Update README.md

README.md

@@ -56,13 +56,12 @@ image = Image.open("image_path.jpg").convert("RGB")
 # Preprocess and predict
 def Mem_preprocess():
     transform = transforms.Compose([
-    transforms.Resize(224),
-    transforms.CenterCrop(size=(224,224)),  
-    transforms.ToTensor(),
-    # Note: The model normalizes the image inside the forward pass
-    # using mean = (0.48145466, 0.4578275, 0.40821073) and 
-    # std = (0.26862954, 0.26130258, 0.27577711)
-])
+        transforms.Resize(224),
+        transforms.CenterCrop(size=(224, 224)),  
+        transforms.ToTensor(),
+        transforms.Normalize(mean=(0.48145466, 0.4578275, 0.40821073), 
+                             std=(0.26862954, 0.26130258, 0.27577711))
+    ])
     return transform
 
 image = Mem_preprocess()(image).unsqueeze(0).to(device)