Update README.md

README.md

@@ -55,7 +55,7 @@ model = torch.load("lamem_all_clip_Lora_16.0R_8.0alphaLora_32_batch_0.00005_loss
 image = Image.open("image_path.jpg").convert("RGB")
 
 # Preprocess and predict
-def Mem_augmentations():
+def Mem_preprocess():
     transform = transforms.Compose([
     transforms.Resize(224),
     transforms.CenterCrop(size=(224,224)),  
@@ -66,7 +66,7 @@ def Mem_augmentations():
 ])
     return transform
 
-image = Mem_augmentations()(image).unsqueeze(0).to(device)
+image = Mem_preprocess()(image).unsqueeze(0).to(device)
 
 with torch.no_grad():
     mem_score = model(image).item()