Update app.py

app.py

@@ -59,23 +59,23 @@ orientation_labels = {
 
 model_race = RaceClassifier(n_classes=4)
 model_race.to(device)
-model_race.load_state_dict(torch.load('best_model_race_deneme.pt', map_location=torch.device('cpu')))
+model_race.load_state_dict(torch.load('best_model_race.pt', map_location=torch.device('cpu')))
 
 model_age = RaceClassifier(n_classes=3)
 model_age.to(device)
-model_age.load_state_dict(torch.load('best_model_age_last.pt', map_location=torch.device('cpu')))
+model_age.load_state_dict(torch.load('best_model_age.pt', map_location=torch.device('cpu')))
 
 model_education = RaceClassifier(n_classes=2)
 model_education.to(device)
-model_education.load_state_dict(torch.load('best_model_education_last.pt', map_location=torch.device('cpu')))
+model_education.load_state_dict(torch.load('best_model_education.pt', map_location=torch.device('cpu')))
 
 model_gender = RaceClassifier(n_classes=4)
 model_gender.to(device)
-model_gender.load_state_dict(torch.load('best_model_gender_last.pt', map_location=torch.device('cpu')))
+model_gender.load_state_dict(torch.load('best_model_gender.pt', map_location=torch.device('cpu')))
 
 model_orientation = RaceClassifier(n_classes=2)
 model_orientation.to(device)
-model_orientation.load_state_dict(torch.load('best_model_orientation_last.pt', map_location=torch.device('cpu')))
+model_orientation.load_state_dict(torch.load('best_model_orientation.pt', map_location=torch.device('cpu')))
 
 
 def evaluate(model, input, mask):