diff --git a/nodes.py b/nodes.py
index ad474d3cd..1ca1f2c48 100644
--- a/nodes.py
+++ b/nodes.py
@@ -1695,44 +1695,41 @@ class PreviewImage(SaveImage):
                 "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
                 }
 
+
 class LoadImage:
     @classmethod
     def INPUT_TYPES(s):
         input_dir = folder_paths.get_input_directory()
-        files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f))]
-        files = folder_paths.filter_files_content_types(files, ["image"])
+        image_paths = []
+        for root, _, files in os.walk(input_dir, followlinks=True):
+            image_files = folder_paths.filter_files_content_types(files, ["image"])
+            for image_file in image_files:
+                path_relative = os.path.relpath(os.path.join(root, image_file), input_dir)
+                path_relative = path_relative.replace('\\', '/')
+                image_paths.append(path_relative)
         return {"required":
-                    {"image": (sorted(files), {"image_upload": True})},
+                    {"image": (sorted(list(set(image_paths))), {"image_upload": True})},
                 }
 
     CATEGORY = "image"
-    SEARCH_ALIASES = ["load image", "open image", "import image", "image input", "upload image", "read image", "image loader"]
-
     RETURN_TYPES = ("IMAGE", "MASK")
     FUNCTION = "load_image"
     def load_image(self, image):
         image_path = folder_paths.get_annotated_filepath(image)
-
         img = node_helpers.pillow(Image.open, image_path)
-
         output_images = []
         output_masks = []
         w, h = None, None
-
         for i in ImageSequence.Iterator(img):
             i = node_helpers.pillow(ImageOps.exif_transpose, i)
-
             if i.mode == 'I':
                 i = i.point(lambda i: i * (1 / 255))
             image = i.convert("RGB")
-
             if len(output_images) == 0:
                 w = image.size[0]
                 h = image.size[1]
-
             if image.size[0] != w or image.size[1] != h:
                 continue
-
             image = np.array(image).astype(np.float32) / 255.0
             image = torch.from_numpy(image)[None,]
             if 'A' in i.getbands():
@@ -1745,19 +1742,15 @@ class LoadImage:
                 mask = torch.zeros((64,64), dtype=torch.float32, device="cpu")
             output_images.append(image)
             output_masks.append(mask.unsqueeze(0))
-
             if img.format == "MPO":
                 break  # ignore all frames except the first one for MPO format
-
         if len(output_images) > 1:
             output_image = torch.cat(output_images, dim=0)
             output_mask = torch.cat(output_masks, dim=0)
         else:
             output_image = output_images[0]
             output_mask = output_masks[0]
-
         return (output_image, output_mask)
-
     @classmethod
     def IS_CHANGED(s, image):
         image_path = folder_paths.get_annotated_filepath(image)
@@ -1765,13 +1758,10 @@ class LoadImage:
         with open(image_path, 'rb') as f:
             m.update(f.read())
         return m.digest().hex()
-
     @classmethod
     def VALIDATE_INPUTS(s, image):
-        if not folder_paths.exists_annotated_filepath(image):
-            return "Invalid image file: {}".format(image)
-
         return True
+        
 
 class LoadImageMask:
     SEARCH_ALIASES = ["import mask", "alpha mask", "channel mask"]