From bf300ae9dc47918be4a30de90436fe7563fafb45 Mon Sep 17 00:00:00 2001 From: debarpanb Date: Wed, 12 Oct 2022 11:11:52 +0530 Subject: [PATCH] added technical validation --- .../annotations/LABELS/breathing-deep.csv | 0 .../annotations/LABELS/breathing-shallow.csv | 0 .../annotations/LABELS/cough-heavy.csv | 0 .../annotations/LABELS/cough-shallow.csv | 0 .../annotations/LABELS/counting-fast.csv | 0 .../annotations/LABELS/counting-normal.csv | 0 .../annotations/LABELS/vowel-a.csv | 0 .../annotations/LABELS/vowel-e.csv | 0 .../annotations/LABELS/vowel-o.csv | 0 .../conf/classification.conf | 0 .../conf/feature.conf | 0 .../conf/train_lr.conf | 0 .../conf/train_mlp.conf | 0 .../conf/train_rbfSVM.conf | 0 .../data/breathing-deep/all | 0 .../data/breathing-deep/all.scp | 0 .../data/breathing-deep/bad_ids.npy | Bin .../data/breathing-deep/feats.scp | 0 .../data/breathing-shallow/all | 0 .../data/breathing-shallow/all.scp | 0 .../data/breathing-shallow/bad_ids.npy | Bin .../data/breathing-shallow/feats.scp | 0 .../data/cough-heavy/all | 0 .../data/cough-heavy/all.scp | 0 .../data/cough-heavy/bad_ids.npy | Bin .../data/cough-heavy/feats.scp | 0 .../data/cough-shallow/all | 0 .../data/cough-shallow/all.scp | 0 .../data/cough-shallow/bad_ids.npy | Bin .../data/cough-shallow/feats.scp | 0 .../data/counting-fast/all | 0 .../data/counting-fast/all.scp | 0 .../data/counting-fast/bad_ids.npy | Bin .../data/counting-fast/feats.scp | 0 .../data/counting-normal/all | 0 .../data/counting-normal/all.scp | 0 .../data/counting-normal/bad_ids.npy | Bin .../data/counting-normal/feats.scp | 0 .../data/vowel-a/all | 0 .../data/vowel-a/all.scp | 0 .../data/vowel-a/bad_ids.npy | Bin .../data/vowel-a/feats.scp | 0 .../data/vowel-e/all | 0 .../data/vowel-e/all.scp | 0 .../data/vowel-e/bad_ids.npy | Bin .../data/vowel-e/feats.scp | 0 .../data/vowel-o/all | 0 .../data/vowel-o/all.scp | 0 .../data/vowel-o/bad_ids.npy | Bin .../data/vowel-o/feats.scp | 0 .../local/classification.py | 0 .../local/feature_extraction.py | 0 .../local/filter_list.py | 0 .../local/prepare_list.py | 0 .../parse_options.sh | 0 .../path_files/wav.scp | 0 .../plot_results.ipynb | 0 .../results/RandomForest/confusion_matrix.jpg | Bin .../results/RandomForest/y_pred.npy | Bin .../results/RandomForest/y_pred_proba.npy | Bin .../results/RandomForest/y_true.npy | Bin .../{ => 9_class_classification}/run.sh | 0 .../run_classification.sh | 0 .../run_feature_extraction.sh | 0 .../annotations/LABELS/breathing-deep.csv | 2747 ++ .../annotations/LABELS/breathing-shallow.csv | 2747 ++ .../annotations/LABELS/cough-heavy.csv | 2234 ++ .../annotations/LABELS/cough-shallow.csv | 2233 ++ .../annotations/LABELS/counting-fast.csv | 2234 ++ .../annotations/LABELS/counting-normal.csv | 2234 ++ .../annotations/LABELS/vowel-a.csv | 2234 ++ .../annotations/LABELS/vowel-e.csv | 2747 ++ .../annotations/LABELS/vowel-o.csv | 2233 ++ .../conf/classification.conf | 13 + .../gender_classification/conf/feature.conf | 29 + .../gender_classification/conf/train_lr.conf | 12 + .../gender_classification/conf/train_mlp.conf | 13 + .../conf/train_rbfSVM.conf | 11 + .../data/breathing-deep/all | 2283 ++ .../data/breathing-deep/all.scp | 2283 ++ .../data/breathing-deep/bad_ids.npy | Bin 0 -> 18160 bytes .../data/breathing-deep/feats.scp | 2585 ++ .../data/breathing-shallow/all | 2234 ++ .../data/breathing-shallow/all.scp | 2234 ++ .../data/breathing-shallow/bad_ids.npy | Bin 0 -> 22752 bytes .../data/breathing-shallow/feats.scp | 2544 ++ .../data/cough-heavy/all | 2087 ++ .../data/cough-heavy/all.scp | 2087 ++ .../data/cough-heavy/bad_ids.npy | Bin 0 -> 10096 bytes .../data/cough-heavy/feats.scp | 2144 ++ .../data/cough-shallow/all | 2085 ++ .../data/cough-shallow/all.scp | 2085 ++ .../data/cough-shallow/bad_ids.npy | Bin 0 -> 10768 bytes .../data/cough-shallow/feats.scp | 2137 ++ .../data/counting-fast/all | 2046 ++ .../data/counting-fast/all.scp | 2046 ++ 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.../local/filter_list.py | 31 + .../local/prepare_list.py | 43 + .../metadata_files/combined_data.csv | 2747 ++ .../gender_classification/parse_options.sh | 97 + .../gender_classification/path_files/wav.scp | 24712 ++++++++++++++++ .../run_classification.sh | 28 + .../run_feature_extraction.sh | 45 + 125 files changed, 108750 insertions(+) rename technical_validation/{ => 9_class_classification}/annotations/LABELS/breathing-deep.csv (100%) rename technical_validation/{ => 9_class_classification}/annotations/LABELS/breathing-shallow.csv (100%) rename technical_validation/{ => 9_class_classification}/annotations/LABELS/cough-heavy.csv (100%) rename technical_validation/{ => 9_class_classification}/annotations/LABELS/cough-shallow.csv (100%) rename technical_validation/{ => 9_class_classification}/annotations/LABELS/counting-fast.csv (100%) rename technical_validation/{ => 9_class_classification}/annotations/LABELS/counting-normal.csv (100%) rename technical_validation/{ => 9_class_classification}/annotations/LABELS/vowel-a.csv (100%) rename technical_validation/{ => 9_class_classification}/annotations/LABELS/vowel-e.csv (100%) rename technical_validation/{ => 9_class_classification}/annotations/LABELS/vowel-o.csv (100%) rename technical_validation/{ => 9_class_classification}/conf/classification.conf (100%) rename technical_validation/{ => 9_class_classification}/conf/feature.conf (100%) rename technical_validation/{ => 9_class_classification}/conf/train_lr.conf (100%) rename technical_validation/{ => 9_class_classification}/conf/train_mlp.conf (100%) rename technical_validation/{ => 9_class_classification}/conf/train_rbfSVM.conf (100%) rename technical_validation/{ => 9_class_classification}/data/breathing-deep/all (100%) rename technical_validation/{ => 9_class_classification}/data/breathing-deep/all.scp (100%) rename technical_validation/{ => 9_class_classification}/data/breathing-deep/bad_ids.npy (100%) rename technical_validation/{ => 9_class_classification}/data/breathing-deep/feats.scp (100%) rename technical_validation/{ => 9_class_classification}/data/breathing-shallow/all (100%) rename technical_validation/{ => 9_class_classification}/data/breathing-shallow/all.scp (100%) rename technical_validation/{ => 9_class_classification}/data/breathing-shallow/bad_ids.npy (100%) rename technical_validation/{ => 9_class_classification}/data/breathing-shallow/feats.scp (100%) rename technical_validation/{ => 9_class_classification}/data/cough-heavy/all (100%) rename technical_validation/{ => 9_class_classification}/data/cough-heavy/all.scp (100%) rename technical_validation/{ => 9_class_classification}/data/cough-heavy/bad_ids.npy (100%) rename technical_validation/{ => 9_class_classification}/data/cough-heavy/feats.scp (100%) rename technical_validation/{ => 9_class_classification}/data/cough-shallow/all (100%) rename technical_validation/{ => 9_class_classification}/data/cough-shallow/all.scp (100%) rename technical_validation/{ => 9_class_classification}/data/cough-shallow/bad_ids.npy (100%) rename technical_validation/{ => 9_class_classification}/data/cough-shallow/feats.scp (100%) rename technical_validation/{ => 9_class_classification}/data/counting-fast/all (100%) rename technical_validation/{ => 9_class_classification}/data/counting-fast/all.scp (100%) rename technical_validation/{ => 9_class_classification}/data/counting-fast/bad_ids.npy (100%) rename technical_validation/{ => 9_class_classification}/data/counting-fast/feats.scp (100%) rename technical_validation/{ => 9_class_classification}/data/counting-normal/all (100%) rename technical_validation/{ => 9_class_classification}/data/counting-normal/all.scp (100%) rename technical_validation/{ => 9_class_classification}/data/counting-normal/bad_ids.npy (100%) rename technical_validation/{ => 9_class_classification}/data/counting-normal/feats.scp (100%) rename technical_validation/{ => 9_class_classification}/data/vowel-a/all 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9_class_classification}/local/classification.py (100%) rename technical_validation/{ => 9_class_classification}/local/feature_extraction.py (100%) rename technical_validation/{ => 9_class_classification}/local/filter_list.py (100%) rename technical_validation/{ => 9_class_classification}/local/prepare_list.py (100%) rename technical_validation/{ => 9_class_classification}/parse_options.sh (100%) rename technical_validation/{ => 9_class_classification}/path_files/wav.scp (100%) rename technical_validation/{ => 9_class_classification}/plot_results.ipynb (100%) rename technical_validation/{ => 9_class_classification}/results/RandomForest/confusion_matrix.jpg (100%) rename technical_validation/{ => 9_class_classification}/results/RandomForest/y_pred.npy (100%) rename technical_validation/{ => 9_class_classification}/results/RandomForest/y_pred_proba.npy (100%) rename technical_validation/{ => 9_class_classification}/results/RandomForest/y_true.npy (100%) rename technical_validation/{ => 9_class_classification}/run.sh (100%) rename technical_validation/{ => 9_class_classification}/run_classification.sh (100%) rename technical_validation/{ => 9_class_classification}/run_feature_extraction.sh (100%) create mode 100755 technical_validation/gender_classification/annotations/LABELS/breathing-deep.csv create mode 100755 technical_validation/gender_classification/annotations/LABELS/breathing-shallow.csv create mode 100755 technical_validation/gender_classification/annotations/LABELS/cough-heavy.csv create mode 100755 technical_validation/gender_classification/annotations/LABELS/cough-shallow.csv create mode 100755 technical_validation/gender_classification/annotations/LABELS/counting-fast.csv create mode 100755 technical_validation/gender_classification/annotations/LABELS/counting-normal.csv create mode 100755 technical_validation/gender_classification/annotations/LABELS/vowel-a.csv create mode 100755 technical_validation/gender_classification/annotations/LABELS/vowel-e.csv create mode 100755 technical_validation/gender_classification/annotations/LABELS/vowel-o.csv create mode 100644 technical_validation/gender_classification/conf/classification.conf create mode 100644 technical_validation/gender_classification/conf/feature.conf create mode 100644 technical_validation/gender_classification/conf/train_lr.conf create mode 100644 technical_validation/gender_classification/conf/train_mlp.conf create mode 100644 technical_validation/gender_classification/conf/train_rbfSVM.conf create mode 100644 technical_validation/gender_classification/data/breathing-deep/all create mode 100644 technical_validation/gender_classification/data/breathing-deep/all.scp create mode 100644 technical_validation/gender_classification/data/breathing-deep/bad_ids.npy create mode 100644 technical_validation/gender_classification/data/breathing-deep/feats.scp create mode 100644 technical_validation/gender_classification/data/breathing-shallow/all create mode 100644 technical_validation/gender_classification/data/breathing-shallow/all.scp create mode 100644 technical_validation/gender_classification/data/breathing-shallow/bad_ids.npy create mode 100644 technical_validation/gender_classification/data/breathing-shallow/feats.scp create mode 100644 technical_validation/gender_classification/data/cough-heavy/all create mode 100644 technical_validation/gender_classification/data/cough-heavy/all.scp create mode 100644 technical_validation/gender_classification/data/cough-heavy/bad_ids.npy create mode 100644 technical_validation/gender_classification/data/cough-heavy/feats.scp create mode 100644 technical_validation/gender_classification/data/cough-shallow/all create mode 100644 technical_validation/gender_classification/data/cough-shallow/all.scp create mode 100644 technical_validation/gender_classification/data/cough-shallow/bad_ids.npy create mode 100644 technical_validation/gender_classification/data/cough-shallow/feats.scp create mode 100644 technical_validation/gender_classification/data/counting-fast/all create mode 100644 technical_validation/gender_classification/data/counting-fast/all.scp create mode 100644 technical_validation/gender_classification/data/counting-fast/bad_ids.npy create mode 100644 technical_validation/gender_classification/data/counting-fast/feats.scp create mode 100644 technical_validation/gender_classification/data/counting-normal/all create mode 100644 technical_validation/gender_classification/data/counting-normal/all.scp create mode 100644 technical_validation/gender_classification/data/counting-normal/bad_ids.npy create mode 100644 technical_validation/gender_classification/data/counting-normal/feats.scp create mode 100644 technical_validation/gender_classification/data/vowel-a/all create mode 100644 technical_validation/gender_classification/data/vowel-a/all.scp create mode 100644 