Fixed issues with class_names.txt in app.py

app.py

@@ -8,7 +8,7 @@ from model import create_effnetb2_model
 from timeit import default_timer as timer
 
 # Setup class names
-with open('demos/foodvision_big/class_names.txt', 'r') as f:
+with open('foodvision_big/class_names.txt', 'r') as f:
   class_names = [food_name.strip() for food_name in f.readlines()]
 
 ### 2. Model and transforms preparation ###
@@ -18,7 +18,7 @@ effnetb2, effnetb2_transforms = create_effnetb2_model(
 )
 
 # Load save weights
-effnetb2.load_state_dict(torch.load('demos/foodvision_big/09_pretrained_effnetb2_feature_extractor_food101_20_percent.pth', map_location=torch.device("cpu"))) # load the model to the CPU
+effnetb2.load_state_dict(torch.load('foodvision_big/09_pretrained_effnetb2_feature_extractor_food101_20_percent.pth', map_location=torch.device("cpu"))) # load the model to the CPU
 
 ### 3. Predict function ###
 def predict(img) -> tuple[dict, float]: