"top_left": {
"x": 335,
"y": 645
},
"top_right": {
"x": 370,
"y": 646
},
"bottom_right": {
"x": 370,
"y": 660
},
"bottom_left": {
"x": 334,
"y": 658
},
"width": 35.5,
"height": 13.5
}
}
]
},
{
"text": "144.02",
"bounds": {
"top_left": {
"x": 406,
"y": 647
},
"top_right": {
"x": 454,
"y": 647
},
"bottom_right": {
"x": 454,
"y": 662
},
"bottom_left": {
"x": 406,
"y": 661
},
"width": 48,
"height": 14.5
},
"words": [
{
"text": "144.02",
"bounds": {
"top_left": {
"x": 406,
"y": 647
},
"top_right": {
"x": 454,
"y": 648
},
"bottom_right": {
"x": 453,
"y": 662
},
"bottom_left": {
"x": 406,
"y": 662
},
"width": 47.5,
"height": 14.5
}
}
]
}
]
},
{
"text": "CASH TEND 150.02",
"chunks": [
{
"text": "CASH TEND",
"bounds": {
"top_left": {
"x": 292,
"y": 660
},
"top_right": {
"x": 375,
"y": 660
},
"bottom_right": {
"x": 375,
"y": 675
},
"bottom_left": {
"x": 292,
"y": 675
},
"width": 83,
"height": 15
},
"words": [
{
"text": "CASH",
"bounds": {
"top_left": {
"x": 293,
"y": 660
},
"top_right": {
"x": 324,
"y": 661
},
"bottom_right": {
"x": 323,
"y": 675
},
"bottom_left": {
"x": 292,
"y": 675
},
"width": 31,
"height": 14.5
}
},
{
"text": "TEND",
"bounds": {
"top_left": {
"x": 342,
"y": 661
},
"top_right": {
"x": 373,
"y": 661
},
"bottom_right": {
"x": 372,
"y": 675
},
"bottom_left": {
"x": 342,
"y": 675
},
"width": 30.5,
"height": 14
}
}
]
},
{
"text": "150.02",
"bounds": {
"top_left": {
"x": 404,
"y": 661
},
"top_right": {
"x": 454,
"y": 661
},
"bottom_right": {
"x": 454,
"y": 677
},
"bottom_left": {
"x": 404,
"y": 678
},
"width": 50,
"height": 16.5
},
"words": [
{
"text": "150.02",
"bounds": {
"top_left": {
"x": 405,
"y": 662
},
"top_right": {
"x": 454,
"y": 662
},
"bottom_right": {
"x": 454,
"y": 677
},
"bottom_left": {
"x": 404,
"y": 678
},
"width": 49.5,
"height": 15.5
}
}
]
}
]
},
{
"text": "CHANGE DUE 6.00",
"chunks": [
{
"text": "CHANGE DUE",
"bounds": {
"top_left": {
"x": 289,
"y": 675
},
"top_right": {
"x": 374,
"y": 675
},
"bottom_right": {
"x": 374,
"y": 690
},
"bottom_left": {
"x": 289,
"y": 690
},
"width": 85,
"height": 15
},
"words": [
{
"text": "CHANGE",
"bounds": {
"top_left": {
"x": 292,
"y": 676
},
"top_right": {
"x": 340,
"y": 676
},
"bottom_right": {
"x": 340,
"y": 690
},
"bottom_left": {
"x": 292,
"y": 690
},
"width": 48,
"height": 14
}
},
{
"text": "DUE",
"bounds": {
"top_left": {
"x": 349,
"y": 676
},
"top_right": {
"x": 372,
"y": 676
},
"bottom_right": {
"x": 372,
"y": 690
},
"bottom_left": {
"x": 349,
"y": 690
},
"width": 23,
"height": 14
}
}
]
},
{
"text": "6.00",
"bounds": {
"top_left": {
"x": 419,
"y": 678
},
"top_right": {
"x": 453,
"y": 678
},
"bottom_right": {
"x": 453,
"y": 692
},
"bottom_left": {
"x": 420,
"y": 693
},
"width": 33.5,
"height": 14.5
},
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"text": "6.00",
"bounds": {
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"y": 678
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"top_right": {
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},
"bottom_right": {
"x": 453,
"y": 692
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"bottom_left": {
"x": 420,
"y": 693
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"width": 32.5,
"height": 14.5
}
}
]
}
]
},
{
"text": "# ITEMS SOLD 26",
"chunks": [
{
"text": "# ITEMS SOLD 26",
"bounds": {
"top_left": {
"x": 249,
"y": 689
},
"top_right": {
"x": 376,
"y": 690
},
"bottom_right": {
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"y": 706
},
"bottom_left": {
"x": 248,
"y": 705
},
"width": 127.5,
"height": 16
},
"words": [
{
"text": "#",
"bounds": {
"top_left": {
"x": 251,
"y": 690
},
"top_right": {
"x": 260,
"y": 690
},
"bottom_right": {
"x": 259,
"y": 705
},
"bottom_left": {
"x": 251,
"y": 705
},
"width": 8.5,
"height": 15
}
},
{
"text": "ITEMS",
"bounds": {
"top_left": {
"x": 269,
"y": 690
},
"top_right": {
"x": 308,
"y": 691
},
"bottom_right": {
"x": 308,
"y": 706
},
"bottom_left": {
"x": 268,
"y": 705
},
"width": 39.5,
"height": 15
}
},
{
"text": "SOLD",
"bounds": {
"top_left": {
"x": 316,
"y": 691
},
"top_right": {
"x": 348,
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},
"bottom_right": {
"x": 348,
"y": 706
},
"bottom_left": {
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}
},
{
"text": "26",
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"top_right": {
"x": 372,
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},
"bottom_right": {
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"y": 705
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"bottom_left": {
"x": 357,
