README fixes tags.

README.md

@@ -96,13 +96,15 @@ These attacks require access to model gradients:
 ## Usage
 
 ```python
-from datasets import load_dataset
+import json
 import torch
 from torchvision import transforms
 from PIL import Image
+from pathlib import Path
 
-# Load the dataset
-dataset = load_dataset("your-org/adversarial_pcam")
+# Load the dataset information
+with open('organized_dataset/dataset.json', 'r') as f:
+    dataset_info = json.load(f)
 
 # Define transformation
 transform = transforms.Compose([
@@ -110,20 +112,35 @@ transform = transforms.Compose([
     transforms.ToTensor()
 ])
 
-# Process samples
-def process_sample(example):
-    img = Image.open(example["image"]).convert("RGB")
-    return {"image": transform(img), "label": example["label"]}
-
-# Apply processing
-dataset = dataset.map(process_sample)
-
-# Access data
-img_tensor = dataset["train"][0]["image"]
-label = dataset["train"][0]["label"]
-
-print("Label:", label)
-print("Image shape:", img_tensor.shape)  # Should be (3, 224, 224)
+# Function to load and process images
+def load_image(image_path):
+    img = Image.open(image_path).convert("RGB")
+    return transform(img)
+
+# Example: Loading a set of related images (original, adversarial, and perturbation)
+for entry in dataset_info:
+    # Load adversarial image
+    adv_path = Path('organized_dataset') / entry['adversarial']
+    adv_image = load_image(adv_path)
+    
+    # Load original image
+    orig_path = Path('organized_dataset') / entry['original'][0]
+    orig_image = load_image(orig_path)
+    
+    # Load perturbation if available
+    if entry['perturbation']:
+        pert_path = Path('organized_dataset') / entry['perturbation']
+        pert_image = load_image(pert_path)
+    
+    # Access metadata
+    attack_type = entry['attack']
+    label = entry['label']
+    prediction = entry['prediction']
+    
+    print(f"Attack: {attack_type}")
+    print(f"True Label: {label}")
+    print(f"Model Prediction: {prediction}")
+    print(f"Image shapes: {adv_image.shape}")  # Should be (3, 224, 224)
 ```
 
 ## **📊 Attack Success Rates**