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@@ -120,7 +120,7 @@ The model was trained using a Tesla T4 GPU on Google Cloud in the us-central reg
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  # Usage
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- Here's an example of how to use the model for inference on a new image. This assumes the model has been saved in a TensorFlow SavedModel format.
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  First, make sure you have TensorFlow installed:
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@@ -143,7 +143,7 @@ os.environ["KERAS_BACKEND"] = "jax"
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  loaded_model = keras.saving.load_model("hf://Recompense/FoodVision")
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- # Define the class names (replace with the actual class names from your training)
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  class_names = ['apple_pie', 'baby_back_ribs', 'baklava', 'beef_carpaccio', 'beef_tartare', 'beet_salad', 'beignets', 'bibimbap', 'bread_pudding', 'breakfast_burrito', 'bruschetta', 'buffalo_wings', 'caesar_salad', 'cannoli', 'caprese_salad', 'carrot_cake', 'cheesecake', 'cheese_plate', 'chicken_curry', 'chicken_quesadilla', 'chicken_wings', 'chocolate_cake', 'chocolate_mousse', 'churros', 'clam_chowder', 'club_sandwich', 'crab_cakes', 'creme_brulee', 'croque_madame', 'cup_cakes', 'deviled_eggs', 'donuts', 'dumplings', 'edamame', 'eggs_benedict', 'escargots', 'falafel', 'filet_mignon', 'fish_and_chips', 'foie_gras', 'french_fries', 'french_onion_soup', 'french_toast', 'fried_calamari', 'fried_chicken', 'frozen_yogurt', 'garlic_bread', 'gnocchi', 'greek_salad', 'grilled_cheese_sandwich', 'grilled_salmon', 'guacamole', 'gyros', 'hamburger', 'hot_dog', 'ice_cream', 'lasagna', 'lobster_bisque', 'lobster_roll_sandwich', 'macaroni_and_cheese', 'macarons', 'miso_soup', 'mussels', 'nachos', 'omelette', 'onion_rings', 'oysters', 'pad_thai', 'paella', 'pancakes', 'panna_cotta', 'peking_duck', 'pho', 'pizza', 'pork_chop', 'poutine', 'prime_rib', 'pulled_pork_sandwich', 'ramen', 'ravioli', 'red_velvet_cake', 'risotto', 'samosas', 'sashimi', 'scallops', 'shrimp_scampi', 'smores', 'spaghetti_bolognese', 'spaghetti_carbonara', 'spring_rolls', 'steak', 'strawberry_shortcake', 'sushi', 'tacos', 'takoyaki', 'tiramisu', 'tuna_tartare', 'waffles'] # Example class names
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  # Create a function to load and prepare images (from your notebook)
 
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  # Usage
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+ Here's an example of how to use the model for inference on a new image.
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  First, make sure you have TensorFlow installed:
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  loaded_model = keras.saving.load_model("hf://Recompense/FoodVision")
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+ # Define the class names (replace with the actual class names from your training), to test the model intitially you can use these class names and upload an image based on any class you choose
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  class_names = ['apple_pie', 'baby_back_ribs', 'baklava', 'beef_carpaccio', 'beef_tartare', 'beet_salad', 'beignets', 'bibimbap', 'bread_pudding', 'breakfast_burrito', 'bruschetta', 'buffalo_wings', 'caesar_salad', 'cannoli', 'caprese_salad', 'carrot_cake', 'cheesecake', 'cheese_plate', 'chicken_curry', 'chicken_quesadilla', 'chicken_wings', 'chocolate_cake', 'chocolate_mousse', 'churros', 'clam_chowder', 'club_sandwich', 'crab_cakes', 'creme_brulee', 'croque_madame', 'cup_cakes', 'deviled_eggs', 'donuts', 'dumplings', 'edamame', 'eggs_benedict', 'escargots', 'falafel', 'filet_mignon', 'fish_and_chips', 'foie_gras', 'french_fries', 'french_onion_soup', 'french_toast', 'fried_calamari', 'fried_chicken', 'frozen_yogurt', 'garlic_bread', 'gnocchi', 'greek_salad', 'grilled_cheese_sandwich', 'grilled_salmon', 'guacamole', 'gyros', 'hamburger', 'hot_dog', 'ice_cream', 'lasagna', 'lobster_bisque', 'lobster_roll_sandwich', 'macaroni_and_cheese', 'macarons', 'miso_soup', 'mussels', 'nachos', 'omelette', 'onion_rings', 'oysters', 'pad_thai', 'paella', 'pancakes', 'panna_cotta', 'peking_duck', 'pho', 'pizza', 'pork_chop', 'poutine', 'prime_rib', 'pulled_pork_sandwich', 'ramen', 'ravioli', 'red_velvet_cake', 'risotto', 'samosas', 'sashimi', 'scallops', 'shrimp_scampi', 'smores', 'spaghetti_bolognese', 'spaghetti_carbonara', 'spring_rolls', 'steak', 'strawberry_shortcake', 'sushi', 'tacos', 'takoyaki', 'tiramisu', 'tuna_tartare', 'waffles'] # Example class names
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  # Create a function to load and prepare images (from your notebook)