task_categories:image-to-text task_categories:object-detection language:en license:cc-by-nc-nd-4.0 code finance region:us
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.
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**.
@InProceedings{huggingface:dataset,
title = {ocr-receipts-text-detection},
author = {TrainingDataPro},
year = {2023}
}
---
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
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. 

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**.

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F4d5c600731265119bb28668959d5c357%2FFrame%2016.png?generation=1695111877176656&alt=media)

# Get the dataset

### This is just an example of the data

Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=ocr-receipts-text-detection) to discuss your requirements, learn about the price and buy the dataset.

# 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

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F62643adde75dd6ca4e3f26909174ae40%2Fcarbon.png?generation=1695112527839805&alt=media)

# Text Detection in the Receipts might be made in accordance with your requirements.

## [TrainingData](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=ocr-receipts-text-detection) 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**