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Face Detection Data Set and Benchmark (FDDB) in Darknet

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FDDB

This repository contains scripts automating conversion of the FDDB dataset to a format required by the Darknet framework.

Usage

  1. Clone and navigate to the repository

  2. Use the following links in order to download a complete FDDB dataset.

     wget http://vis-www.cs.umass.edu/fddb/FDDB-folds.tgz
     wget http://vis-www.cs.umass.edu/fddb/README.txt
     wget http://tamaraberg.com/faceDataset/originalPics.tar.gz
    
  3. Create a new folder and call it images. Unpack the supplied images inside of it.

     tar -xzvf FDDB-folds.tgz
     mdkir images && tar -xzvf originalPics.tar.gz -C images
    
  4. Prepare data.

     find FDDB-folds -type f -regex ".*[0-9]-.*txt" -exec cat {} >> FDDB-folds/FDDB-annotations.txt \;
     find FDDB-folds -type f -regex ".*[0-9]+.txt" -exec cat {} >> FDDB-folds/FDDB-paths.txt \;
    
  5. Install the required Python libraries.

     pip install Pillow
    
  6. Generate all the files required by the Darknet.

     python ./scripts/cs_fddb_convert_to_darknet.py
    

License

This is free and unencumbered software released into the public domain. For more information, please refer to the LICENSE file.

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