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TRODO: A public vehicle odometers dataset for computer vision
TRODO: مجموعه داده کیلومتر شمار خودروهای عمومی برای بینایی ماشین-2021
In the field of transportation and logistics, smart vision systems have been employed successfully to automate various
tasks such as number-plate recognition and vehicle identity
recognition. The development of such automated systems is
possible with the availability of large image datasets having
proper annotations. The TRODO dataset is a rich-annotated
collection of odometer displays that can enable automatic
mileage reading from raw images. Initially, the dataset consisted of 2613 frames captured in different conditions in
terms of resolution, quality, illumination and vehicle type. After data pre-processing and cleaning, the number of images
was reduced to 2389. The images were annotated using the
CVAT image annotation tool. The dataset provides the following information for each frame: the type of odometer (analog or digital), the mileage value displayed on the odometer, the bounding boxes of the odometer, and the digits and
characters displayed on the screen. Combined with machine
learning and artificial intelligence, the TRODO dataset can be
used to train odometer classifiers, digit recognition and number reading models from odometers and similar types of displays.
Keywords: Computer vision | Image processing | Digit recognition | Odometer | Mileage reading |
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