USE CASE
Parking Spaces Image Annotation
A dataset of parking lot photos for classifying available and occupied parking spaces
Computer Vision
Ability to recognize and analyze images and video
Object Detection
Determining the position of an object with Bounding Box annotation
Classification
Ability to assess and separate objects based on predetermined features
Transportation
Using machine learning in the automotive industry
3 500
photos
4 weeks
project duration
Our Partners
CASE DESCRIPTION
Collection of parking lot photos through parsing and crowdsourcing
Detection of parking spaces using Bounding Box in CVAT. Classification of parking spaces as available, occupied, and partially occupied
APPLICATION AREAS OF THE DATASET
Parking Analytics:
Classification for analyzing the geographical distribution of available parking spaces and making decisions about parking construction and planning
Traffic Management:
Computer vision and classification to determine the degree of parking space occupancy in different areas, optimizing vehicle movement, and reducing road congestion
Development of Autonomous Vehicles:
Computer vision for training autonomous vehicles to recognize and classify parking spaces
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Why
Training Data
- Quality Assurance:
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Enhanced Data Accuracy
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Consistency in Labels
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Reliable Ground Truth
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Mitigation of Annotation Biases
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Cost and Time Efficiency
- Data Security and Confidentiality:
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GDPR Compliance
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Non-disclosure agreement
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Data Encryption
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Multiple data storage options
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Access Controls and Authentication
- Expert Team:
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6 years in industry
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35 top project managers
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40+ languages
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100+ countries
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250k+ assessors
- Flexible and Scalable Solutions:
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24/7 availability of customer service
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100% post payment
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$550 minimum check
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Variable Workload
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Customized Solutions
Team leads project
Anton Tseluiko
Operations manager
Arthur Kazukevich
Python-developer
Daria Yurkevich
Quality Control Manager