technical_validation/gender_classification/data/vowel-a/bad_ids.npy create mode 100644 technical_validation/gender_classification/data/vowel-a/feats.scp create mode 100644 technical_validation/gender_classification/data/vowel-e/all create mode 100644 technical_validation/gender_classification/data/vowel-e/all.scp create mode 100644 technical_validation/gender_classification/data/vowel-e/bad_ids.npy create mode 100644 technical_validation/gender_classification/data/vowel-e/feats.scp create mode 100644 technical_validation/gender_classification/data/vowel-o/all create mode 100644 technical_validation/gender_classification/data/vowel-o/all.scp create mode 100644 technical_validation/gender_classification/data/vowel-o/bad_ids.npy create mode 100644 technical_validation/gender_classification/data/vowel-o/feats.scp create mode 120000 technical_validation/gender_classification/feats create mode 100644 technical_validation/gender_classification/local/__pycache__/scoring.cpython-38.pyc create mode 100644 technical_validation/gender_classification/local/classification.py create mode 100755 technical_validation/gender_classification/local/feature_extraction.py create mode 100644 technical_validation/gender_classification/local/filter_list.py create mode 100644 technical_validation/gender_classification/local/prepare_list.py create mode 100644 technical_validation/gender_classification/metadata_files/combined_data.csv create mode 100755 technical_validation/gender_classification/parse_options.sh create mode 100644 technical_validation/gender_classification/path_files/wav.scp create mode 100755 technical_validation/gender_classification/run_classification.sh create mode 100755 technical_validation/gender_classification/run_feature_extraction.sh diff --git a/technical_validation/annotations/LABELS/breathing-deep.csv b/technical_validation/9_class_classification/annotations/LABELS/breathing-deep.csv similarity index 100% rename from technical_validation/annotations/LABELS/breathing-deep.csv rename to technical_validation/9_class_classification/annotations/LABELS/breathing-deep.csv diff --git a/technical_validation/annotations/LABELS/breathing-shallow.csv b/technical_validation/9_class_classification/annotations/LABELS/breathing-shallow.csv similarity index 100% rename from technical_validation/annotations/LABELS/breathing-shallow.csv rename to technical_validation/9_class_classification/annotations/LABELS/breathing-shallow.csv diff --git a/technical_validation/annotations/LABELS/cough-heavy.csv b/technical_validation/9_class_classification/annotations/LABELS/cough-heavy.csv similarity index 100% rename from technical_validation/annotations/LABELS/cough-heavy.csv rename to technical_validation/9_class_classification/annotations/LABELS/cough-heavy.csv diff --git a/technical_validation/annotations/LABELS/cough-shallow.csv b/technical_validation/9_class_classification/annotations/LABELS/cough-shallow.csv similarity index 100% rename from technical_validation/annotations/LABELS/cough-shallow.csv rename to technical_validation/9_class_classification/annotations/LABELS/cough-shallow.csv diff --git a/technical_validation/annotations/LABELS/counting-fast.csv b/technical_validation/9_class_classification/annotations/LABELS/counting-fast.csv similarity index 100% rename from technical_validation/annotations/LABELS/counting-fast.csv rename to technical_validation/9_class_classification/annotations/LABELS/counting-fast.csv diff --git a/technical_validation/annotations/LABELS/counting-normal.csv b/technical_validation/9_class_classification/annotations/LABELS/counting-normal.csv similarity index 100% rename from technical_validation/annotations/LABELS/counting-normal.csv rename to technical_validation/9_class_classification/annotations/LABELS/counting-normal.csv diff --git a/technical_validation/annotations/LABELS/vowel-a.csv b/technical_validation/9_class_classification/annotations/LABELS/vowel-a.csv similarity index 100% rename from technical_validation/annotations/LABELS/vowel-a.csv rename to technical_validation/9_class_classification/annotations/LABELS/vowel-a.csv diff --git a/technical_validation/annotations/LABELS/vowel-e.csv b/technical_validation/9_class_classification/annotations/LABELS/vowel-e.csv similarity index 100% rename from technical_validation/annotations/LABELS/vowel-e.csv rename to technical_validation/9_class_classification/annotations/LABELS/vowel-e.csv diff --git a/technical_validation/annotations/LABELS/vowel-o.csv b/technical_validation/9_class_classification/annotations/LABELS/vowel-o.csv similarity index 100% rename from technical_validation/annotations/LABELS/vowel-o.csv rename to technical_validation/9_class_classification/annotations/LABELS/vowel-o.csv diff --git a/technical_validation/conf/classification.conf b/technical_validation/9_class_classification/conf/classification.conf similarity index 100% rename from technical_validation/conf/classification.conf rename to technical_validation/9_class_classification/conf/classification.conf diff --git a/technical_validation/conf/feature.conf b/technical_validation/9_class_classification/conf/feature.conf similarity index 100% rename from technical_validation/conf/feature.conf rename to technical_validation/9_class_classification/conf/feature.conf diff --git a/technical_validation/conf/train_lr.conf b/technical_validation/9_class_classification/conf/train_lr.conf similarity index 100% rename from technical_validation/conf/train_lr.conf rename to technical_validation/9_class_classification/conf/train_lr.conf diff --git a/technical_validation/conf/train_mlp.conf b/technical_validation/9_class_classification/conf/train_mlp.conf similarity index 100% rename from technical_validation/conf/train_mlp.conf rename to technical_validation/9_class_classification/conf/train_mlp.conf diff --git a/technical_validation/conf/train_rbfSVM.conf b/technical_validation/9_class_classification/conf/train_rbfSVM.conf similarity index 100% rename from technical_validation/conf/train_rbfSVM.conf rename to technical_validation/9_class_classification/conf/train_rbfSVM.conf diff --git a/technical_validation/data/breathing-deep/all b/technical_validation/9_class_classification/data/breathing-deep/all similarity index 100% rename from technical_validation/data/breathing-deep/all rename to technical_validation/9_class_classification/data/breathing-deep/all diff --git a/technical_validation/data/breathing-deep/all.scp