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{"id":1028,"datatype":"1","titleimg":"[{\"name\": \"APY190730002.png\", \"url\": \"https://res.datatang.com/asset/productNew/APY190730002.png?Expires=2007353670&OSSAccessKeyId=LTAI5tQwXnJZbubgVfVa1ep9&Signature=0n1h5CswI46eZGTLeaIGSEbGbbY%3D\", \"size\": 2048, \"progress\": 100}]","type1":"147","type1str":null,"type2":"150","type2str":null,"dataname":"4,601 Images-22 Kinds of Bills OCR Data","datazy":[{"title":"Data size","desc":"Data size","content":"4,601 images, 22 kinds"},{"title":"Collection environment","desc":"Collection environment","content":"pure color background"},{"title":"Data diversity","desc":"Data diversity","content":"including multiple types of bills, multiple provinces"},{"title":"Device","desc":"Device","content":"cellphone"},{"title":"Image Parameter","desc":"Image Parameter","content":"the image data is in .jpg format, the annotation file is in .json format"},{"title":"Annotation content","desc":"Annotation content","content":"line-level quadrilateral bounding box annotation, line-level transcription for the texts"},{"title":"Accuracy","desc":"Accuracy","content":"the error bound of each vertex of quadrilateral bounding box is within 5 pixels, which is a qualified annotation, the accuracy of bounding boxes is not less than 97%; the texts transcription accuracy is not less than 97%"}],"datatag":"Multiple types of bills,Multiple provinces","technologydoc":null,"downurl":null,"datainfo":null,"standard":null,"dataylurl":null,"flag":null,"publishtime":null,"createby":null,"createtime":null,"ext1":null,"samplestoreloc":null,"hosturl":null,"datasize":null,"industryPlan":null,"keyInformation":["4,601 images","22 kings of bills","multiple provinces"],"samplePresentation":[],"officialSummary":"4,601 Images-22 Kinds of Bills OCR Data. The data background is pure color. The data covers 22 kinds of bills of multiple provinces. In terms of annotation, line-level quadrilateral bounding box annotation, line-level transcription for the texts were annotated in the data. The data can be used for tasks such as OCR for bills.","dataexampl":null,"datakeyword":["OCR"," bill annotation"," bill transcription"," multiple types of bills","multiple provinces"],"isDelete":null,"ids":null,"idsList":null,"datasetCode":null,"productStatus":null,"tagTypeEn":"Data Type,Language","tagTypeZh":null,"website":null,"samplePresentationList":null,"datazyList":null,"keyInformationList":null,"dataexamplList":null,"bgimg":null,"datazyScriptList":null,"datakeywordListString":null,"sourceShowPage":"ocr","BGimg":"","voiceBg":["/shujutang/static/image/comm/audio_bg.webp","/shujutang/static/image/comm/audio_bg2.webp","/shujutang/static/image/comm/audio_bg3.webp","/shujutang/static/image/comm/audio_bg4.webp","/shujutang/static/image/comm/audio_bg5.webp"]}
4,601 Images-22 Kinds of Bills OCR Data. The data background is pure color. The data covers 22 kinds of bills of multiple provinces. In terms of annotation, line-level quadrilateral bounding box annotation, line-level transcription for the texts were annotated in the data. The data can be used for tasks such as OCR for bills.
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Specifications
Data size
4,601 images, 22 kinds
Collection environment
pure color background
Data diversity
including multiple types of bills, multiple provinces
Device
cellphone
Image Parameter
the image data is in .jpg format, the annotation file is in .json format
Annotation content
line-level quadrilateral bounding box annotation, line-level transcription for the texts
Accuracy
the error bound of each vertex of quadrilateral bounding box is within 5 pixels, which is a qualified annotation, the accuracy of bounding boxes is not less than 97%; the texts transcription accuracy is not less than 97%
Specifications
Sample
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