"y": 706
},
"width": 15,
"height": 14.5
}
}
]
}
]
},
{
"text": "TC# 0783 6080 4072 3416 2495 5",
"chunks": [
{
"text": "TC# 0783 6080 4072 3416 2495 5",
"bounds": {
"top_left": {
"x": 192,
"y": 703
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"x": 438,
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"bottom_right": {
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"bottom_left": {
"x": 192,
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},
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"text": "TC#",
"bounds": {
"top_left": {
"x": 193,
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"top_right": {
"x": 218,
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"x": 218,
"y": 720
},
"bottom_left": {
"x": 194,
"y": 720
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"width": 24.5,
"height": 16
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},
{
"text": "0783",
"bounds": {
"top_left": {
"x": 225,
"y": 704
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"top_right": {
"x": 259,
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"bottom_right": {
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"bottom_left": {
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},
{
"text": "6080",
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"x": 266,
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"x": 300,
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"bottom_right": {
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"y": 721
},
"bottom_left": {
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"y": 721
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"width": 33.5,
"height": 17
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{
"text": "4072",
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"y": 705
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"y": 705
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"bottom_right": {
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"y": 721
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"bottom_left": {
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"y": 721
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"width": 33.5,
"height": 16
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},
{
"text": "3416",
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"x": 348,
"y": 705
},
"top_right": {
"x": 380,
"y": 705
},
"bottom_right": {
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"y": 722
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"bottom_left": {
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"y": 721
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"width": 32,
"height": 16.5
}
},
{
"text": "2495",
"bounds": {
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"x": 389,
"y": 706
},
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"y": 706
},
"bottom_right": {
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"y": 723
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"bottom_left": {
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"width": 31,
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}
},
{
"text": "5",
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"y": 706
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"top_right": {
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"bottom_left": {
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"width": 8.5,
"height": 17
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]
}
]
},
{
"text": "04/27/19 12:59:46",
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"text": "04/27/19",
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"text": "12:59:46",
"bounds": {
"top_left": {
"x": 330,
"y": 763
},
"top_right": {
"x": 395,
"y": 765
},
"bottom_right": {
"x": 395,
"y": 779
},
"bottom_left": {
"x": 330,
"y": 780
},
"width": 65,
"height": 15.5
}
}
]
}
]
},
{
"text": "Scan with Walmart app to save receipts",
"chunks": [
{
"text": "Scan with Walmart app to save receipts",
"bounds": {
"top_left": {
"x": 154,
"y": 779
},
"top_right": {
"x": 469,
"y": 782
},
"bottom_right": {
"x": 469,
"y": 801
},
"bottom_left": {
"x": 154,
"y": 796
},
"width": 315,
"height": 18
},
"words": [
{
"text": "Scan",
"bounds": {
"top_left": {
"x": 155,
"y": 780
},
"top_right": {
"x": 188,
"y": 779
},
"bottom_right": {
"x": 188,
"y": 797
},
"bottom_left": {
"x": 155,
"y": 797
},
"width": 33,
"height": 17.5
}
},
{
"text": "with",
"bounds": {
"top_left": {
"x": 196,
"y": 779
},
"top_right": {
"x": 230,
"y": 779
},
