Update app.py

app.py

@@ -1,29 +1,20 @@
 from PIL import Image
-from transformers import ViTFeatureExtractor, ViTForImageClassification
 import warnings
 import requests
 import gradio as gr
 
 warnings.filterwarnings('ignore')
 
-# Load the pre-trained Vision Transformer model and feature extractor
-model_name = "google/vit-base-patch16-224"
-feature_extractor = ViTFeatureExtractor.from_pretrained(model_name)
-model = ViTForImageClassification.from_pretrained(model_name)
-
 # API key for the nutrition information
 api_key = 'XshljGSwf/pq3GcgBdHtOg==G9X2wnPqW5c6vp0F'
 
 def identify_image(image_path):
     """Identify the food item in the image."""
+    API_URL = "https://api-inference.huggingface.co/models/nateraw/food"
+    headers = {"Authorization": huggingface_api}
     image = Image.open(image_path)
-    inputs = feature_extractor(images=image, return_tensors="pt")
-    outputs = model(**inputs)
-    logits = outputs.logits
-    predicted_class_idx = logits.argmax(-1).item()
-    predicted_label = model.config.id2label[predicted_class_idx]
-    food_name = predicted_label.split(',')[0]
-    return food_name
+    response = requests.post(API_URL, headers=headers, data=image)
+    return response.json()[0]['label']
 
 def get_calories(food_name):
     """Get the calorie information of the identified food item."""