The Trucks dataset offers a comprehensive collection of images featuring various trucks and heavy vehicles. Curated meticulously from diverse sources including the internet, Roboflow, and the streets of Cotonou, Akpakpa in Benin, it provides a diverse representation of truck types and environments. The dataset consists of 746 annotated images, each formatted in YOLOv8 for precise object detection and localization.
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Key Features:
Data Sources: Images sourced from internet repositories, roboflow, and real-world locations in Cotonou, Akpakpa.
Annotation Format: Annotated using YOLOv8 format, ensuring compatibility with popular deep learning frameworks.
Pre-Processing: Each image underwent meticulous pre-processing steps, including automatic orientation adjustment to strip EXIF metadata, resizing to a standardized 640×640 resolution for consistency, and conversion to grayscale for specialized applications like CRT phosphor simulation.
Applications: This dataset is perfect for training and validating machine learning models designed to detect trucks and heavy vehicles in different environments. Applications include but are not limited to:
Autonomous vehicle navigation systems.
Traffic monitoring and management solutions.
Urban planning and infrastructure development.
Environmental impact assessments involving heavy vehicle emissions.
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