Update tasks/audio.py

tasks/audio.py

@@ -10,7 +10,7 @@ import numpy as np
 import scipy
 
 from sklearn.preprocessing import StandardScaler
-from .fourier import FourierPreprocessor, Fourier
+from .fourier import FourierPreprocessor
 
 from .utils.evaluation import AudioEvaluationRequest
 from .utils.emissions import tracker, clean_emissions_data, get_space_info
@@ -22,7 +22,8 @@ router = APIRouter()
 
 DESCRIPTION = "Random Forest"
 ROUTE = "/audio"
-MODEL_PATH = Path(__file__).parent / "audio_models" / "RandomForestClassifier_withScaler.pkl"
+# MODEL_PATH = Path(__file__).parent / "audio_models" / "RandomForestClassifier_withScaler.pkl"
+MODEL_PATH = Path(__file__).parent / "audio_models" / "RandomForestClassifier_withScaler_rawData.pkl"
 # MODEL_PATH = Path(__file__).parent / "audio_models" / "RandomForestClassifier_withScaler_cloudpickle.pkl"
 
 
@@ -64,13 +65,14 @@ async def evaluate_audio(request: AudioEvaluationRequest):
 
     # Extract audio samples from test_dataset
     x_test = [sample["audio"]["array"] for sample in test_dataset]
+    x_test_preprocessed = FourierPreprocessor().transform(x_test)
 
     clf = joblib.load(MODEL_PATH)
 
     # with open(MODEL_PATH, 'rb') as f:
     #     clf = pickle.load(f)
     
-    predictions = clf.predict(x_test)
+    predictions = clf.predict(x_test_preprocessed)
 
     # --------------------------------------------------------------------------------------------
     # YOUR MODEL INFERENCE STOPS HERE