License Plate Detection and Recognition in Unconstrained Scenarios
Paper Information
Abstract
Links and BibTex
- Springer (NOT AVAILABLE YET)
- DOI: NOT AVAILABLE YET
- BibTex:
@INPROCEEDINGS{silva2018a,
author={S. M. Silva and C. R. Jung},
booktitle={2018 European Conference on Computer Vision (ECCV)},
title={License Plate Detection and Recognition in Unconstrained Scenarios},
year={2018},
pages={},
keywords={Automobiles;Cameras;Character recognition;Databases;Licenses;Training},
doi={},
month={Sep},}
Downloads
Training and evaluation datasets
The data available for download in this webpage consists only of annotations. The images where those annotations come from are part of freely available datasets not owned by us. So please refer to the following links for instructions on how to obtain each dataset.
Training annotations: download the zip file and take a look at the README.txt for more instructions about how the data is organized.
Test dataset (CD-HARD): CSV containg an image filename (1st column) and the license plates on it (2nd column and so on) for each row. The images used are solely from Cars dataset.
Implementation and Trained Networks
We created a GitHub repository containing the necessary code to reproduce our results. You can checkout, compile and test using the following commands:
git clone https://github.com/sergiomsilva/alpr-unconstrained
cd alpr-unconstrained/
cd darknet/ && make && cd ..
bash run.sh samples/ /tmp/output_dir /tmp/output_dir/results.csv
More details can be found in the project description.