fix

Author: stefanotorneo

src/arduino/app_bricks/audio_classification/__init__.py

@@ -122,8 +122,7 @@ def classify_from_file(audio_path: str, confidence: float = 0.8) -> dict | None:
                     features = list(struct.unpack(fmt, frames))
                 else:
                     raise ValueError(f"Unsupported sample width: {samp_width} bytes. Cannot process this WAV file.")
-
-                classification = EdgeImpulseRunnerFacade.infer_from_features(features)
+                classification = AudioClassification.infer_from_features(features)
                 best_match = AudioDetector.get_best_match(classification, confidence)
                 if not best_match:
                     return None

src/arduino/app_bricks/motion_detection/__init__.py

@@ -26,7 +26,7 @@ def __init__(self, confidence: float = 0.4):
         """
         self._confidence = confidence
         super().__init__()
-        model_info = EdgeImpulseRunnerFacade.get_model_info()
+        model_info = self.get_model_info()
         if not model_info:
             raise ValueError("Failed to retrieve model information. Ensure the EI model runner service is running.")
         if model_info.frequency <= 0 or model_info.input_features_count <= 0:
@@ -133,7 +133,7 @@ def _detection_loop(self):
             return
 
         try:
-            ret = EdgeImpulseRunnerFacade.infer_from_features(features.tolist())
+            ret = self.infer_from_features(features.tolist())
             spotted_movement = self._movement_spotted(ret)
             if spotted_movement is not None:
                 keyword, confidence, complete_detection = spotted_movement

src/arduino/app_bricks/object_detection/__init__.py

@@ -31,7 +31,7 @@ def __init__(self, confidence: float = 0.3):
         """
         self.confidence = confidence
         super().__init__()
-        self._model_info = EdgeImpulseRunnerFacade.get_model_info()
+        self._model_info = self.get_model_info()
         if not self._model_info:
             raise ValueError("Failed to retrieve model information. Ensure the Edge Impulse service is running.")
 

src/arduino/app_bricks/vibration_anomaly_detection/__init__.py

@@ -48,7 +48,7 @@ def __init__(self, anomaly_detection_threshold: float = 1.0):
         """
         self._anomaly_detection_threshold = anomaly_detection_threshold
         super().__init__()
-        model_info = EdgeImpulseRunnerFacade.get_model_info()
+        model_info = self.get_model_info()
         if not model_info:
             raise ValueError("Failed to retrieve model information. Ensure the EI model runner service is running.")
         if model_info.frequency <= 0 or model_info.input_features_count <= 0:
@@ -133,7 +133,7 @@ def loop(self):
             if features is None or len(features) == 0:
                 return
 
-            ret = EdgeImpulseRunnerFacade.infer_from_features(features.tolist())
+            ret = self.infer_from_features(features.tolist())
             logger.debug(f"Inference result: {ret}")
             spotted_anomaly = self._extract_anomaly_score(ret)
             if spotted_anomaly is not None:

src/arduino/app_internal/core/ei.py

@@ -129,7 +129,7 @@ def infer_from_features(cls, features: list) -> dict | None:
         """
         try:
             url = cls._get_ei_url()
-            model_info = EdgeImpulseRunnerFacade.get_model_info()
+            model_info = cls.get_model_info()
             features = features[: int(model_info.input_features_count)]
 
             response = requests.post(f"{url}/api/features", json={"features": features})