# Declare some parameters
batch_size = 32
# Define some model-specific parameters
elg_first_layer_stride = 1
elg_num_modules = 3
elg_num_feature_maps = 32
# Define training data source
from datasources import UnityEyes
unityeyes = UnityEyes(
session,
batch_size=batch_size,
data_format='NCHW',
unityeyes_path='/home/xiehuan/datasets/UnityEyes_Windows/imgs',
min_after_dequeue=1000,
generate_heatmaps=True,
shuffle=True,
staging=True,
eye_image_shape=(36, 60),
heatmaps_scale=1.0 / elg_first_layer_stride,
)
unityeyes.set_augmentation_range('translation', 2.0, 10.0)
unityeyes.set_augmentation_range('rotation', 1.0, 10.0)
unityeyes.set_augmentation_range('intensity', 0.5, 20.0)
unityeyes.set_augmentation_range('blur', 0.1, 1.0)
unityeyes.set_augmentation_range('scale', 0.01, 0.1)
unityeyes.set_augmentation_range('rescale', 1.0, 0.5)
unityeyes.set_augmentation_range('num_line', 0.0, 2.0)
unityeyes.set_augmentation_range('heatmap_sigma', 7.5, 2.5)
from datasources import HDF5Source
test_losses_or_metrics=['gaze_mse', 'gaze_angular'],
# Data sources for training and testing.
train_data={
'real':
HDF5Source(
session,
batch_size,
hdf_path='../datasets/MPIIGaze_kaggle_students.h5',
keys_to_use=['train'],
min_after_dequeue=100,
),
'unity':
UnityEyes(
session,
batch_size,
unityeyes_path='../datasets/UnityEyes/',
)
},
test_data={
'real':
HDF5Source(
session,
batch_size,
hdf_path='../datasets/MPIIGaze_kaggle_students.h5',
keys_to_use=['validation'],
testing=True,
),
},
beta1=BETA1,
beta2=BETA2)