UQTR Dataset - Snowy and non-snowy road images
- Citation Author(s):
-
Tatiana Ortegon-Sarmiento
(Université du Québec à Trois-Rivières, Universidad de Granada)
Sousso Kelouwani
(Université du Québec à Trois-Rivières)
Ali Amamou
(Université du Québec à Trois-Rivières)
Jonathan Boisclair
(Université du Québec à Trois-Rivières)
Alvaro Uribe-Quevedo
(Ontario Tech University)
Muhammad Zeshan Alam
(Brandon University)
Patricia Paderewski-Rodriguez
(Universidad de Granada)
Francisco Gutierrez-Vela
(Universidad de Granada)
- Submitted by:
- Tatiana Ortegon Sarmiento
- Last updated:
- DOI:
- 10.21227/q4af-r432
- Data Format:
- Links:
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Abstract
The UQTR dataset consists of 7838 real and synthetic images of the Université du Québec à Trois-Rivières (UQTR) campus road under normal and snow conditions. The image resolution is 1280×720. It includes lane labels in .txt files, where each row stores the set of points of a lane. The points are stored as x1 y1 x2 y2, as in the tutorial by Ruijin Liu, Zejian Yuan, Tie Liu, Zhiliang Xiong: Train and Test Your Custom Data.
Synthetic data were generated using different image synthesis techniques from real road data to improve lane detection in snowy winter conditions. Simulation data, corresponding to a virtual environment of the UQTR campus, are also included.
The dataset includes:
- 967 real road images
- 6655 images with synthetic snow
- 216 images of the virtual environment
References to 3D models of the virtual environment:
- Feel funny, “Shelter a00,” 2010, accessed July 2023. [Online]. Available: https://www.turbosquid.com/3d-models/free-max-model-bus-shelter/520824
- NinjRosa, "Stop," 2022, accessed July 2023. [Online]. Available: https://www.turbosquid.com/3d-models/stop-1958611
- Adobe Systems Incorporated, "Mixamo Bryce character," 2015, accessed July 2023. [Online]. Available: https://www.mixamo.com/#/?page=2&type=Character
Instructions:
This dataset can be used for training and testing deep learning models of lane detection. It consists of images, in .jpg format, and lane labels, in .txt files, and is divided into two datasets, a training dataset, with 6271 images, and a test dataset, with 1567 images. The images and their respective labels, whose names are the same but with different formats, are distributed in separate folders for ease of use.
To use this datset:
- Download the dataset.
- Load images from train_images and test_images folders.
- Load labels from train_labels and test_labels folders.
- Model training
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