metadata

language:
  - en
license: cc-by-nc-nd-4.0
task_categories:
  - image-to-text
  - object-detection
tags:
  - code
  - finance
dataset_info:
  features:
    - name: id
      dtype: int32
    - name: name
      dtype: string
    - name: image
      dtype: image
    - name: mask
      dtype: image
    - name: width
      dtype: uint16
    - name: height
      dtype: uint16
    - name: shapes
      sequence:
        - name: label
          dtype:
            class_label:
              names:
                '0': receipt
                '1': shop
                '2': item
                '3': date_time
                '4': total
        - name: type
          dtype: string
        - name: points
          sequence:
            sequence: float32
        - name: rotation
          dtype: float32
        - name: occluded
          dtype: uint8
        - name: attributes
          sequence:
            - name: name
              dtype: string
            - name: text
              dtype: string
  splits:
    - name: train
      num_bytes: 55510934
      num_examples: 20
  download_size: 54557192
  dataset_size: 55510934

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.

💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on TrainingData to buy the dataset

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.

💴 Buy the Dataset: This is just an example of the data. Leave a request on https://trainingdata.pro/datasets to discuss your requirements, learn about the price and buy the dataset

TrainingData provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets

TrainingData's GitHub: https://github.com/trainingdata-pro

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