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1
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10
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100
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101
{"xml": "", "json": "\"{\\\"line_items\\\": {\\\"item_name\\\": \\\"ES CHOCO GREEN TEA\\\", \\\"item_quantity\\\": \\\"1\\\", \\\"item_value\\\": \\\"13.000\\\"}, \\\"subtotal\\\": {\\\"subtotal\\\": \\\"13.000\\\", \\\"tax\\\": \\\"1.300\\\"}, \\\"total\\\": {\\\"total\\\": \\\"14.300\\\", \\\"cash\\\": \\\"100.000\\\", \\\"change\\\": \\\"85.700\\\"}}\"", "kie": ""}
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102
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103
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104
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105
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106
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107
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108
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109
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11
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110
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111
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112
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113
{"xml": "", "json": "\"{\\\"line_items\\\": {\\\"item_name\\\": \\\"ICED CM\\\", \\\"item_value\\\": \\\"22,000\\\"}, \\\"total\\\": {\\\"cash\\\": \\\"22,000\\\"}}\"", "kie": ""}
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114
{"xml": "", "json": "\"{\\\"line_items\\\": {\\\"item_name\\\": \\\"Puyo 6 (Package)\\\", \\\"item_unit_price\\\": \\\"70,000\\\", \\\"item_quantity\\\": \\\"1x\\\", \\\"item_value\\\": \\\"70,000\\\", \\\"sub\\\": [{\\\"item_name\\\": \\\"Si1ky Lychee\\\", \\\"item_quantity\\\": \\\"2x\\\"}, {\\\"item_name\\\": \\\"Si1ky Mango\\\", \\\"item_quantity\\\": \\\"1x\\\"}, {\\\"item_name\\\": \\\"Si1ky Cotton Candy\\\", \\\"item_quantity\\\": \\\"1x\\\"}, {\\\"item_name\\\": \\\"Si1ky Green Tea\\\", \\\"item_quantity\\\": \\\"1x\\\"}, {\\\"item_name\\\": \\\"Si1ky Chocolate\\\", \\\"item_quantity\\\": \\\"1x\\\"}]}, \\\"subtotal\\\": {\\\"subtotal\\\": \\\"70,000\\\"}, \\\"total\\\": {\\\"total\\\": \\\"70,000\\\", \\\"change\\\": \\\"0\\\", \\\"creditcarditem_value\\\": \\\"70,000\\\"}}\"", "kie": ""}
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115
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116
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121
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128
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129
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130
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131
{"xml": "", "json": "\"{\\\"line_items\\\": [{\\\"item_name\\\": \\\"1001-Choco Bun\\\", \\\"item_unit_price\\\": \\\"22.000\\\", \\\"item_quantity\\\": \\\"x1\\\", \\\"item_value\\\": \\\"22.000\\\"}, {\\\"item_name\\\": \\\"6001-Plastic Bag Small\\\", \\\"item_unit_price\\\": \\\"0\\\", \\\"item_quantity\\\": \\\"x1\\\", \\\"item_value\\\": \\\"0\\\"}], \\\"total\\\": {\\\"total\\\": \\\"22.000\\\", \\\"cash\\\": \\\"50.000\\\", \\\"change\\\": \\\"28.000\\\", \\\"line_count\\\": \\\"2\\\"}}\"", "kie": ""}
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132
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133
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134
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135
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136
{"xml": "", "json": "\"{\\\"line_items\\\": {\\\"item_name\\\": \\\"SATE PADANG\\\", \\\"item_value\\\": \\\"60,000\\\"}, \\\"subtotal\\\": {\\\"subtotal\\\": \\\"60,000\\\", \\\"tax\\\": \\\"6,000\\\"}, \\\"total\\\": {\\\"total\\\": \\\"66,000\\\", \\\"cash\\\": \\\"100,000\\\", \\\"change\\\": \\\"34,000\\\", \\\"line_count\\\": \\\"1.00xITEMS\\\"}}\"", "kie": ""}