b/technical_validation/9_class_classification/data/breathing-deep/all.scp similarity index 100% rename from technical_validation/data/breathing-deep/all.scp rename to technical_validation/9_class_classification/data/breathing-deep/all.scp diff --git a/technical_validation/data/breathing-deep/bad_ids.npy b/technical_validation/9_class_classification/data/breathing-deep/bad_ids.npy similarity index 100% rename from technical_validation/data/breathing-deep/bad_ids.npy rename to 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technical_validation/run_feature_extraction.sh rename to technical_validation/9_class_classification/run_feature_extraction.sh diff --git a/technical_validation/gender_classification/annotations/LABELS/breathing-deep.csv b/technical_validation/gender_classification/annotations/LABELS/breathing-deep.csv new file mode 100755 index 00000000..90226a16 --- /dev/null +++ b/technical_validation/gender_classification/annotations/LABELS/breathing-deep.csv @@ -0,0 +1,2747 @@ +FILENAME, QUALITY +vK2bLRNzllXNeyOMudnNSL5cfpG2_breathing-deep,2 +bjA2KpSxneNskrLBeqi4bqoTDQl2_breathing-deep,2 +htQzROl26OWQpIYFDzv11F79PLR2_breathing-deep,2 +pW9mCAeWYiMoM7wW7riLvNRbYDO2_breathing-deep,2 +L7S8iIPKgiO6QWLC3mGkROCMa0s1_breathing-deep,1 +eP8gEM0KcBU6S5JpMdycX74KP3p2_breathing-deep,2 +UiUUhL0PMjWVA6W2dKte1DCE6wG2_breathing-deep,0 +QQbzKidDxHQ0eZFEL4uG68s1lc02_breathing-deep,2 +cfZUmZvsecYVKw5eSi4qIhfJVpI3_breathing-deep,2 +tiKv850hJFTmpCAvfJOmOOqkeUs1_breathing-deep,0 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diff --git a/technical_validation/gender_classification/annotations/LABELS/cough-heavy.csv b/technical_validation/gender_classification/annotations/LABELS/cough-heavy.csv new file mode 100755 index 00000000..5cb44d73 --- /dev/null +++ b/technical_validation/gender_classification/annotations/LABELS/cough-heavy.csv @@ -0,0 +1,2234 @@ +FILENAME, QUALITY +vK2bLRNzllXNeyOMudnNSL5cfpG2_cough-heavy,2 +bjA2KpSxneNskrLBeqi4bqoTDQl2_cough-heavy,2 +htQzROl26OWQpIYFDzv11F79PLR2_cough-heavy,2 +pW9mCAeWYiMoM7wW7riLvNRbYDO2_cough-heavy,2 +L7S8iIPKgiO6QWLC3mGkROCMa0s1_cough-heavy,2 +eP8gEM0KcBU6S5JpMdycX74KP3p2_cough-heavy,2 +UiUUhL0PMjWVA6W2dKte1DCE6wG2_cough-heavy,0 +QQbzKidDxHQ0eZFEL4uG68s1lc02_cough-heavy,2 +cfZUmZvsecYVKw5eSi4qIhfJVpI3_cough-heavy,2 +tiKv850hJFTmpCAvfJOmOOqkeUs1_cough-heavy,0 +LqGeCxef4fN4IPanKEbWkO1fAwJ3_cough-heavy,2 +XUsJp0qysAPtu3vBI0UCiHRJhZ22_cough-heavy,2 +eZ9KEu3fmEgvxINqgcbkBXoEsv53_cough-heavy,2 +TRK6gUseEUS7dbF0soG80W1uLm53_cough-heavy,0 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mode 100644 index 00000000..204279a6 --- /dev/null +++ b/technical_validation/gender_classification/conf/classification.conf @@ -0,0 +1,13 @@ +[default] +#feature_type=mfcc +classifier = RandomForest +#can be LogisticRegression, RandomForest + +[RandomForest] +n_estimators=50 +criterion=gini + +[LogisticRegression] +C=1.0 +max_iter=100 +class_weight=balanced \ No newline at end of file diff --git a/technical_validation/gender_classification/conf/feature.conf b/technical_validation/gender_classification/conf/feature.conf new file mode 100644 index 00000000..cc347f06 --- /dev/null +++ b/technical_validation/gender_classification/conf/feature.conf @@ -0,0 +1,29 @@ +[default] +#feature_type=mfcc +feature_type=logMelSpec +sampling_rate = 44100 +# parameters below are in samples +window_size = 1024 +window_shift = 441 + +[sad] +threshold = 0.0001 +# parameters below are in milli-seconds +start_end_sil_length = 20 +silence_margin = 50 + +[mfcc] +n_mfcc = 39 +n_mels = 64 +fmax = 22050 +add_deltas = True +add_delta_deltas = True + +[logMelSpec] +n_mfcc = 40 +n_mels = 64 +f_max = 22050 +#window_size = 25 +#hop_length = 10 +compute_deltas = True +compute_delta_deltas = True \ No newline at end of file diff --git a/technical_validation/gender_classification/conf/train_lr.conf b/technical_validation/gender_classification/conf/train_lr.conf new file mode 100644 index 00000000..84f0731e --- /dev/null +++ b/technical_validation/gender_classification/conf/train_lr.conf @@ -0,0 +1,12 @@ +[default] +#model = linearSVM, LogisticRegression, rbfSVM +model = linearSVM +seed = 42 + +[LogisticRegression] +C = 0.01 +max_iter = 40 +solver = liblinear +penalty = l2 +class_weight = balanced +verbose = True \ No newline at end of file diff --git a/technical_validation/gender_classification/conf/train_mlp.conf b/technical_validation/gender_classification/conf/train_mlp.conf new file mode 100644 index 00000000..f18f6220 --- /dev/null +++ b/technical_validation/gender_classification/conf/train_mlp.conf @@ -0,0 +1,13 @@ +[default] +model = MLP +seed = 42 + +[MLP] +learning_rate_init = 0.001 +alpha = 0.001 +solver = adam +hidden_layer_sizes = 20 +max_iter = 500 +activation = tanh +verbose = True +class_weight = balanced diff --git a/technical_validation/gender_classification/conf/train_rbfSVM.conf b/technical_validation/gender_classification/conf/train_rbfSVM.conf new file mode 100644 index 00000000..3f4b1d0f --- /dev/null +++ b/technical_validation/gender_classification/conf/train_rbfSVM.conf @@ -0,0 +1,11 @@ +[default] +#model = linearSVM, LogisticRegression, rbfSVM +model = rbfSVM +seed = 42 + +[rbfSVM] +C = 100 +kernel=rbf +class_weight=balanced +probability=True +verbose = True \ No newline at end of file diff --git a/technical_validation/gender_classification/data/breathing-deep/all b/technical_validation/gender_classification/data/breathing-deep/all new file mode 100644 index 00000000..8bc9653b --- /dev/null +++ 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100644 index 00000000..9f4f219c --- /dev/null +++ b/technical_validation/gender_classification/local/classification.py @@ -0,0 +1,185 @@ +# created by DebarpanB +# date 26th August, 2022 + +import argparse, configparser +import numpy as np +import pandas as pd +import pickle +import os +import random +from sklearn.decomposition import PCA +from sklearn.preprocessing import StandardScaler +from sklearn.linear_model import LogisticRegression +from sklearn.ensemble import RandomForestClassifier +from sklearn.model_selection import train_test_split +from sklearn.metrics import auc +from matplotlib import pyplot as plt +from pdb import set_trace as bp + +SEED = 42 +random.seed(SEED) +np.random.seed(SEED) + +def score(reference_labels,sys_scores,thresholds=np.arange(0,1,0.0001)): + + # Arrays to store true positives, false positives, true negatives, false