Added helper function to load Gammatone filters impulses responses from a directory.

core/utils.py

@@ -72,7 +72,8 @@ def generate_signals(df, movement, in_place=True, drop_hrirs=True):
     return df
 
 
-def generate_augmented_labelled_dataset(signals, labels, symmetry=True, n_augment: int = 1, n_samples=None, sounds=None):
+def generate_augmented_labelled_dataset(signals, labels, symmetry=True, n_augment: int = 1, n_samples=None,
+                                        sounds=None):
     n_channels = 2
 
     if sounds is not None:
@@ -120,7 +121,7 @@ def generate_augmented_labelled_dataset(signals, labels, symmetry=True, n_augmen
         # inverse left and right ears signals, and changes the azimuth accordingly
         # e.g. if signal is coming from 45°, it comes from 315° after left/right ears signals inversion
         augmented_signals2 = np.flip(augmented_signals.copy(), axis=2)
-        augmented_labels2 = 360-augmented_labels.copy()
+        augmented_labels2 = 360 - augmented_labels.copy()
         augmented_signals = np.concatenate([augmented_signals, augmented_signals2])
         augmented_labels = np.concatenate([augmented_labels, augmented_labels2])
     return augmented_signals, augmented_labels
@@ -201,3 +202,26 @@ def set_gpus():
             print(e)
 
 
+def get_gtf_kernels(gtf_dirpath):
+    """
+    Load all files found in gtf_dirpath that starts with 'filter' and ends with '.wav'
+    and return a n-dimensional array of time-reversed loaded signals
+    :return:
+    """
+    import os
+    import scipy.io.wavfile
+    wav_files = [file for file in os.listdir(gtf_dirpath) if file.startswith('filter') and file.endswith('.wav')]
+
+    print(f'found {len(wav_files)} filters to be loaded...')
+
+    samplerates = []
+    gtf_irs = []
+    for wav_file in wav_files:
+        samplerate, data = scipy.io.wavfile.read(filename=os.path.join(gtf_dirpath, wav_file))
+        samplerates.append(samplerate)
+        gtf_irs.append(data)
+    gtf_irs = np.array(gtf_irs)
+    assert gtf_irs.shape[0] == len(wav_files)
+    kernels = np.flip(gtf_irs, axis=1)
+    kernels = np.transpose(kernels)
+    return kernels

pytests/test_utils.py

@@ -14,3 +14,9 @@ def test_load_ircam_morphological_data():
 
     # there should be a dataframe of shape (51,60)
     assert all_infos.shape == (51, 60)
+
+
+def test_get_gtf_kernels():
+    from core.utils import get_gtf_kernels
+    kernels = get_gtf_kernels("../gtf/")
+    assert kernels.shape == (512, 20)