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Transportation

In order to catalog and inspect important transportation infrastructure from the sky, curated datasets of airports, highways, ports, freight yards, and railways need to be collected and labeled. Below are some shared from the Roboflow community to train custom computer vision models for automated detection.

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.

Minor Damage

  • Dan
  • Minor-Damage-Car Dataset
  • 376 images

Major Damage

  • Dan
  • Major-Damage-Car Dataset
  • 547 images

Object Detection

This is an object detection dataset that me and my teamates have created. We picked these images from Google Earth. These images are aerial images in which we will be detetcting objects according to cateogary. The images consists of different cateogaries such as Airplane, Bridges, Playground, Water-Bodies and Vehicles. The Dataset consists of total 700 images out of which 490 are used for training ,140 for validation and remaining 70 for testing. We have first uploaded these images and then annoteted them on roboflow itself. The version used for this project is Earth Vision small scale dataset version4.