negatives + TP = np.zeros((len(reference_labels),len(thresholds))) + TN = np.zeros((len(reference_labels),len(thresholds))) + for keyCnt in range(len(sys_scores)): # Repeat for each recording + sys_labels = (sys_scores[keyCnt]>=thresholds)*1 # System label for a range of thresholds as binary 0/1 + gt = reference_labels[keyCnt] + + ind = np.where(sys_labels == gt) # system label matches the ground truth + if gt==1: # ground-truth label=1: True positives + TP[keyCnt,ind]=1 + else: # ground-truth label=0: True negatives + TN[keyCnt,ind]=1 + + total_positives = sum(reference_labels) # Total number of positive samples + total_negatives = len(reference_labels)-total_positives # Total number of negative samples + + TP = np.sum(TP,axis=0) # Sum across the recordings + TN = np.sum(TN,axis=0) + + TPR = TP/total_positives # True positive rate: #true_positives/#total_positives + TNR = TN/total_negatives # True negative rate: #true_negatives/#total_negatives + + AUC = auc( 1-TNR, TPR ) # AUC + + return AUC, TPR, TNR + +def get_data(file_list,feats_file,labels_file,shuffle=False): + #bp() + #%% read the list of files + file_list = open(file_list).readlines() + file_list = [line.strip().split() for line in file_list] + + #%% read labels + temp = open(labels_file).readlines() + temp = [line.strip().split() for line in temp] + labels={} + categories = ['female', 'male'] + for fil,label in temp: + labels[fil]=categories.index(label) + del temp + + #%% read feats.scp + temp = open(feats_file).readlines() + temp = [line.strip().split() for line in temp] + feats={} + for fil,filpath in temp: + feats[fil]=filpath + del temp + + #%% make examples + egs = [] + for fil,_ in file_list: + if feats.get(fil,None): + F = pickle.load(open(feats[fil],'rb')) + label = labels.get(fil,None) + if label is not None: + egs.append( np.concatenate( (F.mean(axis=0).reshape(1,-1),np.array([label]).reshape(1,-1)),axis=1 ) ) + + egs = np.vstack(egs) + + if shuffle: + np.random.shuffle(egs) + return egs[:,:-1], egs[:,-1] + +def expand(x, y, gap=1e-4): + add = np.tile([0, gap, np.nan], len(x)) + x1 = np.repeat(x, 3) + add + y1 = np.repeat(y, 3) + add + return x1, y1 + +def main(config, datadir_name, audiocategory, output_dir): + # bp() + print(audiocategory) + datadir = os.path.join(datadir_name, audiocategory) + # Training dataset + train_feats, train_labels = get_data(datadir+"/all.scp",datadir+"/feats.scp",datadir+"/all", shuffle=True) + train_feats = train_feats[:, :int(train_feats.shape[1]/3)] + + X_train, X_test, y_train, y_test = train_test_split(train_feats, train_labels, test_size=0.3, random_state=SEED) + X_train, X_val, y_train, y_val = train_test_split(X_train, y_train, test_size =0.21, random_state=SEED) + + if config['default']['classifier']=='RandomForest': + print(config['default']['classifier']) + scaler = StandardScaler(with_mean=True, with_std=False) + # X_train = scaler.fit_transform(X_train) + # X_val = scaler.transform(X_val) + # X_test = scaler.transform(X_test) + + clf = RandomForestClassifier(n_estimators=int(config[config['default']['classifier']]['n_estimators']), + criterion=config[config['default']['classifier']]['criterion'], + random_state=SEED) + clf.fit(X_train, y_train) + val_auc, _, _ = score(y_val.tolist(), clf.predict_proba(X_val)[:,1].tolist()) + print(f'Val auc: {val_auc}') + # exit() + test_auc, _, _ = score(y_test.tolist(), clf.predict_proba(X_test)[:,1].tolist()) + print(f'Test auc: {test_auc}') + exit() + test_accuracy = (np.count_nonzero(clf.predict(X_test)==y_test)*100)/y_test.shape[0] + print(f'Test accuracy: {test_accuracy}') + op_save_path = os.path.join(output_dir, config['default']['classifier']) + if not os.path.exists(op_save_path): os.mkdir(op_save_path) + np.save(os.path.join(op_save_path, 'y_true.npy'), y_test) + np.save(os.path.join(op_save_path, 'y_pred.npy'), clf.predict(X_test)) + np.save(os.path.join(op_save_path, 'y_pred_proba.npy'), clf.predict_proba(X_test)) + elif config['default']['classifier']=='LogisticRegression': + print(config['default']['classifier']) + scaler = StandardScaler(with_mean=True, with_std=False) + # X_train = scaler.fit_transform(X_train) + # X_val = scaler.transform(X_val) + # X_test = scaler.transform(X_test) + clf = LogisticRegression(C=float(config[config['default']['classifier']]['C']), + class_weight=config[config['default']['classifier']]['class_weight'], + max_iter=int(config[config['default']['classifier']]['max_iter']), + random_state=SEED) + clf.fit(X_train, y_train) + val_auc, _, _ = score(y_val.tolist(), clf.predict_proba(X_val)[:,1].tolist()) + print(f'Val auc: {val_auc}') + # exit() + test_auc, _, _ = score(y_test.tolist(), clf.predict_proba(X_test)[:,1].tolist()) + print(f'Test auc: {test_auc}') + exit() + # val_accuracy = (np.count_nonzero(clf.predict(X_val)==y_val)*100)/y_val.shape[0] + # print(f'Val accuracy: {val_accuracy}') + test_accuracy = (np.count_nonzero(clf.predict(X_test)==y_test)*100)/y_test.shape[0] + print(f'Test accuracy: {test_accuracy}') + op_save_path = os.path.join(output_dir, config['default']['classifier']) + if not os.path.exists(op_save_path): os.mkdir(op_save_path) + np.save(os.path.join(op_save_path, 'y_true.npy'), y_test) + np.save(os.path.join(op_save_path, 'y_pred.npy'), clf.predict(X_test)) + np.save(os.path.join(op_save_path, 'y_pred_proba.npy'), clf.predict_proba(X_test)) + else: + print('unknown classifier. exiting...') + exit() + + #plot + # cdict = {0: 'red', 1: 'blue', 2: 'green'} + # fig, ax = plt.subplots() + # for g in np.unique(train_labels): + # ix = np.where(train_labels == g) + # ax.scatter(X_proj[ix][:,0], X_proj[ix][:,1], c = cdict[g], label = g, s = 100, alpha=0.4*(2.1-g)) + # #ax.scatter(*expand(X_proj[ix][:,0], X_proj[ix][:,1]), lw=0, c = cdict[g], label = g, s = 100, alpha=0.5) + # ax.legend() + # save_plot_dir = outdir+'/'+config['default']['type'] + # if not os.path.exists(save_plot_dir): os.mkdir(save_plot_dir) + # plt.savefig(save_plot_dir+'/plot.png') + + +if __name__=='__main__': + parser = argparse.ArgumentParser() + parser.add_argument('--classification_config', '-c', required=True) + parser.add_argument('--datadir', '-d', required=True) + parser.add_argument('--audiocategory', '-a', required=True) + # parser.add_argument('--metadata_file', '-m', required=True) + parser.add_argument('--output_dir', '-o', required=True) + args = parser.parse_args() + + config = configparser.ConfigParser() + config.read(args.classification_config) + + main(config, args.datadir, args.audiocategory, args.output_dir) \ No newline at end of file diff --git a/technical_validation/gender_classification/local/feature_extraction.py b/technical_validation/gender_classification/local/feature_extraction.py new file mode 100755 index 00000000..8e629bf7 --- /dev/null +++ b/technical_validation/gender_classification/local/feature_extraction.py @@ -0,0 +1,137 @@ +import argparse, configparser +import pickle +import librosa +import numpy as np +import torchaudio +import torch +from pdb import set_trace as bp + +def compute_SAD(sig,fs,threshold=0.0001,sad_start_end_sil_length=100, sad_margin_length=50): + ''' Compute threshold based sound activity ''' + # Leading/Trailing margin + sad_start_end_sil_length = int(sad_start_end_sil_length*1e-3*fs) + # Margin around active samples + sad_margin_length = int(sad_margin_length*1e-3*fs) + + sample_activity = np.zeros(sig.shape) + sample_activity[np.power(sig,2)>threshold] = 1 + sad = np.zeros(sig.shape) + for i in range(sample_activity.shape[0]): + if sample_activity[i] == 1: sad[i-sad_margin_length:i+sad_margin_length] = 1 + sad[0:sad_start_end_sil_length] = 0 + sad[-sad_start_end_sil_length:] = 0 + return sad + + +def read_audio(file_path,sampling_rate): + fs=librosa.get_samplerate(file_path) + try: + s,fs = librosa.load(file_path,sr=sampling_rate) + if np.mean(s)==0 or len(s)<1024: + raise ValueError() + # waveform level amplitude normalization + s = s/np.max(np.abs(s)) + sad = compute_SAD(s,fs) + s = s[np.where(sad==1)] + except ValueError: + s = None + print("Read audio failed for "+file_path) + return s, file_path.split('/')[-2] + +def compute_mfcc(s,config): + # Compute MFCC using librosa toolkit. + F = librosa.feature.mfcc(s,sr=int(config['default']['sampling_rate']), + n_mfcc=int(config['mfcc']['n_mfcc']), + n_fft = int(config['default']['window_size']), + hop_length = int(config['default']['window_shift']), + n_mels = int(config['mfcc']['n_mels']), + fmax = int(config['mfcc']['fmax'])) + + features = np.array(F) + if config['mfcc']['add_deltas'] in ['True','true','TRUE','1']: + deltas = librosa.feature.delta(F) + features = np.concatenate((features,deltas),axis=0) + + if config['mfcc']['add_delta_deltas'] in ['True','true','TRUE','1']: + ddeltas = librosa.feature.delta(F,order=2) + features = np.concatenate((features,ddeltas),axis=0) + + return features + +def compute_logMelSpec(s, config): + ''' Feature preparation + Steps: + 1. Apply feature extraction to waveform + 2. Convert amplitude to dB if required + 3. Append delta and delta-delta features + ''' + #bp() + F_extractor = torchaudio.transforms.MelSpectrogram(sample_rate=int(config['default']['sampling_rate']), + n_fft= int(config['default']['window_size']), + n_mels= int(config['logMelSpec']['n_mels']), + f_max= int(config['logMelSpec']['f_max']), + hop_length= int(config['default']['window_shift'])) + F = F_extractor(torch.tensor(s)) + if config['default']['feature_type'] == 'logMelSpec': + F = torchaudio.functional.amplitude_to_DB(F,multiplier=10,amin=1e-10,db_multiplier=0) + Fo=F + if config['logMelSpec']['compute_deltas'] == 'True' : + FD = torchaudio.functional.compute_deltas(F) + Fo = torch.cat((F,FD),dim=0) + if config['logMelSpec']['compute_delta_deltas'] == 'True': + FD = torchaudio.functional.compute_deltas(F) + FDD = torchaudio.functional.compute_deltas(FD) + Fo = torch.cat((F,FD,FDD),dim=0) + return (Fo.T.numpy()) + +def main(config, in_wav_list, out_folder): + + in_wav_list = open(in_wav_list).readlines() + in_wav_list = [line.strip().split(" ") for line in in_wav_list] + + feats_list=[] + bad_ids_list=[] + for file_id,file_path in in_wav_list: + s, aud_id = read_audio(file_path,int(config['default']['sampling_rate'])) + + if s is None: + bad_ids_list.append(aud_id) + continue + + # sad = compute_SAD(s,config) + # ind=np.where(sad==1) + # s = s[ind] # Equivalent to stripping the silence portions of the waveform + if len(s)/int(config['default']['sampling_rate'])<0.5 or np.sum(s)==0: + bad_ids_list.append(aud_id) + continue + + if config['default']['feature_type'] == 'mfcc': + f = compute_mfcc(s,config) + elif config['default']['feature_type'] == 'logMelSpec': + f = compute_logMelSpec(s,config) + else: + raise ValueError("Need to implement the feature: "+config['default']['feature_type']) + + out_file_name = out_folder+"/"+file_id+'_'+config['default']['feature_type']+'.pkl' + with open(out_folder+"/"+file_id+'_'+config['default']['feature_type']+'.pkl','wb') as fp: + pickle.dump(f,fp) + feats_list.append((file_id,out_file_name)) + with open(out_folder+"/feats.scp","w") as f: + for file_id,out_file_name in feats_list: + f.write(file_id+" "+out_file_name+"\n") + np.save(out_folder+"/bad_ids.npy", np.array(bad_ids_list)) + + print("Feature extraction completed for "+str(len(in_wav_list))+" files") + print("Feature matrices saved to "+out_folder) + +if __name__=='__main__': + + parser = argparse.ArgumentParser() + parser.add_argument('--config','-c',required=True) + parser.add_argument('--in_wav_list','-i',required=True) + parser.add_argument('--out_folder','-o',required=False) + args = parser.parse_args() + + config = configparser.ConfigParser() + config.read(args.config) + main(config, args.in_wav_list, args.out_folder) diff --git a/technical_validation/gender_classification/local/filter_list.py b/technical_validation/gender_classification/local/filter_list.py new file mode 100644 index 00000000..a9c9b1b4 --- /dev/null +++ b/technical_validation/gender_classification/local/filter_list.py @@ -0,0 +1,31 @@ +# created by DebarpanB +# date 26th August, 2022 + +import argparse, configparser +from ast import parse +from turtle import pd +import numpy as np +import pandas as pd + +def main(featslist, labellist, pathlist): + df_feats = pd.read_csv(featslist, header=None, delimiter=' ') + df_feats.columns = ['id', 'feat_path'] + + df_labels = pd.read_csv(labellist, header=None, delimiter=' ') + df_labels.columns = ['id', 'label'] + + df_path = pd.read_csv(pathlist, header=None, delimiter=' ') + df_path.columns = ['id', 'path'] + + df_labels[(df_labels.id.isin(df_feats.id.values))].to_csv(labellist, header=None, index=False, sep=' ') + df_path[(df_path.id.isin(df_feats.id.values))].to_csv(pathlist, header=None, index=False, sep=' ') + + +if __name__=='__main__': + parser = argparse.ArgumentParser() + parser.add_argument('--featslist', '-f', required=True) + parser.add_argument('--labellist', '-l', required=True) + parser.add_argument('--pathlist', '-s', required=True) + args = parser.parse_args() + + main(args.featslist, args.labellist, args.pathlist) \ No newline at end of file diff --git a/technical_validation/gender_classification/local/prepare_list.py b/technical_validation/gender_classification/local/prepare_list.py new file mode 100644 index 00000000..a9bd6cec --- /dev/null +++ b/technical_validation/gender_classification/local/prepare_list.py @@ -0,0 +1,43 @@ +# created by DebarpanB +# date 26th August, 2022 + +import argparse, configparser +import pickle +import pandas as pd +import librosa +import numpy as np +import torchaudio +import torch +from pdb import set_trace as bp + +def main(annotation_file, metadata_file, pathfile, outlist, outpath): + df_metadata = pd.read_csv(metadata_file) + df_annotation = pd.read_csv(annotation_file) + df_annotation["id"] = df_annotation["FILENAME"].str.split("_", n=1, expand=True)[0] + df_annotation_drop = df_annotation.drop(columns=["FILENAME"]).iloc[:, [1, 0]] + genders = [] + for fid in df_annotation_drop.id.values: + genders.append(df_metadata[df_metadata.id==fid].g.values[0]) + df_annotation_drop['gender'] = genders + df_annotation_drop = df_annotation_drop[(df_annotation_drop[' QUALITY'].isin([1,2]))].drop(columns=[' QUALITY']) + df_annotation_drop = df_annotation_drop[(df_annotation_drop['gender'].isin(['male', 'female']))] + df_annotation_drop.to_csv(outlist, header=None, index=False, sep=' ') + + df_path = pd.read_csv(pathfile, header=None, delimiter=' ') + df_path.columns = ['id', 'path'] + df_path_select = df_path[(df_path.id.isin(df_annotation.FILENAME.values))] + assert df_annotation.shape[0]==df_path_select.shape[0] + df_path_select["id"] = df_path_select["id"].str.split("_", n=1, expand=True)[0] + df_path_select[(df_path_select.id.isin(df_annotation_drop.id.values))].to_csv(outpath, header=None, index=False, sep=' ') + + +if __name__=='__main__': + parser = argparse.ArgumentParser() + parser.add_argument('--annotation', '-a', required=True) + parser.add_argument('--pathfile', '-p', required=True) + parser.add_argument('--outlist', '-l', required=True) + parser.add_argument('--outpath', '-s', required=True) + parser.add_argument('--metadata_file', '-m', required=True) + args = parser.parse_args() + + main(args.annotation, args.metadata_file, args.pathfile, args.outlist, args.outpath) \ No newline at end of file diff --git a/technical_validation/gender_classification/metadata_files/combined_data.csv b/technical_validation/gender_classification/metadata_files/combined_data.csv new file mode 100644 index 00000000..6a3211f6 --- /dev/null +++ b/technical_validation/gender_classification/metadata_files/combined_data.csv @@ -0,0 +1,2747 @@ 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Bangalore,Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +sbdVe2aEGKeFcPXdhSf5QOuA5qA3,70,healthy,2020-04-14,y,male,India,Noida,Uttar Pradesh,,,,True,,,,,,,,,,,,,,,,,,,,,,, +bbemMSSF2DWykY2lW3pFokk39Wr1,20,healthy,2020-04-15,y,male,India,Indiranagar,Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +jx5lw63NN0SESDVLpYEQTHXuzti2,39,healthy,2020-04-15,y,male,India,Chennai,Tamil Nadu,,,,,,,,,,,,,,,,,,,,,,,,,,, +cFePAw64vTSRzgy3ZXZFGC1E7rS2,25,healthy,2020-04-15,y,male,India,Thiruvananthapuram,Kerala,,,,,,,,,,,,,,,,,,,,,,,,,,, +7uVROrqAKPMofUKBkPhYGgeU1513,28,healthy,2020-04-15,y,male,India,Bangalore,Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +xTrcp3vDL8bkpVEICdd1YsOURKx1,10,healthy,2020-04-15,y,male,India,East Delhi ,Delhi,,,,,,,,,,,,,,,,,,,,,,,,,,, +e5xiRpxobLe69psjXzZtitwdxpg1,31,healthy,2020-04-15,y,male,India,Nasik,Maharashtra,,,,,,,,,,,,,,,,,,,,,,,,,,, +dEM0ehwUlrWLDRwRyFVY35hHfDG3,24,resp_illness_not_identified,2020-04-15,y,female,India,Vasco da gama ,Goa,,,,,,,,,,,,,,,,,,,,,,,,,,, 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Nadu,,,,,,,,,,,,,,,,,,,,,,,,,,, +nHni2h50bzR6jh4FDPgY2NtVs7I2,32,healthy,2020-04-15,y,male,Finland,Espoo,Uusimaa,,,,,,,,,,,,,,,,,,,,,,,,,,, +3oM1GutSzARkQnaiMdIUMOSczz42,26,healthy,2020-04-15,y,female,India,Bangalore,Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +oTCyHYFIjtezHe2Tr9yZg8Lj5sv2,41,healthy,2020-04-15,y,female,India,"IISc., Bengaluru",Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +38CylWLQxybGkrRABrmg63KnAJd2,19,healthy,2020-04-15,y,male,India,Ernakulam,Kerala,,,,,,,,,,,,,,,,,,,,,,,,,,, +cAdvtOxMKHg9hO3IbimCRK9Vooi1,35,healthy,2020-04-15,y,male,India,Bangalore,Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +Eik9USYv51RYy1mxzPOGxPLhn4o1,31,healthy,2020-04-15,y,male,India,Rangareddy,Telangana,,True,,,,,,,,,,,,,,,,,,,,,,,,, +OmMVi6kdnHbu8sKZsh6HsGHm4Cs1,30,healthy,2020-04-16,y,male,India,Bangalore,Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +MCyZwW6oHlddq3Cy7QRwPHw5gof1,25,healthy,2020-04-16,y,male,India,Vaishali,Bihar,,,,,,,,,,,,,,,,,,,,,,,,,,, +f1tDfcVYVlOPYBAWP1ZDMdGER4m2,35,healthy,2020-04-16,y,male,India,R K Hegde Nagar,Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +j6TNknVPY1Y5LO4PYT6RoykWbha2,28,healthy,2020-04-15,n,male,India,Bengaluru,Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +3W9lHLbMzRVftjy3sxNnXwOTy6q1,27,healthy,2020-04-16,y,female,India,Kamrup Metro,Assam,,,,,,,,,,,,,,,,,,,,,,,,,,, +TLfuOcZh0HfnVRRdez4CxLFiPki2,28,healthy,2020-04-14,y,male,India,Gurgaon,Haryana,,True,,,,,,,,,,,,,,,,,,,,,,,,, +IS3AoZuo0cXtuYb2aDWkrIWTciP2,30,healthy,2020-04-15,y,female,India,Bangalore,Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +9g7Qa5FMZgUoDcKvLIPLo7m6mOD3,25,healthy,2020-04-15,y,male,India,Vizianagaram,Andhra Pradesh,,,,,,,,,,,,,,,,,,,,,,,,,,, +nyOEOseZX2cXF7ItBTJP316eTrx2,39,healthy,2020-04-15,y,male,India,South,Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +wGREdkmvqncUfRgcia9679biMIC3,42,healthy,2020-04-16,y,female,India,Mumbai,Maharashtra,,,,,,,,,,,,,,,,,,,,,,,,,,, +11GcRROEvCReCSBzteGoFLw1GyS2,29,healthy,2020-04-16,y,male,India,"Borewell road, whitefield",Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, 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,Odisha,,,,,,,,,,,,,,,,,,,,,,,,,,, +ysvx8FCvKbPi3Z6Jkhcd6sNsnwn1,26,healthy,2020-04-15,y,male,India,"Maharaj Bada, Lashkar, Gwalior",Madhya Pradesh,,,,,,,,,,,,,,,,,,,,,,,,,,, +1gimjLEgqBdoHReixdq8HlEBfEr2,25,healthy,2020-04-15,y,male,India,Iisc,Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +TCLyqYcr88coeJe3jnikuqyjBvs1,44,healthy,2020-04-16,y,female,India,Kolkata,West