diff --git a/IPAdapterPlus.py b/IPAdapterPlus.py
index 65b95a7..912bcb1 100644
--- a/IPAdapterPlus.py
+++ b/IPAdapterPlus.py
@@ -1334,20 +1334,26 @@ class IPAdapterWeights:
     @classmethod
     def INPUT_TYPES(s):
         return {"required": {
-            "weights": ("STRING", {"default": '1.0', "multiline": True }),
-            "timing": (["custom", "linear", "ease_in_out", "ease_in", "ease_out", "reverse_in_out", "random"], ),
+            "weights": ("STRING", {"default": '1.0, 0.0', "multiline": True }),
+            "timing": (["custom", "linear", "ease_in_out", "ease_in", "ease_out", "random"], ),
             "frames": ("INT", {"default": 0, "min": 0, "max": 9999, "step": 1 }),
             "start_frame": ("INT", {"default": 0, "min": 0, "max": 9999, "step": 1 }),
             "end_frame": ("INT", {"default": 9999, "min": 0, "max": 9999, "step": 1 }),
-            },
+            "add_starting_frames": ("INT", {"default": 0, "min": 0, "max": 9999, "step": 1 }),
+            "add_ending_frames": ("INT", {"default": 0, "min": 0, "max": 9999, "step": 1 }),
+            "method": (["full batch", "shift batches", "alternate batches"], { "default": "full batch" }),
+            }, "optional": {
+                "image": ("IMAGE",),
+            }
         }
 
-    RETURN_TYPES = ("FLOAT",)
+    RETURN_TYPES = ("FLOAT", "FLOAT", "INT", "IMAGE", "IMAGE")
+    RETURN_NAMES = ("weights", "weights_invert", "total_frames", "image_1", "image_2")
     FUNCTION = "weights"
 
     CATEGORY = "ipadapter/utils"
 
-    def weights(self, weights, timing, frames, start_frame, end_frame):
+    def weights(self, weights, timing, frames, start_frame, end_frame, add_starting_frames, add_ending_frames, method, image=None):
         import random
 
         # convert the string to a list of floats separated by commas or newlines
@@ -1355,6 +1361,7 @@ class IPAdapterWeights:
         weights = [float(weight) for weight in weights.split(",") if weight.strip() != ""]
 
         if timing != "custom":
+            frames = max(frames, 2)
             start = 0.0
             end = 1.0
 
@@ -1379,19 +1386,92 @@ class IPAdapterWeights:
                     weights.append(start + (end - start) * math.sin(i / n * math.pi / 2))
                 elif timing == "ease_out":
                     weights.append(start + (end - start) * (1 - math.cos(i / n * math.pi / 2)))
-                elif timing == "reverse_in_out":
-                    weights.append(start + (end - start) * (1 - math.sin((1 - i / n) * math.pi / 2)))
                 elif timing == "random":
                     weights.append(random.uniform(start, end))
-            weights[-1] = end if timing != "random" else weights[-1]
 
+            weights[-1] = end if timing != "random" else weights[-1]
             if end_frame < frames:
                 weights.extend([end] * (frames - end_frame))
 
         if len(weights) == 0:
             weights = [0.0]
+                
+        frames = len(weights)
+        
+        # repeat the images for cross fade
+        image_1 = None
+        image_2 = None
+        if image is not None:
+            if "shift" in method:
+                image_1 = image[:-1]
+                image_2 = image[1:]
+                
+                weights = weights * image_1.shape[0]
+                #weights_invert = [1.0 - w for w in weights]
 
