Update app.py

app.py

@@ -4,13 +4,13 @@ from transformers import pipeline
 vit_classifier = pipeline("image-classification", model="ElioBaserga/fruits-and-vegetables-vit")
 clip_detector = pipeline(model="openai/clip-vit-large-patch14", task="zero-shot-image-classification")
 
-labels_oxford_pets = ['apple', 'banana', 'beetroot', 'bell pepper', 'cabbage', 'capsicum', 'carrot', 'cauliflower', 'chilli pepper', 'corn', 'cucumber', 'eggplant', 'garlic', 'ginger', 'grapes', 'jalepeno', 'kiwi', 'lemon', 'lettuce', 'mango', 'onion', 'orange', 'paprika', 'pear', 'peas', 'pineapple', 'pomegranate', 'potato', 'raddish', 'soy beans', 'spinach', 'sweetcorn', 'sweetpotato', 'tomato', 'turnip', 'watermelon']
+labels_fruit_and_vegetable = ['apple', 'banana', 'beetroot', 'bell pepper', 'cabbage', 'capsicum', 'carrot', 'cauliflower', 'chilli pepper', 'corn', 'cucumber', 'eggplant', 'garlic', 'ginger', 'grapes', 'jalepeno', 'kiwi', 'lemon', 'lettuce', 'mango', 'onion', 'orange', 'paprika', 'pear', 'peas', 'pineapple', 'pomegranate', 'potato', 'raddish', 'soy beans', 'spinach', 'sweetcorn', 'sweetpotato', 'tomato', 'turnip', 'watermelon']
 
 def classify_pet(image):
     vit_results = vit_classifier(image)
     vit_output = {result['label']: result['score'] for result in vit_results}
     
-    clip_results = clip_detector(image, candidate_labels=labels_oxford_pets)
+    clip_results = clip_detector(image, candidate_labels=labels_fruit_and_vegetable)
     clip_output = {result['label']: result['score'] for result in clip_results}
     
     return {"ViT Classification": vit_output, "CLIP Zero-Shot Classification": clip_output}