File size: 4,050 Bytes
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---
language:
- en
license: cc-by-nc-nd-4.0
task_categories:
- image-to-text
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': Barcode
- 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: 284124996
num_examples: 11
download_size: 283531190
dataset_size: 284124996
---
# OCR Barcodes Detection - Object Detection Dataset
The dataset consists of images of various **grocery goods** that have **barcode labels**. Each image in the dataset is annotated with polygons around the barcode labels. Additionally, Optical Character Recognition (**OCR**) has been performed on each bounding box to extract the barcode numbers.
# 💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on **[TrainingData](https://trainingdata.pro/datasets?utm_source=huggingface&utm_medium=cpc&utm_campaign=ocr-barcodes-detection)** to buy the dataset
The dataset is particularly valuable for applications in *grocery retail, inventory management, supply chain optimization, and automated checkout systems*. It serves as a valuable resource for researchers, developers, and businesses working on barcode-related projects in the retail and logistics domains.
# 💴 Buy the Dataset: This is just an example of the data. Leave a request on **[https://trainingdata.pro/datasets](https://trainingdata.pro/datasets?utm_source=huggingface&utm_medium=cpc&utm_campaign=ocr-barcodes-detection)** to discuss your requirements, learn about the price and buy the dataset
# Dataset structure
- **images** - contains of original images of goods
- **boxes** - includes labeling for the original images
- **annotations.xml** - contains coordinates of the polygons and detected text of the barcode, 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 polygons and detected text . For each point, the x and y coordinates are provided.
# Barcodes Detection might be made in accordance with your requirements.
## **[TrainingData](https://trainingdata.pro/datasets?utm_source=huggingface&utm_medium=cpc&utm_campaign=ocr-barcodes-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-datamarket/TrainingData_All_datasets**
*keywords: barcode, barcode detection, annotated dataset, barcode images, barcode localization, deep learning, barcode identification, data-driven classifier, barcode reader, barcode scanner, decoder, qr code, 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* |