processing framework

FeatureExtraction/test_panns.py

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+import logging
+from audiopreprocessing import triggerlog
+#logger = logging.getLogger(__name__)
+import sys
+logging.basicConfig(format="%(asctime)s/%(levelname)s: [%(module)s] %(message)s", level=logging.INFO, handlers=[logging.FileHandler('test_panns.log'), logging.StreamHandler(sys.stdout)])
+from pathlib import Path
+from mtafe_panns import mtafe_panns
+from dataset_files import random_audio_chunk, serialize_dict_obj
+mtafe = mtafe_panns(
+    audio_paths=random_audio_chunk(4),
+    max_audio_in_queue=4,
+    audio_feeder_threads=4,
+    feature_extractor_threads=1,
+    desired_sr=32000,
+    force_mono=False,
+    chunk_length=15,
+    chunk_overlap=2,
+    batch_size=32
+)
+mtafe.extract()
+
+print("Saving inferenced results to file...")
+p = Path('./test_panns.pkl')
+serialize_dict_obj(p, mtafe.features)