swap

pages/Model_Evaluation.py

@@ -93,22 +93,9 @@ val_transform = transforms.Compose([
     transforms.ToTensor(),
     transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
 ])
-
-# ---- Load Data from Hugging Face (cached) ----
-@st.cache_resource
-def load_test_data_from_huggingface():
-    dataset = load_dataset(
-        "Ci-Dave/DDR_dataset_train_test",
-        data_files={"test": "splits/test_labels_updated.csv"},
-        split="test"
-    )
-    df = dataset.to_pandas()
-    csv_path = "test_labels_temp.csv"
-    df.to_csv(csv_path, index=False)
-    dataset = DDRDataset(csv_path=csv_path, transform=val_transform)
     
-    # ---- DDRDataset Class Definition ----
-    class DDRDataset(Dataset):
+# ---- DDRDataset Class Definition ----
+class DDRDataset(Dataset):
         def __init__(self, csv_path, transform=None):
             self.data = pd.read_csv(csv_path)
             self.image_paths = self.data['image_path']
@@ -131,6 +118,19 @@ def load_test_data_from_huggingface():
                 image = self.transform(image)
     
             return image, torch.tensor(label, dtype=torch.long)
+    
+# ---- Load Data from Hugging Face (cached) ----
+@st.cache_resource
+def load_test_data_from_huggingface():
+    dataset = load_dataset(
+        "Ci-Dave/DDR_dataset_train_test",
+        data_files={"test": "splits/test_labels_updated.csv"},
+        split="test"
+    )
+    df = dataset.to_pandas()
+    csv_path = "test_labels_temp.csv"
+    df.to_csv(csv_path, index=False)
+    dataset = DDRDataset(csv_path=csv_path, transform=val_transform)
     return DataLoader(dataset, batch_size=32, shuffle=False)
 
 # ---- Load Model from Hugging Face (cached) ----