Bengal,,,,,,,,,,,,,,,,,,,,,,,,,,, +9KCtOKDALHXZZpzXizYJxBQ2Ulz1,29,healthy,2020-04-15,y,male,India,Vizag,Andhra Pradesh,,,,True,,,,,,,,,,,,,,,,,,,,,,, +jP5F3ypFwtN53rC9dVSUG8sMqHr2,18,healthy,2020-04-15,y,male,India,Bangalore,Karnataka,,,,,,,,,,,,,,,,,,,,,,,,,,, +6sZ85LTF8WdTDcMX028uCjK4UH32,21,healthy,2020-04-15,y,male,India,Lucknow,Uttar Pradesh,,,,,,,,,,,,,,,,,,,,,,,,,,, +ok6CEL3947hifXVHHmCDt35a7D32,25,healthy,2020-04-15,y,male,India,Nagpur,Maharashtra,,,,,,,,,,,,,,,,,,,,,,,,,,, +5FcCm1G9aPbjeCwnAgd7UUQFK062,36,healthy,2020-04-15,y,female,India,pune ,Maharashtra,,,,,,,,,,,,,,,,,,,,,,,,,,, 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http://www.apache.org/licenses/LICENSE-2.0 +# +# THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED +# WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE, +# MERCHANTABLITY OR NON-INFRINGEMENT. +# See the Apache 2 License for the specific language governing permissions and +# limitations under the License. + + +# Parse command-line options. +# To be sourced by another script (as in ". parse_options.sh"). +# Option format is: --option-name arg +# and shell variable "option_name" gets set to value "arg." +# The exception is --help, which takes no arguments, but prints the +# $help_message variable (if defined). + + +### +### The --config file options have lower priority to command line +### options, so we need to import them first... +### + +# Now import all the configs specified by command-line, in left-to-right order +for ((argpos=1; argpos<$#; argpos++)); do + if [ "${!argpos}" == "--config" ]; then + argpos_plus1=$((argpos+1)) + config=${!argpos_plus1} + [ ! -r $config ] && echo "$0: missing config '$config'" && exit 1 + . $config # source the config file. + fi +done + + +### +### Now we process the command line options +### +while true; do + [ -z "${1:-}" ] && break; # break if there are no arguments + case "$1" in + # If the enclosing script is called with --help option, print the help + # message and exit. Scripts should put help messages in $help_message + --help|-h) if [ -z "$help_message" ]; then echo "No help found." 1>&2; + else printf "$help_message\n" 1>&2 ; fi; + exit 0 ;; + --*=*) echo "$0: options to scripts must be of the form --name value, got '$1'" + exit 1 ;; + # If the first command-line argument begins with "--" (e.g. --foo-bar), + # then work out the variable name as $name, which will equal "foo_bar". + --*) name=`echo "$1" | sed s/^--// | sed s/-/_/g`; + # Next we test whether the variable in question is undefned-- if so it's + # an invalid option and we die. Note: $0 evaluates to the name of the + # enclosing script. + # The test [ -z ${foo_bar+xxx} ] will return true if the variable foo_bar + # is undefined. We then have to wrap this test inside "eval" because + # foo_bar is itself inside a variable ($name). + eval '[ -z "${'$name'+xxx}" ]' && echo "$0: invalid option $1" 1>&2 && exit 1; + + oldval="`eval echo \\$$name`"; + # Work out whether we seem to be expecting a Boolean argument. + if [ "$oldval" == "true" ] || [ "$oldval" == "false" ]; then + was_bool=true; + else + was_bool=false; + fi + + # Set the variable to the right value-- the escaped quotes make it work if + # the option had spaces, like --cmd "queue.pl -sync y" + eval $name=\"$2\"; + + # Check that Boolean-valued arguments are really Boolean. + if $was_bool && [[ "$2" != "true" && "$2" != "false" ]]; then + echo "$0: expected \"true\" or \"false\": $1 $2" 1>&2 + exit 1; + fi + shift 2; + ;; + *) break; + esac +done + + +# Check for an empty argument to the --cmd option, which can easily occur as a +# result of scripting errors. +[ ! -z "${cmd+xxx}" ] && [ -z "$cmd" ] && echo "$0: empty argument to --cmd option" 1>&2 && exit 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annotationdir='annotations/LABELS/' +#audiodir='/data1/srikanthr/Coswara/data_preparation/Coswara-Data-Extracted' +# pathfile='path_files/wav.scp' +# metadata_file='metadata_files/combined_data.csv' +audiocategory='counting-normal' + +datadir_name='data' +#datadir=$datadir_name/$audiocategory +feature_dir_name='feats' +#feature_dir=$feature_dir_name/$audiocategory +output_dir='results' + +classification_config='conf/classification.conf' + +. parse_options.sh + +mkdir -p $output_dir + +if [ $stage -le 0 ]; then + + echo "==== classification =====" + python local/classification.py -c $classification_config -a $audiocategory -d $datadir_name -o $output_dir +fi diff --git a/technical_validation/gender_classification/run_feature_extraction.sh b/technical_validation/gender_classification/run_feature_extraction.sh new file mode 100755 index 00000000..ff5952cd --- /dev/null +++ b/technical_validation/gender_classification/run_feature_extraction.sh @@ -0,0 +1,45 @@ +# created by DebarpanB +# date 25th August, 2022 + +stage=0 + +annotationdir='annotations/LABELS/' +#audiodir='/data1/srikanthr/Coswara/data_preparation/Coswara-Data-Extracted' +pathfile='path_files/wav.scp' +audiocategory=$1 + +datadir_name='data' +datadir=$datadir_name/$audiocategory +feature_dir_name='feats' +feature_dir=$feature_dir_name/$audiocategory +metadata_file='metadata_files/combined_data.csv' +output_dir='results' + +classification_config='conf/classification.conf' +feats_config='conf/feature.conf' + +. parse_options.sh + +mkdir -p $datadir +mkdir -p $feature_dir +mkdir -p $output_dir + +if [ $stage -le 0 ]; then + echo "==== Preparing lists =====" + python local/prepare_list.py -a $annotationdir/${audiocategory}.csv -p $pathfile -m $metadata_file -l $datadir/all -s $datadir/all.scp +fi + +if [ $stage -le 1 ]; then + # Creates a separate pickle file containing feature matrix for each recording in the wav.scp + # Expects a data folder, with train_dev and eval folders inside. each folder has a wav.scp file + # Each row in wav.scp is formatted as: + # Feature matrices are written to: $feature_dir/{train_dev/eval_set}/_.pkl + # feature.conf specifies configuration settings for feature extraction + + echo "==== Feature extraction =====" + mkdir -p $feature_dir + #python local/feature_extraction.py -c $feats_config -i $datadir/all.scp -o $feature_dir + cp $feature_dir/feats.scp $datadir/feats.scp + #mv $feature_dir/bad_ids.npy $datadir/bad_ids.npy + python local/filter_list.py -f $datadir/feats.scp -l $datadir/all -s $datadir/all.scp +fi \ No newline at end of file