def test_load_and_featurize_single_column(model, size, array_path):
"""Test that all of the featurizations and attributes for each model are correct"""
feat = ImageFeaturizer(model=model)
feat.load_and_featurize_data(save_features=True,
omit_time=True,
omit_model=True,
omit_depth=True,
omit_output=True,
**LOAD_DATA_ARGS)
check_array = np.load(array_path)
try:
compare_featurizer_class(feat, size, check_array, **COMPARE_ARGS)
finally:
# Remove path to the generated csv at the end of the test
if os.path.isdir('tests/ImageFeaturizer_testing/csv_tests'):
shutil.rmtree('tests/ImageFeaturizer_testing/csv_tests')
del feat
def test_writing_features_to_csv_with_robust_naming():
"""Make sure the featurizer writes the name correctly to csv with robust naming config"""
f = ImageFeaturizer()
f.load_and_featurize_data(save_features=True,
omit_time=True,
**LOAD_DATA_ARGS_MULT)
check_array_path = '{}_squeezenet_depth-1_output-512'.format(CSV_NAME_MULT)
full_check = '{}_full'.format(check_array_path)
feature_check = '{}_features_only'.format(check_array_path)
try:
assert os.path.isfile(full_check)
assert os.path.isfile(feature_check)
finally:
if os.path.isdir('tests/ImageFeaturizer_testing/csv_tests'):
shutil.rmtree('tests/ImageFeaturizer_testing/csv_tests')
if os.path.isfile('{}_full'.format(check_array_path)):
os.remove('{}_full'.format(check_array_path))
pass
if os.path.isfile('{}_features_only'.format(check_array_path)):
os.remove('{}_features_only'.format(check_array_path))
def test_load_and_featurize_data_multiple_columns(model, size, array_path):
"""Test featurizations and attributes for each model are correct with multiple image columns"""
feat = ImageFeaturizer(model=model, auto_sample=True)
feat.load_and_featurize_data(save_features=True,
omit_time=True,
omit_model=True,
omit_depth=True,
omit_output=True,
**LOAD_DATA_ARGS_MULT)
check_array = np.load(array_path)
try:
compare_featurizer_class(feat, size, check_array, **COMPARE_ARGS_MULT)
finally:
# Remove path to the generated csv at the end of the test
if os.path.isdir('tests/ImageFeaturizer_testing/csv_tests'):
shutil.rmtree('tests/ImageFeaturizer_testing/csv_tests')
if os.path.isfile('{}_full'.format(CSV_NAME_MULT)):
os.remove('{}_full'.format(CSV_NAME_MULT))
pass
if os.path.isfile('{}_features_only'.format(CSV_NAME_MULT)):
os.remove('{}_features_only'.format(CSV_NAME_MULT))
del feat
def create_numpy_arrays(model):
"""Create the prediction arrays"""
f = ImageFeaturizer(model=model, auto_sample=True)
f.load_and_featurize_data(**LOAD_DATA_ARGS_MULT)
np.save(CHECK_ARRAY_MULT.format(model), f.featurized_data)
return f