Parking Spaces Detection
A dataset of parking lot photos for classifying available and occupied parking spaces
Dataset
Computer Vision
Ability to recognize and analyze images and video
Classification
Ability to assess and separate objects based on predetermined features
Object Detection
Determining the position of an object with Bounding Box annotation
Transportation
Using machine learning in the automotive industry
3 500
photos
4 weeks
project duration
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
The dataset consists of two folders:
APPLICATION AREAS OF THE DATASET
Classification for analyzing the geographical distribution of available parking spaces and making decisions about parking construction and planning
Parking Analytics:
Computer vision for training autonomous vehicles to recognize and classify parking spaces
Development of Autonomous Vehicles:
Computer vision and classification to determine the degree of parking space occupancy in different areas, optimizing vehicle movement, and reducing road congestion
Traffic Management:

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LLM Teamleads
Team
Arthur Kazukevich
Python-developer
Daria Yurkevich
Anton Tseluyko
Quality Control Manager
Operations manager
Why
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Data Security and Confidentiality:
Enhanced Data Accuracy
Consistency in Labels
Reliable Ground Truth
Mitigation of Annotation Biases
Cost and Time Efficiency
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Non-disclosure agreement
Data Encryption
Multiple data storage options
Access Controls and Authentication
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