DINO&GTSDBv1 Computer Vision Project

nam nguyen

Updated 2 months ago

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Classes (50)
Ahead_only
Beware_of_ice_snow
Bicycles_crossing
Bumpy_road
Children_crossing
Dangerous_curve_to_the_left
Dangerous_curve_to_the_right
Double_curve
End_of_all_speed_and_passing_limits
End_of_no_passing
End_of_no_passing_by_vehicles_over_3_5_metric_tons
End_of_speed_limit_80_km_h
General_caution
Go_straight_or_left
Go_straight_or_right
Green_light_traffic_light
Keep_left
Keep_right
No_entry
No_passing
No_passing_for_vehicles_over_3_5_metric_tons
No_vehicles
Pedestrians
Priority_road
Red_light_traffic_light
Right_of_way_at_the_next_intersection
Road_narrows_on_the_right
Road_work
Roundabout_mandatory
Slippery_road
Speed_limit_100_km_h
Speed_limit_120_km_h
Speed_limit_20_km_h
Speed_limit_30_km_h
Speed_limit_50_km_h
Speed_limit_60_km_h
Speed_limit_70_km_h
Speed_limit_80_km_h
Stop
Traffic_signals
Turn_left_ahead
Turn_right_ahead
Vehicles_over_3_5_metric_tons_prohibited
Wild_animals_crossing
Yellow_light_traffic_light
Yield bus car person truck
Description

This project was created by downloading the GTSDB German Traffic Sign Detection Benchmark

dataset from Kaggle and importing the annotated training set files (images and annotation files)

to Roboflow.

https://www.kaggle.com/datasets/safabouguezzi/german-traffic-sign-detection-benchmark-gtsdb

The annotation files were adjusted to conform to the YOLO Keras TXT format prior to upload, as the original format did not include a label map file.

v1 contains the original imported images, without augmentations. This is the version to download and import to your own project if you'd like to add your own augmentations.

v2 contains an augmented version of the dataset, with annotations. This version of the project was trained with Roboflow's "FAST" model.

v3 contains an augmented version of the dataset, with annotations. This version of the project was trained with Roboflow's "ACCURATE" model.

Supervision

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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{
                            dino-gtsdbv1-ykj2f_dataset,
                            title = { DINO&GTSDBv1 Dataset },
                            type = { Open Source Dataset },
                            author = { nam nguyen },
                            howpublished = { \url{ https://universe.roboflow.com/nam-nguyen-mnkr2/dino-gtsdbv1-ykj2f } },
                            url = { https://universe.roboflow.com/nam-nguyen-mnkr2/dino-gtsdbv1-ykj2f },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { sep },
                            note = { visited on 2024-11-21 },
                            }