From 0088cef32a4006af0895044ba4ddfc93bbf7a094 Mon Sep 17 00:00:00 2001
From: Michael <weigmi87303@th-nuernberg.de>
Date: Mon, 16 Feb 2026 18:58:18 +0100
Subject: [PATCH] small changes and lazy import of tensorflow

---
 predict_pipeline/config.yaml       |  1 +
 predict_pipeline/predict_sample.py | 14 ++++----------
 2 files changed, 5 insertions(+), 10 deletions(-)

diff --git a/predict_pipeline/config.yaml b/predict_pipeline/config.yaml
index abeabe9..a2d2586 100644
--- a/predict_pipeline/config.yaml
+++ b/predict_pipeline/config.yaml
@@ -8,6 +8,7 @@ model:
 
 scaler:
   use_scaling: False
+  path = "C:"
 
 mqtt:
   enabled: true
diff --git a/predict_pipeline/predict_sample.py b/predict_pipeline/predict_sample.py
index 3826ea3..37411ee 100644
--- a/predict_pipeline/predict_sample.py
+++ b/predict_pipeline/predict_sample.py
@@ -9,7 +9,6 @@ import pickle
 #sys.path.append('/home/edgekit/MSY_FS/fahrsimulator_msy2526_ai/tools')
 sys.path.append(r"c:\\repo\\Fahrsimulator_MSY2526_AI\\tools")
 import db_helpers
-import tensorflow as tf
 import joblib
 
 _MODEL_CACHE = {}
@@ -55,6 +54,7 @@ def callModel(sample, model_path):
         elif suffix == ".joblib":
             model = joblib.load(model_path)
         elif suffix == ".keras":
+            import tensorflow as tf
             model = tf.keras.models.load_model(model_path)
         else:
             raise ValueError(f"Unsupported model format: {suffix}. Use .pkl, .joblib, or .keras.")
@@ -83,9 +83,6 @@ def callModel(sample, model_path):
         return prediction.item()
     return prediction.squeeze()
 
-
-
-
 def buildMessage(valid, result: np.int32, config_file_path, sample=None):
     with Path(config_file_path).open("r", encoding="utf-8") as f:
         cfg = yaml.safe_load(f)
@@ -106,7 +103,6 @@ def buildMessage(valid, result: np.int32, config_file_path, sample=None):
     }
     return message
 
-
 def sendMessage(config_file_path, message):
     with Path(config_file_path).open("r", encoding="utf-8") as f:
         cfg = yaml.safe_load(f)
@@ -186,11 +182,13 @@ def main():
 
     sample = getLastEntryFromSQLite(database_path, table_name, row_key)
     valid, sample = replace_nan(sample, config_file_path=config_file_path)
+
     if not valid:
         print("Sample invalid: more than 50% NaN.")
         message = buildMessage(valid, None, config_file_path, sample=sample)
         sendMessage(config_file_path, message)
         return
+    
     model_path = cfg["model"]["path"]
     sample_np = sample_to_numpy(sample)
     sample_np = scale_sample(sample_np, use_scaling=use_scaling)
@@ -203,9 +201,5 @@ def main():
 if __name__ == "__main__":
     main()
 
-# to do:
-# config file
-# bei sample holen outlier ersetzen
-# mediane abspeichern
-# falls nur nan, dann sample verwerfen
+
 # https://www.youtube.com/watch?v=Q09tWwz6WoI