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To run the evaluation,

  • download the dataset:
    $ git submodule update --init
  • set up a Python 3 virtual environment and install the required packages:
    $ mkvirtualenv -p $(which python3) system
    (system) $ pip install -U pip
    (system) $ pip install -r requirements.txt
    (system) $ pip install -r dataset/requirements.txt
  • remove the log file with results:
    (system) $ rm __main__.log
  • run the main shell script:
    (system) $ ./__main.sh

Evaluation results will be printed to the standard output and stored inside the __main__.log log file. The dataset takes up about 579M of disk space. The evaluation requires about 70G of memory and a month of wall clock time with 32 Intel Xeon E5-2650 v2 (2.60 GHz) CPU cores; you can reduce the memory requirements by turning the individual preprocessing.images.CACHES and preprocessing.features.CACHES dictionaries into LRU caches with fixed size.