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Commit d320fbc6 authored by Manuel Günther's avatar Manuel Günther
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Allowing feature extraction and projection to fail, when --allow-missing-files is enabled

parent f71b04c5
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......@@ -128,6 +128,15 @@ def project(algorithm, extractor, groups = None, indices = None, allow_missing_f
feature = extractor.read_feature(feature_file)
# project feature
projected = algorithm.project(feature)
if projected is None:
if allow_missing_files:
logger.debug("... Projection for extracted file %s failed; skipping", feature_file)
continue
else:
logger.error("Projection of file '%s' was not successful", feature_file)
continue
# write it
algorithm.write_feature(projected, projected_file)
......@@ -265,6 +274,15 @@ def enroll(algorithm, extractor, compute_zt_norm, indices = None, groups = ['dev
enroll_features = [reader.read_feature(enroll_file) for enroll_file in enroll_files]
model = algorithm.enroll(enroll_features)
if model is None:
if allow_missing_files:
logger.debug("... Enrollment for model %s failed; skipping", model_id)
continue
else:
logger.error("Enrollemnt of model '%s' was not successful", model_id)
continue
# save the model
algorithm.write_model(model, model_file)
......@@ -303,6 +321,15 @@ def enroll(algorithm, extractor, compute_zt_norm, indices = None, groups = ['dev
t_enroll_features = [reader.read_feature(t_enroll_file) for t_enroll_file in t_enroll_files]
t_model = algorithm.enroll(t_enroll_features)
if t_model is None:
if allow_missing_files:
logger.debug("... Enrollment for T-model %s failed; skipping", t_model_id)
continue
else:
logger.error("Enrollemnt of T-model '%s' was not successful", t_model_id)
continue
# save model
algorithm.write_model(t_model, t_model_file)
else:
......
......@@ -117,6 +117,15 @@ def extract(extractor, preprocessor, groups=None, indices = None, allow_missing_
data = preprocessor.read_data(data_file)
# extract feature
feature = extractor(data)
if feature is None:
if allow_missing_files:
logger.debug("... Feature extraction for data file %s failed; skipping", data_file)
continue
else:
logger.error("Feature extraction of file '%s' was not successful", data_file)
continue
# write feature
extractor.write_feature(feature, feature_file)
else:
......
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