diff --git a/compass_image_loader.py b/compass_image_loader.py
index b0be7ec..301867b 100644
--- a/compass_image_loader.py
+++ b/compass_image_loader.py
@@ -136,6 +136,65 @@ class CompassImageLoader:
     FUNCTION = "load_images"
     OUTPUT_NODE = False
 
+    def load_images(
+        self, directory, direction, modality, frame=None, width=0, height=0,
+        direction_in=None
+    ):
+        if direction_in and direction_in.strip():
+            resolved_direction = direction_in.strip()
+        elif direction and direction.strip():
+            resolved_direction = direction.strip()
+        else:
+            resolved_direction = ""
+
+        base_dir = folder_paths.get_input_directory()
+        target_dir = _resolve_target_dir(base_dir, directory, resolved_direction)
+        modality_path = os.path.join(target_dir, modality)
+
+        if not os.path.isdir(modality_path):
+            raise RuntimeError(f"Compass directory not found: {modality_path}")
+
+        files = _list_image_files(modality_path)
+        if not files:
+            raise RuntimeError(f"No images found in: {modality_path}")
+
+        if frame is None or str(frame).strip() == "":
+            selected_files = files
+            output_path = modality_path
+        else:
+            try:
+                index = int(str(frame).strip())
+            except (ValueError, TypeError):
+                raise RuntimeError(
+                    f"Invalid frame number: '{frame}'. Must be an integer."
+                )
+
+            if index < 0 or index >= len(files):
+                raise RuntimeError(
+                    f"Frame index {index} out of bounds. "
+                    f"Found {len(files)} images in {modality_path}."
+                )
+
+            selected_files = [files[index]]
+            output_path = os.path.join(modality_path, files[index])
+
+        tensors = []
+        final_w, final_h = 0, 0
+
+        for filename in selected_files:
+            filepath = os.path.join(modality_path, filename)
+            image = Image.open(filepath).convert("RGB")
+            image, final_w, final_h = _resize_image(image, width, height)
+
+            np_arr = np.array(image).astype(np.float32) / 255.0
+            tensors.append(torch.from_numpy(np_arr)[None,])
+
+        image_batch = (
+            tensors[0] if len(tensors) == 1 else torch.cat(tensors, dim=0)
+        )
+
+        return (image_batch, output_path, resolved_direction, final_w, final_h, len(selected_files))
+
     @classmethod
     def IS_CHANGED(
         cls, directory, direction, modality, frame=None, width=0, height=0,