traffic Computer Vision Project
Traffic2
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* 50% probability of horizontal flip
* 50% probability of vertical flip
* Random Gaussian blur of between 0 and 3.25 pixels
* Randomly crop between 0 and 33 percent of the image
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==============================
Barrier-Ahead
Cattle Caution
Cycle-Crossing
Dangerous-Dip
Eating-Place
Falling-Rocks
Ferry First-Aid-Post
For state of the art Computer Vision training notebooks you can use with this dataset,
Give-Way
Horn-Prohibited
Hospital
Hump
Left-Hair-Pin-Bend
Left-Reverse-Bend
Left-hand-curve
Light-Refreshment
Men-at-Work
Narrow-Bridge
Narrow-road-ahead
No-Parking No-Stopping
No-Thorough-Road
No-Thorough-SideRoad
Parking-Lot-Cars
Parking-Lot-Cycle
Parking-Lot-Scooter-and-MotorCycle
Parking-This-side
Pedestrian-Crossing Pedestrian-Prohibited
Petrol-Pump--Gas-Station
Public-Telephone
Resting-Place
Right-Hair-Pin-Bend
Right-Hand-Curve
Right-Reverse-Bend
Road-Wideness-Ahead
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Round-About School-Ahead
Slippery-Road Speed-Limit--10-
Speed-Limit--100-
Speed-Limit--110-
Speed-Limit--120-
Speed-Limit--130-
Speed-Limit--140-
Speed-Limit--150-
Speed-Limit--160-
Speed-Limit--20-
Speed-Limit--25-
Speed-Limit--35-
Speed-Limit--45-
Speed-Limit--48-
Speed-Limit--5-
Speed-Limit--50-
Speed-Limit--55-
Speed-Limit--60-
Speed-Limit--65-
Speed-Limit--70-
Speed-Limit--75-
Speed-Limit--8-
Speed-Limit--80-
Speed-Limit--90-
Speed-Limit-3
Speed-Limit-30
Speed-limit--15-
Speed-limit--40-
Steep-Ascent
Steep-Desecnt
Stop Straight-Prohibitor-No-Entry
The dataset includes 9199 images.
The following augmentation was applied to create 3 versions of each source image:
The following pre-processing was applied to each image:
This dataset was exported via roboflow.com on March 5, 2024 at 6:35 AM GMT
To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
Traffic-sign are annotated in YOLOv9 format.
traffic sign - v1 2023-12-23 2:51pm
visit https://github.com/roboflow/notebooks
walking
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Cite This Project
LICENSE
CC BY 4.0 If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
traffic-vzwaq_dataset,
title = { traffic Dataset },
type = { Open Source Dataset },
author = { Traffic2 },
howpublished = { \url{ https://universe.roboflow.com/traffic2-x6dux/traffic-vzwaq } },
url = { https://universe.roboflow.com/traffic2-x6dux/traffic-vzwaq },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { sep },
note = { visited on 2024-09-22 },
}