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Commit 56bc342f authored by Amir MOHAMMADI's avatar Amir MOHAMMADI
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Merge branch 'fix-hdf5' into 'master'

Fix: hdf5 v3 not supported

Closes #28

See merge request !27
parents 79c69bb4 cce8ebd4
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1 merge request!27Fix: hdf5 v3 not supported
Pipeline #58567 passed
......@@ -305,6 +305,7 @@ class GMM(BioAlgorithm, BaseEstimator):
max_iter=self.kmeans_training_iterations,
init_method="k-means||",
init_max_iter=5,
random_state=self.init_seed,
),
)
......
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......@@ -28,8 +28,8 @@ import bob.bio.gmm
from bob.bio.base.test import utils
from bob.bio.gmm.algorithm import GMM
from bob.learn.em.mixture import GMMMachine
from bob.learn.em.mixture import GMMStats
from bob.learn.em.mixture.gmm import GMMMachine
from bob.learn.em.mixture.gmm import GMMStats
logger = logging.getLogger(__name__)
......@@ -57,8 +57,8 @@ def test_training():
# Set a small training iteration count
gmm1 = GMM(
number_of_gaussians=2,
kmeans_training_iterations=1,
ubm_training_iterations=1,
kmeans_training_iterations=5,
ubm_training_iterations=5,
init_seed=seed_value,
)
train_data = utils.random_training_set(
......@@ -95,7 +95,7 @@ def test_projector():
)
# Generate and project random feature
feature = utils.random_array((20, 45), -5.0, 5.0, seed=84)
feature = utils.random_array((20, 45), -5.0, 5.0, seed=seed_value)
projected = gmm1.project(feature)
assert isinstance(projected, bob.learn.em.mixture.GMMStats)
......@@ -120,7 +120,7 @@ def test_enroll():
)
gmm1.ubm = ubm
# Enroll the biometric reference from random features
enroll = utils.random_training_set((20, 45), 5, -5.0, 5.0, seed=21)
enroll = utils.random_training_set((20, 45), 5, -5.0, 5.0, seed=seed_value)
biometric_reference = gmm1.enroll(enroll)
assert not biometric_reference.is_similar_to(biometric_reference.ubm)
assert isinstance(biometric_reference, GMMMachine)
......@@ -153,9 +153,9 @@ def test_score():
probe = GMMStats.from_hdf5(
pkg_resources.resource_filename("bob.bio.gmm.test", "data/gmm_projected.hdf5")
)
probe_data = utils.random_array((20, 45), -5.0, 5.0, seed=84)
probe_data = utils.random_array((20, 45), -5.0, 5.0, seed=seed_value)
reference_score = -0.098980
reference_score = 0.601025
numpy.testing.assert_almost_equal(
gmm1.score(biometric_reference, probe), reference_score, decimal=5
......
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