|
--- |
|
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](https://trainingdata.pro/datasets/ocr-receipts-text-detection?utm_source=huggingface&utm_medium=cpc&utm_campaign=ocr-receipts-text-detection)** 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](https://trainingdata.pro/datasets/ocr-receipts-text-detection?utm_source=huggingface&utm_medium=cpc&utm_campaign=ocr-receipts-text-detection)** to discuss your requirements, learn about the price and buy the dataset |
|
|
|
## **[TrainingData](https://trainingdata.pro/datasets/ocr-receipts-text-detection?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** |
|
|
|
*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* |
