Updated local Ai internals

src/preprocessor/soundpreprocessor.py

@@ -11,6 +11,8 @@ from pyAudioAnalysis import audioBasicIO
 from pyAudioAnalysis import MidTermFeatures
 import numpy
 
+from birbnetes_iot_platform_raspberry import BirbnetesIoTPlatformStatusDriver
+
 """
 Abstract base class for Sender
 """
@@ -28,11 +30,11 @@ class SoundPreProcessor(AbcPreProcessor):
 
     def __init__(self):
         logging.info("Downloading current model...")
-        _, self._temp_model_name = tempfile.mkstemp()
+        temp_model_handle, self._temp_model_name = tempfile.mkstemp()
         self._temp_means_name = self._temp_model_name + "MEANS"
 
         logging.debug("Fetching model info...")
-
+        BirbnetesIoTPlatformStatusDriver.enqueue_pattern('green', [1])
         if config.SVM_MODEL_ID:
             model_id_to_get = config.SVM_MODEL_ID
         else:
@@ -44,13 +46,15 @@ class SoundPreProcessor(AbcPreProcessor):
         self._model_details = r.json()
 
         logging.debug("Downloading model...")
+        BirbnetesIoTPlatformStatusDriver.enqueue_pattern('green', [1])
         r = requests.get(f"{config.API_URL}/model/svm/{self._model_details['id']}")
         r.raise_for_status()
 
-        with open(self._temp_model_name, 'wb') as f:
+        with open(temp_model_handle, 'wb') as f:  # bruhtastic
             f.write(r.content)
 
         logging.debug("Downloading MEANS...")
+        BirbnetesIoTPlatformStatusDriver.enqueue_pattern('green', [1])
         r = requests.get(f"{config.API_URL}/model/svm/{self._model_details['id']}?means")
         r.raise_for_status()
 
@@ -69,9 +73,14 @@ class SoundPreProcessor(AbcPreProcessor):
             self._mid_window, self._mid_step, self._short_window, \
             self._short_step, self._compute_beat = load_model(self._temp_model_name)
 
+        target_class_name = self._model_details['target_class_name']
+
         logging.info("The loaded model contains the following classes: " + ", ".join(self._classes))
-        if config.SVM_TARGET_CLASS_NAME not in self._classes:
+        if target_class_name not in self._classes:
-            raise Exception(f"The specified target class {config.SVM_TARGET_CLASS_NAME} is not in the possible classes")
+            raise Exception(
+                f"The specified target class {target_class_name} is not in the possible classes (Wrong model info?)")
+
+        self._target_id = self._classes.index(target_class_name)
 
     def preprocesssignal(self, file_path: str) -> bool:
         """
@@ -107,16 +116,17 @@ class SoundPreProcessor(AbcPreProcessor):
 
         logging.debug("Running classification...")
 
-        target_id = self._classes.index(config.SVM_TARGET_CLASS_NAME)  # Might raise ValueError
-
         feature_vector = (mid_features - self._mean) / self._std
-        class_id, probability = classifier_wrapper(self._classifier, self._model_details['type'].lower(),
+        class_id, probability = classifier_wrapper(
-                                                   feature_vector)
+            self._classifier, self._model_details['type'].lower(), feature_vector
+        )
         class_id = int(class_id)  # faszom
 
-        logging.debug(f"Sample {file_path} identified as {self._classes[class_id]} with the probablility of {probability[class_id]}")
+        logging.debug(
+            f"Sample {file_path} identified as {self._classes[class_id]} with the probablility of {probability[class_id]}"
+        )
 
-        return bool(class_id == target_id)
+        return bool(class_id == self._target_id)
 
     def __del__(self):
         try:

src/utils/config.py

@@ -27,7 +27,6 @@ MQTT_PORT = int(os.getenv("GUARD_MQTT_PORT", 1883))
 MQTT_USERNAME = os.getenv("GUARD_MQTT_USERNAME", None)
 MQTT_PASSWORD = os.getenv("GUARD_MQTT_PASSWORD", None)
 
-SVM_TARGET_CLASS_NAME = os.environ.get("SVM_TARGET_CLASS_NAME", "chirp")
 SVM_MODEL_ID = os.environ.get("SVM_MODEL_ID")
 
 API_URL = os.environ.get("API_URL", "http://localhost:8080")