kurzti88066/Fahrsimulator_MSY2526_AI
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small changes and lazy import of tensorflow

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This commit is contained in:
Michael Weig 2026-02-16 18:58:18 +01:00
parent cf88f88814
commit 0088cef32a
2 changed files with 5 additions and 10 deletions
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1
predict_pipeline/config.yaml
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@ -8,6 +8,7 @@ model:
scaler: scaler:
use_scaling: False use_scaling: False
path = "C:"
mqtt: mqtt:
enabled: true enabled: true

14
predict_pipeline/predict_sample.py
View File

@ -9,7 +9,6 @@ import pickle
#sys.path.append('/home/edgekit/MSY_FS/fahrsimulator_msy2526_ai/tools') #sys.path.append('/home/edgekit/MSY_FS/fahrsimulator_msy2526_ai/tools')
sys.path.append(r"c:\\repo\\Fahrsimulator_MSY2526_AI\\tools") sys.path.append(r"c:\\repo\\Fahrsimulator_MSY2526_AI\\tools")
import db_helpers import db_helpers
import tensorflow as tf
import joblib import joblib
_MODEL_CACHE = {} _MODEL_CACHE = {}
@ -55,6 +54,7 @@ def callModel(sample, model_path):
elif suffix == ".joblib": elif suffix == ".joblib":
model = joblib.load(model_path) model = joblib.load(model_path)
elif suffix == ".keras": elif suffix == ".keras":
import tensorflow as tf
model = tf.keras.models.load_model(model_path) model = tf.keras.models.load_model(model_path)
else: else:
raise ValueError(f"Unsupported model format: {suffix}. Use .pkl, .joblib, or .keras.") 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.item()
return prediction.squeeze() return prediction.squeeze()
def buildMessage(valid, result: np.int32, config_file_path, sample=None): def buildMessage(valid, result: np.int32, config_file_path, sample=None):
with Path(config_file_path).open("r", encoding="utf-8") as f: with Path(config_file_path).open("r", encoding="utf-8") as f:
cfg = yaml.safe_load(f) cfg = yaml.safe_load(f)
@ -106,7 +103,6 @@ def buildMessage(valid, result: np.int32, config_file_path, sample=None):
} }
return message return message
def sendMessage(config_file_path, message): def sendMessage(config_file_path, message):
with Path(config_file_path).open("r", encoding="utf-8") as f: with Path(config_file_path).open("r", encoding="utf-8") as f:
cfg = yaml.safe_load(f) cfg = yaml.safe_load(f)
@ -186,11 +182,13 @@ def main():
sample = getLastEntryFromSQLite(database_path, table_name, row_key) sample = getLastEntryFromSQLite(database_path, table_name, row_key)
valid, sample = replace_nan(sample, config_file_path=config_file_path) valid, sample = replace_nan(sample, config_file_path=config_file_path)
if not valid: if not valid:
print("Sample invalid: more than 50% NaN.") print("Sample invalid: more than 50% NaN.")
message = buildMessage(valid, None, config_file_path, sample=sample) message = buildMessage(valid, None, config_file_path, sample=sample)
sendMessage(config_file_path, message) sendMessage(config_file_path, message)
return return
model_path = cfg["model"]["path"] model_path = cfg["model"]["path"]
sample_np = sample_to_numpy(sample) sample_np = sample_to_numpy(sample)
sample_np = scale_sample(sample_np, use_scaling=use_scaling) sample_np = scale_sample(sample_np, use_scaling=use_scaling)
@ -203,9 +201,5 @@ def main():
if __name__ == "__main__": if __name__ == "__main__":
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 # https://www.youtube.com/watch?v=Q09tWwz6WoI