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OCR Receipts from Grocery Stores Text Detection - retail dataset
The Grocery Store Receipts Dataset is a collection of photos captured from various grocery store receipts. This dataset is specifically designed for tasks related to Optical Character Recognition (OCR) and is useful for retail.
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Each image in the dataset is accompanied by bounding box annotations, indicating the precise locations of specific text segments on the receipts. The text segments are categorized into four classes: item, store, date_time and total.
Dataset structure
- images - contains of original images of receipts
- boxes - includes bounding box labeling for the original images
- annotations.xml - contains coordinates of the bounding boxes and detected text, created for the original photo
Data Format
Each image from images folder is accompanied by an XML-annotation in the annotations.xml file indicating the coordinates of the bounding boxes and detected text . For each point, the x and y coordinates are provided.
Classes:
- store - name of the grocery store
- item - item in the receipt
- date_time - date and time of the receipt
- total - total price of the receipt
Text Detection in the Receipts might be made in accordance with your requirements.
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keywords: receipts reading, retail dataset, consumer goods dataset, grocery store dataset, supermarket dataset, deep learning, retail store management, pre-labeled dataset, annotations, text detection, text recognition, optical character recognition, document text recognition, detecting text-lines, object detection, scanned documents, deep-text-recognition, text area detection, text extraction, images dataset, image-to-text, object detection
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