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AVM Panoramic Parking Space Annotation Dataset
Synthetic Images & Vision Datasets
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£8,000
About
Description：
This dataset consists of high-resolution synthetic top-down parking space images generated from an Around View Monitoring (AVM) system. It covers multiple parking lot environments, including city streets, industrial parks, and underground parking structures, with a variety of parking space types such as standard spaces, irregularly shaped spaces, and disabled parking spots. Each image is at a resolution of 1000×1000 pixels, providing detailed visual input for precise parking space analysis.
The dataset is designed for parking assistance systems, parking space status recognition, and automated parking path planning. It supports perception models that need to identify the location, shape, type, and occupancy status of parking spaces under varied real-world conditions, improving the accuracy of autonomous or assisted parking solutions.
All samples are annotated in JSON format with multiple attributes, including parking space key points, polygonal or linear contours, parking space type classification, and occupancy status (occupied or vacant). The annotation process ensures precise geometric representation, enabling both detection and spatial layout mapping in AVM-based systems.
Data was generated to reflect different lighting and operational conditions, including daytime and nighttime scenarios. Parking layouts vary from open-surface lots to structured multi-level facilities, ensuring the dataset’s applicability across diverse deployment environments. Balanced representation across parking space types and occupancy statuses supports robust model generalization and reduces bias toward specific configurations.
By combining photorealistic AVM-rendered imagery, detailed geometric and categorical annotations, and diverse parking scene coverage, this dataset provides a critical resource for developing advanced parking assistance algorithms, occupancy detection modules, and automated parking planning systems.
Keywords: parking space detection AVM perception occupancy recognition polygon annotation automated parking
Sector: Intelligent Transportation / Autonomous Driving / Parking Assistance Systems / Computer Vision
Metrics: Parking space detection accuracy, occupancy classification precision, contour segmentation IoU
Entities: Standard parking spaces, irregular parking spaces, disabled parking spaces
Geographies: China (urban, industrial, and underground parking environments)
Price Range (USD): 4000–20000
Source type: Synthetic data generation from simulation environment, human annotation
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Usage Notes & Services
©️ Copyright & Licensing
- All rights, title, and copyright for this dataset are the exclusive property of Join Intelligence (JoinAI).
- This dataset is provided under a proprietary license. Without our express written permission, any form of redistribution, modification, public display, or commercial resale is strictly prohibited. 📜 Ethics & Compliance
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- The use of this dataset for any illegal purpose is strictly prohibited. Users are solely responsible for any and all legal consequences resulting from its misuse. 🚀 Our Service Advantages
- Actively Maintained: The dataset is still expanding and being updated regularly. For the most up-to-date version, please contact us directly.
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