config

# Configuration file for presetting options for different datasets

[example]
    data_dir = /path/to/data/dir                      # directory where data is located
    hider_weights = /path/to/hider/weights.h5         # path to a valid "hider" model weights file
    seeker_weights = /path/to/seeker/weights.h5       # path to a valid "seeker" model weights file
    image_size = 256                                  # desired image dimensions: images will be resized to (256, 256)
    channels = 3                                      # number of channels (3 for RGB, 1 for grayscale)
    train_images = 10000                              # number of images in the training set (optional but recommended)
    test_images = 5000                                # number of images in the test set (optional but recommended)
    num_classes = 13                                  # number of classes (optional but recommended)
    max_epochs = 13                                   # maximum number of epochs to train the model
    batch_size = 64                                   # what batch size to use
    gpu = 1                                           # which gpu to use to train the model (for multi-gpu environments)
    model = hns_large                                 # select size of model to use, 'small' and 'large' available

[animals]
    data_dir = /home/thanos/animals
    hider_weights = weights/animals/hider/final_weights.h5
    seeker_weights = weights/animals/seeker/manual_training/best_weights.h5
    image_size = 192
    channels = 3
    train_images = 396416
    test_images = 114114
    num_classes = 398
    max_epochs = 10
    batch_size = 64
    gpu = 0
    model = hns_resnet

[mnist]
    baseline = results/mnist/seeker/final/baseline.txt
    image_size = 28
    channels = 1
    train_images = 60000
    test_images = 10000
    num_classes = 10
    max_epochs = 10
    batch_size = 256
    gpu = 0
    model = hns_small
    memory = 1024

[fashion]
    baseline = results/fashion/seeker/default/baseline.txt
    image_size = 28
    channels = 1
    train_images = 60000
    test_images = 10000
    num_classes = 10
    max_epochs = 10
    batch_size = 256
    gpu = 0
    model = hns_small
    memory = 1024

[cifar10]
    baseline = results/cifar10/seeker/default/baseline.txt
    image_size = 32
    channels = 3
    train_images = 50000
    test_images = 10000
    num_classes = 10
    max_epochs = 100
    batch_size = 128
    gpu = 0
    model = hns_small
    memory = 4096

[cifar100]
    baseline = results/cifar100/seeker/default/baseline.txt
    image_size = 32
    channels = 3
    train_images = 50000
    test_images = 10000
    num_classes = 100
    max_epochs = 100
    batch_size = 128
    gpu = 0
    model = hns_small
    memory = 4096