def test_export_model_overwrite(file_stimuli, tmpdir):
model1 = pysaliency.GaussianSaliencyMapModel(width=0.1)
model2 = pysaliency.GaussianSaliencyMapModel(width=0.8)
filename = str(tmpdir.join('model.hdf5'))
partial_stimuli = pysaliency.FileStimuli(
filenames=file_stimuli.filenames[:5])
export_model_to_hdf5(model1, partial_stimuli, filename)
export_model_to_hdf5(model2, file_stimuli, filename)
model3 = pysaliency.HDF5SaliencyMapModel(file_stimuli, filename)
for s in file_stimuli:
np.testing.assert_allclose(model2.saliency_map(s),
model3.saliency_map(s))
def probabilistic_model(saliency_model):
blurred_model = pysaliency.BluringSaliencyMapModel(saliency_model,
kernel_size=5.0)
centerbias_model = pysaliency.saliency_map_models.LambdaSaliencyMapModel(
[pysaliency.GaussianSaliencyMapModel(width=0.5)],
fn=lambda smaps: 1.0 * smaps[0],
)
model_with_centerbias = blurred_model * centerbias_model
probabilistic_model = SaliencyMapNormalizingModel(model_with_centerbias)
return probabilistic_model
def saliency_model():
return pysaliency.GaussianSaliencyMapModel(center_x=0.15,
center_y=0.85,
width=0.2)