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A simple database for image classification using images from a robot car

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Self-Driving Data

A simple database for image classification using images from a robot car.

Documentation

This repository was created by Paula Moraes and Felipe Salvatore. You can find here a very simple computer vision dataset for classification. It consists of images like

examples of: right, left, up and up images.

Usage

To download the data set just run

$ bash download.sh

Data Details

The data is split into three parts: 56,172 data points of training data (train_data.npy, train_labels.npy), 7,022 points of test data (test_data.npy, test_labels.npy), and 7,022 points of validation data (valid_data.npy, valid_labels.npy). Each data point is a flattened 45x80x3 image (a 10800-dimensional vector). Each image has a corresponding label ('0', '1' and '2') representing a command for the robot car ('0' = up, '1' = left, '2' = right).

Citation

  @misc{self_driving_data2018,
    author = {Paula Moraes and Felipe Salvatore},
    title = {Self Driving Data},
    year = {2018},
    howpublished = {\url{https://github.com/felipessalvatore/self_driving_data/}},
    note = {commit xxxxxxx}
  }

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