LoadImage now loads all the frames from animated images as a batch.

nodes.py

@@ -9,7 +9,7 @@ import math
 import time
 import random
 
-from PIL import Image, ImageOps
+from PIL import Image, ImageOps, ImageSequence
 from PIL.PngImagePlugin import PngInfo
 import numpy as np
 import safetensors.torch
@@ -1410,7 +1410,10 @@ class LoadImage:
     FUNCTION = "load_image"
     def load_image(self, image):
         image_path = folder_paths.get_annotated_filepath(image)
-        i = Image.open(image_path)
+        img = Image.open(image_path)
+        output_images = []
+        output_masks = []
+        for i in ImageSequence.Iterator(img):
             i = ImageOps.exif_transpose(i)
             image = i.convert("RGB")
             image = np.array(image).astype(np.float32) / 255.0
@@ -1420,7 +1423,17 @@ class LoadImage:
                 mask = 1. - torch.from_numpy(mask)
             else:
                 mask = torch.zeros((64,64), dtype=torch.float32, device="cpu")
-        return (image, mask.unsqueeze(0))
+            output_images.append(image)
+            output_masks.append(mask.unsqueeze(0))
+
+        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):