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--- |
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language: |
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- en |
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license: cc-by-nc-nd-4.0 |
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task_categories: |
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- image-to-text |
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tags: |
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- code |
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- finance |
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dataset_info: |
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features: |
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- name: id |
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dtype: int32 |
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- name: name |
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dtype: string |
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- name: image |
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dtype: image |
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- name: mask |
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dtype: image |
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- name: width |
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dtype: uint16 |
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- name: height |
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dtype: uint16 |
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- name: shapes |
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sequence: |
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- name: label |
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dtype: |
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class_label: |
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names: |
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'0': Barcode |
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- name: type |
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dtype: string |
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- name: points |
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sequence: |
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sequence: float32 |
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- name: rotation |
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dtype: float32 |
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- name: occluded |
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dtype: uint8 |
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- name: attributes |
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sequence: |
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- name: name |
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dtype: string |
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- name: text |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 284124996 |
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num_examples: 11 |
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download_size: 283531190 |
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dataset_size: 284124996 |
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--- |
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# OCR Barcodes Detection - Object Detection Dataset |
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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. |
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# 💴 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 |
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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. |
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# 💴 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 |
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# Dataset structure |
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- **images** - contains of original images of goods |
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- **boxes** - includes labeling for the original images |
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- **annotations.xml** - contains coordinates of the polygons and detected text of the barcode, created for the original photo |
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# Data Format |
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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. |
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# Barcodes Detection might be made in accordance with your requirements. |
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## **[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 |
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More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets** |
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TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets** |
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*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* |