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137
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138
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139
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14
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140
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141
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142
{"xml": "", "json": "\"{\\\"line_items\\\": [{\\\"item_name\\\": \\\"Pillow Choco\\\", \\\"item_quantity\\\": \\\"1\\\", \\\"item_value\\\": \\\"18,000\\\"}, {\\\"item_name\\\": \\\"Pillow Cheese\\\", \\\"item_quantity\\\": \\\"1\\\", \\\"item_value\\\": \\\"18,000\\\"}, {\\\"item_name\\\": \\\"Pillow Kombi\\\", \\\"item_quantity\\\": \\\"1\\\", \\\"item_value\\\": \\\"19,500\\\"}], \\\"subtotal\\\": {\\\"subtotal\\\": \\\"55,500\\\", \\\"etc\\\": \\\"0\\\"}, \\\"total\\\": {\\\"total\\\": \\\"55,500\\\", \\\"creditcarditem_value\\\": \\\"55,500\\\", \\\"line_type\\\": \\\"3\\\", \\\"line_count\\\": \\\"3\\\"}}\"", "kie": ""}
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143
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144
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145
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146
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147
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149
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15
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150
{"xml": "", "json": "\"{\\\"line_items\\\": {\\\"item_name\\\": \\\"KFC Winger HC\\\", \\\"item_quantity\\\": \\\"1\\\", \\\"item_value\\\": \\\"20,000\\\"}, \\\"subtotal\\\": {\\\"subtotal\\\": [\\\"20,000\\\", \\\"20,000\\\"], \\\"tax\\\": \\\"2,000\\\"}, \\\"total\\\": {\\\"total\\\": \\\"22,000\\\", \\\"cash\\\": \\\"22,000\\\", \\\"line_count\\\": \\\"1\\\"}}\"", "kie": ""}
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151
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152
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153
{"xml": "", "json": "\"{\\\"line_items\\\": {\\\"item_name\\\": \\\"GIGA\\\", \\\"item_value\\\": \\\"Rp 57,000\\\", \\\"sub\\\": [{\\\"item_name\\\": \\\"CUP GIGA\\\"}, {\\\"item_name\\\": \\\"CHEESE\\\"}, {\\\"item_name\\\": \\\"S. CREAM\\\"}]}, \\\"total\\\": {\\\"total\\\": \\\"Rp 57,0000\\\", \\\"cash\\\": \\\"Rp 57,000\\\"}}\"", "kie": ""}
{"ocr_words": "['1818181', 'GIGA', 'Rp57,000', 'CUP GIGA', 'CHEESE', 'S.CREAM', 'TL', 'RP57000', 'CASH', 'Rp57,000']", "ocr_boxes": "[[[[585.0, 429.0], [716.0, 429.0], [716.0, 463.0], [585.0, 463.0]], ('1818181', 0.6574541330337524)], [[[27.0, 539.0], [144.0, 539.0], [144.0, 582.0], [27.0, 582.0]], ('GIGA', 0.9980373382568359)], [[[511.0, 536.0], [779.0, 533.0], [779.0, 579.0], [512.0, 582.0]], ('Rp57,000', 0.9595993757247925)], [[[30.0, 595.0], [262.0, 595.0], [262.0, 633.0], [30.0, 633.0]], ('CUP GIGA', 0.9398663640022278)], [[[30.0, 649.0], [201.0, 649.0], [201.0, 687.0], [30.0, 687.0]], ('CHEESE', 0.9981423020362854)], [[[31.0, 703.0], [235.0, 703.0], [235.0, 741.0], [31.0, 741.0]], ('S.CREAM', 0.9934402108192444)], [[[116.0, 753.0], [184.0, 753.0], [184.0, 796.0], [116.0, 796.0]], ('TL', 0.9965063333511353)], [[[261.0, 757.0], [774.0, 767.0], [773.0, 809.0], [260.0, 799.0]], ('RP57000', 0.9001103639602661)], [[[113.0, 805.0], [235.0, 811.0], [234.0, 855.0], [112.0, 850.0]], ('CASH', 0.9980565309524536)], [[[514.0, 818.0], [785.0, 824.0], [784.0, 870.0], [513.0, 864.0]], ('Rp57,000', 0.9485452175140381)]]", "ocr_labels": ""}

Dataset Card for "invoices-and-receipts_ocr_v2"

Usage

from datasets import load_dataset

dataset = load_dataset("mychen76/invoices-and-receipts_ocr_v2")
dataset

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Collection including mychen76/invoices-and-receipts_ocr_v2