Barcode Scanning Video Dataset

Project Overview:

Objective

GTS mission was to assemble a specialized video dataset aimed at revolutionizing barcode scanning technology. Barcode Scanning Video Dataset focuses on improving machine learning models for more efficient and precise barcode detection in various real-world scenarios.

Scope

We meticulously gathered and annotated a vast array of videos, capturing barcodes in multiple environments. This variety ensures our dataset’s adaptability and enhances the training effectiveness of machine learning models.

Barcode Scanning Video Dataset
Barcode Scanning Video Dataset
Barcode Scanning Video Dataset
Barcode Scanning Video Dataset

Sources

  • Retail store environments: products on shelves, cashier checkout scenarios.
  • Warehouses: inventory checks, package labelling.
  • Home settings: scanning items for online shopping apps, personal inventory.
  • Outdoor scenarios: scanning tickets at events, QR codes on ads.
Barcode Scanning Video Dataset
Barcode Scanning Video Dataset

Data Collection Metrics

  • Total Video Clips: 50,000
  • Retail Store Clips: 20,000
  • Warehouse Clips: 10,000
  • Home Setting Clips: 12,000
  • Outdoor Scenarios Clips: 8,000

Annotation Process

Stages

  1. Bounding Boxes: Drawing boxes around barcodes in each video frame.
  2. Barcode Type Classification: Labeling barcode types (e.g., UPC, QR, Code128).
  3. Transcription: Providing the exact digital equivalent of the barcode where feasible.
  4. Environmental Tags: Marking factors like lighting conditions (low-light, glared) and obstructions.
  5. Orientation Tags: Noting barcode orientations (e.g., tilted, upside-down).

Annotation Metrics

  • Total Annotations: 1,250,000 (considering average 25 frames annotated per video)
  • Bounding Boxes: 800,000
  • Barcode Classifications: 200,000
  • Transcriptions: 100,000
  • Environmental Tags: 100,000
  • Orientation Tags: 50,000
Barcode Scanning Video Dataset
Barcode Scanning Video Dataset
Barcode Scanning Video Dataset

Quality Assurance

Stages

Expert Review: Engaging experts in barcode technology for annotation reviews.
Consistency Checks: Automated systems to verify transcription accuracy and bounding box alignment.
Inter-annotator Agreement: Multiple annotators assigned overlapping dataset sections to guarantee uniformity.

QA Metrics

  • Annotations Reviewed by Experts: 125,000 (10% of total annotations)
  • Inconsistencies Identified and Rectified: 25,000 (2% of total annotations)

Conclusion

The Barcode Scanning Video Dataset project culminated in the successful aggregation and annotation of a diverse set of videos tailored for barcode recognition. Through methodical processes and an emphasis on quality, this dataset is poised to be a cornerstone in advancing barcode scanning technology, ensuring faster, more versatile, and accurate recognition across numerous applications.

quality dataset

Quality Data Creation

Guaranteed TAT​

Guaranteed TAT

ISO 9001:2015, ISO/IEC 27001:2013 Certified​

ISO 9001:2015, ISO/IEC 27001:2013 Certified

HIPAA Compliance​

HIPAA Compliance

GDPR Compliance​

GDPR Compliance

Compliance and Security​

Compliance and Security

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