Damaged Car Image Dataset

Project Overview:

Objective

Our team successfully built an extensive dataset of car images showcasing diverse types of damage. This dataset is now aiding groundbreaking advancements in AI models for insurance evaluations, repair cost calculations, and accident analysis.

Scope

We undertook a comprehensive project to gather images of cars with varying damage levels. Our collection includes everything from minor scratches to completely wrecked vehicles, captured under different environmental and lighting conditions. Each image is meticulously annotated to detail the damage type and severity.

Damaged Car Image Dataset
Damaged Car Image Dataset
Damaged Car Image Dataset
Damaged Car Image Dataset

Sources

  • Insurance claim photographs.
  • Collaborations with body shops and auto repair centers.
  • Partnership with law enforcement for accident scene images.
  • A platform for users to submit their images.
Damaged Car Image Dataset
Damaged Car Image Dataset

Data Collection Metrics

  • Total Damaged Car Images Collected: 350,000
  • Minor Damages: 125,000
  • Moderate Damages: 150,000
  • Severe Damages: 50,000
  • Total Wrecks: 25,000

Annotation Process

Stages

  1. Image Pre-processing: We standardized the brightness, contrast, and orientation.
  2. Damage Annotation: Our experts outlined damaged areas for precise identification.
  3. Damage Classification: Each damage was tagged, whether a dent, scratch, or shattered glass.
  4. Severity Rating: We rated the severity on a predefined scale.
  5. Validation: We employed both automated tools and manual peer reviews for accuracy.

Annotation Metrics

  • Total Damage Annotations: 700,000
  • Damage Classification Tags: 700,000
  • Severity Ratings: 350,000
Damaged Car Image Dataset
Damaged Car Image Dataset
Damaged Car Image Dataset
Damaged Car Image Dataset

Quality Assurance

Stages

Automated Damage Detection Verification: Used for initial consistency checks.
Peer Review: Annotations were double-checked for accuracy.
Inter-annotator Agreement: Regular re-annotation for consistency among annotators.

QA Metrics

  • Annotations Verified: 175,000
  • Annotations Peer Reviewed: 105,000
  • Inconsistencies Identified and Rectified: 10,500

Conclusion

Damaged Car Image Dataset marks a significant stride in the automotive insurance and repair sectors. By providing a rich, contextually diverse view of car damages, we empower AI models for more precise assessments, streamlining insurance claims and repair processes.

quality dataset

Quality Data Creation

Guaranteed TAT‚Äč

Guaranteed TAT

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

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

HIPAA Compliance‚Äč

HIPAA Compliance

GDPR Compliance‚Äč

GDPR Compliance

Compliance and Security‚Äč

Compliance and Security

Let's Discuss your Data collection Requirement With Us

To get a detailed estimation of requirements please reach us.

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