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Face Masks Detection Dataset

Selfie of people wearing medical masks in 4 variants. The dataset is suitable for re-identification tasks and video analysis and video systems
Computer Vision Ability to recognize and analyze images and video
Classification Ability to assess and separate objects based on predetermined features
Re-identification Recognition of the same object in different observations.
Machine Learning Enables computer systems to automatically learn from data and make predictions
300 988
images
75 247
unique faces
730
GB data

CASE DESCRIPTION

Dataset of photographs of people wearing medical masks

Each set includes: 4 types of selfies of the same persom: no mask, mask on the chin, mask covering only the mouth, mask fully on

APPLICATION AREAS OF THE DATASET

Monitoring Mask Compliance in the Fight Against the Pandemic

Recognition of Correctly Worn Medical Masks to Ensure Safety Measures in Public Places

Face Identification with a Mask On

Recognition and identification of a person wearing a medical mask for biometric authentication systems

AR Filters in Medical Masks

Segmentation of faces in various variations of medical masks to enhance the accuracy of augmented reality in filters and advertising

FACTORS AFFECTING THE FINAL PROJECT COST INCLUDE

Our data quality guarantee is 95%. For annotation orders requiring quality above 95%, we offer enterprise solutions
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Why
Training Data

  • Quality Assurance:
  • Enhanced Data Accuracy
  • Consistency in Labels
  • Reliable Ground Truth
  • Mitigation of Annotation Biases
  • Cost and Time Efficiency
  • Data Security and Confidentiality:
  • GDPR Compliance
  • Non-disclosure agreement
  • Data Encryption
  • Multiple data storage options
  • Access Controls and Authentication
  • Expert Team:
  • 6 years in industry
  • 35 top project managers
  • 40+ languages
  • 100+ countries
  • 250k+ assessors
  • Flexible and Scalable Solutions:
  • 24/7 availability of customer service
  • 100% post payment
  • $550 minimum check
  • Variable Workload
  • Customized Solutions

Team leads project

Anton Tseluyko
Operations manager
Arthur Kazukevich
Python-developer
Daria Yurkevich
Quality Control Manager
woman

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