Update app.py

app.py

@@ -3,6 +3,7 @@ import requests
 from huggingface_hub import hf_hub_download
 import torch
 from PIL import Image
+import numpy as np
 
 # Mengunduh model dari Hugging Face
 model_path = hf_hub_download(repo_id="ahmadalfian/fruits_vegetables_classifier", filename="resnet50_finetuned.pth")
@@ -11,7 +12,9 @@ model_path = hf_hub_download(repo_id="ahmadalfian/fruits_vegetables_classifier",
 class FruitVegetableClassifier(torch.nn.Module):
     def __init__(self):
         super(FruitVegetableClassifier, self).__init__()
-        self.model = torch.load(model_path)
+        self.model = torch.nn.Sequential(
+            torch.load(model_path, map_location=torch.device('cpu'))  # Memastikan dimuat di CPU
+        )
         self.model.eval()
 
     def forward(self, x):
@@ -28,7 +31,7 @@ def predict(image):
 
     with torch.no_grad():
         outputs = model(image_tensor)
-    
+
     predictions = outputs.argmax(dim=1)
     return predictions.item()
 
@@ -47,7 +50,6 @@ def get_nutritional_info(food):
     data = response.json()
 
     if "foods" in data and len(data["foods"]) > 0:
-        # Inisialisasi total untuk nutrisi yang diinginkan
         nutrients_totals = {
             "Energy": 0,
             "Carbohydrate, by difference": 0,
@@ -108,4 +110,4 @@ iface = gr.Interface(
     description="Upload an image of a fruit or vegetable to classify and get its nutritional information."
 )
 
-iface.launch()
+iface.launch()