"bottom_right": {
"x": 230,
"y": 796
},
"bottom_left": {
"x": 196,
"y": 796
},
"width": 34,
"height": 17
}
},
{
"text": "Walmart",
"bounds": {
"top_left": {
"x": 238,
"y": 779
},
"top_right": {
"x": 298,
"y": 780
},
"bottom_right": {
"x": 298,
"y": 796
},
"bottom_left": {
"x": 237,
"y": 796
},
"width": 60.5,
"height": 16.5
}
},
{
"text": "app",
"bounds": {
"top_left": {
"x": 305,
"y": 780
},
"top_right": {
"x": 329,
"y": 780
},
"bottom_right": {
"x": 329,
"y": 797
},
"bottom_left": {
"x": 305,
"y": 796
},
"width": 24,
"height": 16.5
}
},
{
"text": "to",
"bounds": {
"top_left": {
"x": 338,
"y": 781
},
"top_right": {
"x": 354,
"y": 781
},
"bottom_right": {
"x": 353,
"y": 797
},
"bottom_left": {
"x": 338,
"y": 797
},
"width": 15.5,
"height": 16
}
},
{
"text": "save",
"bounds": {
"top_left": {
"x": 363,
"y": 781
},
"top_right": {
"x": 394,
"y": 782
},
"bottom_right": {
"x": 394,
"y": 798
},
"bottom_left": {
"x": 362,
"y": 797
},
"width": 31.5,
"height": 16
}
},
{
"text": "receipts",
"bounds": {
"top_left": {
"x": 402,
"y": 783
},
"top_right": {
"x": 469,
"y": 786
},
"bottom_right": {
"x": 469,
"y": 801
},
"bottom_left": {
"x": 402,
"y": 798
},
"width": 67,
"height": 15
}
}
]
}
]
}
]
}
]
}AI Optical character recognition (OCR)
Mix the power of OCR AI with fine-tuned LLMs to extract and accurately correct text from images and documents
Structured data
Get structured data in JSON format categorized by line and word level, including pixel coordinates for each word to form bounding boxes
File & document types
File support including PDF, PNG, JPEG from passports, invoices, complex images and more
Blazing fast speed
Run millions of images in seconds with the latest AI models and GPUs globally distributed for low latency
Tagging
Get image AI tagging classification for your images to understand the content and context of the image
Secure and private
Keep your data secure and private with end-to-end encryption and containerized AI models for processing data
Integrate vOCR on any platform
Easy to use REST APIs that work out of the box in every language and framework with fully managed caching, logging and authentication
javascript
python
php
ruby
go
java
swift
dart
kotlin
csharp
curl
import { JigsawStack } from "jigsawstack";
const jigsaw = JigsawStack({
apiKey: "sk39wo393.....32ncsmw9339RNj3"
});
const response = await jigsaw.vision.vocr({
"url": "https://jigsawstack.com/preview/vocr-example.jpg",
"prompt": [
"total_price",
"tax",
"highlighted_item_name"
]
})$
npm i jigsawstack
What can you build with JigsawStack vOCR?
5 ways our customers use JigsawStack to build vOCR powered applications
KYC automation
Automate your KYC process by securely extracting text from documents to verify customer identity
Fraud detection
Detect fraudulent activities by analyzing risk factors in documents and images using AI tagging classification
Accessibility
Increase accessibility seamlessly by accurately extracting text from images without the need for manual transcription
Build document solutions
Powered by AI, build document solutions that can extract text from documents and images for various layouts
Healthcare or legal
Safely extract information from sensitive documents and images with end-to-end encryption for compliance and digital transformation
First class Developer Experience (DX)
Striking the right balance between code and dashboard
Logging and analytics on all APIs
Access real-time logs and analytics on all your APIs. Debug errors, track users, location maps, sessions, countries, IPs and 30+ data points
API key security control
Fine grained control over API keys. Whitelist domains with flexible wildcard support, set expiration date and limit access to specific APIs with unlimited keys
Fully typed SDKs
The best docs are the kind that you don't need. Fully typed SDKs with auto-completion and self explanatory params
Team and project management
Manage multiple projects and teams with access control. Invite unlimited team members and assign roles
Globally distributed models in 99+ locations
Access model APIs at blazing fast speeds on the edge network
Blazing fast
99.5% uptime with APIs latency reaching as low as 200ms globally
Simple scalable pricing
Scale up and down as you need without worrying about abused cost with usage based pricing
Consistency
Consistent request and response structure across all API services for predictable use
Up to date
Consistent training for all JigsawStack models to ensure the latest technology is always available without breaking changes