-        return (weights, )
+                image_1 = image_1.repeat_interleave(frames, 0)
+                image_2 = image_2.repeat_interleave(frames, 0)
+            elif "alternate" in method:
+                image_1 = image[::2].repeat_interleave(2, 0)
+                image_1 = image_1[1:]
+                image_2 = image[1::2].repeat_interleave(2, 0)
+
+                mew_weights = weights + [1.0 - w for w in weights]
+                mew_weights = mew_weights * (image_1.shape[0] // 2)
+                if image.shape[0] % 2:
+                    image_1 = image_1[:-1]
+                else:
+                    image_2 = image_2[:-1]
+                    mew_weights = mew_weights + weights
+
+                weights = mew_weights
+                #weights_invert = [1.0 - w for w in weights]
+
+                image_1 = image_1.repeat_interleave(frames, 0)
+                image_2 = image_2.repeat_interleave(frames, 0)
+            else:
+                weights = weights * image.shape[0]
+                #weights_invert = [1.0 - w for w in weights]
+
+                image_1 = image.repeat_interleave(frames, 0)
+
+        # add starting and ending frames
+            if add_starting_frames > 0:
+                weights = [weights[0]] * add_starting_frames + weights
+                image_1 = torch.cat([image[:1].repeat(add_starting_frames, 1, 1, 1), image_1], dim=0)
+                if image_2 is not None:
+                    image_2 = torch.cat([image[:1].repeat(add_starting_frames, 1, 1, 1), image_2], dim=0)
+            if add_ending_frames > 0:
+                weights = weights + [weights[-1]] * add_ending_frames
+                image_1 = torch.cat([image_1, image[-1:].repeat(add_ending_frames, 1, 1, 1)], dim=0)
+                if image_2 is not None:
+                    image_2 = torch.cat([image_2, image[-1:].repeat(add_ending_frames, 1, 1, 1)], dim=0)
+
+        weights_invert = [1.0 - w for w in weights]
+
+        return (weights, weights_invert, len(weights), image_1, image_2, )
+
+class IPAdapterCombineWeights:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+        "required": {
+            "weights_1": ("FLOAT", { "default": 0.0, "min": 0.0, "max": 1.0, "step": 0.05 }),
+            "weights_2": ("FLOAT", { "default": 0.0, "min": 0.0, "max": 1.0, "step": 0.05 }),
+        }}
+    RETURN_TYPES = ("FLOAT", "INT")
+    RETURN_NAMES = ("weights", "count")
+    FUNCTION = "combine"
+    CATEGORY = "ipadapter/utils"
+
+    def combine(self, weights_1, weights_2):
+        if not isinstance(weights_1, list):
+            weights_1 = [weights_1]
+        if not isinstance(weights_2, list):
+            weights_2 = [weights_2]
+        weights = weights_1 + weights_2
+
+        return (weights, len(weights), )
 
 class IPAdapterRegionalConditioning:
     @classmethod
@@ -1521,6 +1601,7 @@ NODE_CLASS_MAPPINGS = {
     "IPAdapterSaveEmbeds": IPAdapterSaveEmbeds,
     "IPAdapterLoadEmbeds": IPAdapterLoadEmbeds,
     "IPAdapterWeights": IPAdapterWeights,
+    "IPAdapterCombineWeights": IPAdapterCombineWeights,
     "IPAdapterRegionalConditioning": IPAdapterRegionalConditioning,
     "IPAdapterCombineParams": IPAdapterCombineParams,
 }
@@ -1555,6 +1636,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "IPAdapterSaveEmbeds": "IPAdapter Save Embeds",
     "IPAdapterLoadEmbeds": "IPAdapter Load Embeds",
     "IPAdapterWeights": "IPAdapter Weights",
+    "IPAdapterCombineWeights": "IPAdapter Combine Weights",
     "IPAdapterRegionalConditioning": "IPAdapter Regional Conditioning",
     "IPAdapterCombineParams": "IPAdapter Combine Params",
 }
\ No newline at end of file
diff --git a/README.md b/README.md
index 5a04b8c..fdb6dba 100644
--- a/README.md
+++ b/README.md
@@ -27,6 +27,8 @@ Please consider a [Github Sponsorship](https://github.com/sponsors/cubiq) or [Pa
 
 ## Important updates
 
+**2024/04/27**: Refactored the IPAdapterWeights mostly useful for AnimateDiff animations.
+
 **2024/04/21**: Added Regional Conditioning nodes to simplify attention masking and masked text conditioning.
 
 **2024/04/16**: Added support for the new SDXL portrait unnorm model (link below). It's very strong and tends to ignore the text conditioning. Lower the CFG to 3-4 or use a RescaleCFG node.
@@ -144,7 +146,7 @@ It's only thanks to generous sponsors that **the whole community** can enjoy ope
 
 ### :trophy: Gold sponsors
 
-[![Kaiber.ai](https://f.latent.vision/imgs/kaiber.png)](https://kaiber.ai/)
+[![Kaiber.ai](https://f.latent.vision/imgs/kaiber.png)](https://kaiber.ai/)&nbsp; &nbsp;[![Kaiber.ai](https://f.latent.vision/imgs/replicate.png)](https://replicate.com/)
 
 ### :tada: Silver sponsors
 
diff --git a/examples/ipadapter_weights.json b/examples/ipadapter_weights.json
index 8388cb3..7a715d7 100644
--- a/examples/ipadapter_weights.json
+++ b/examples/ipadapter_weights.json
@@ -1,6 +1,6 @@
 {
-  "last_node_id": 21,
-  "last_link_id": 37,
+  "last_node_id": 22,
+  "last_link_id": 40,
   "nodes": [
     {
       "id": 7,
@@ -14,7 +14,7 @@
         "1": 180.6060791015625
       },
       "flags": {},
-      "order": 8,
+      "order": 5,
       "mode": 0,
       "inputs": [
         {
@@ -80,49 +80,6 @@
         "Node name for S&R": "VAEDecode"
       }
     },
-    {
-      "id": 5,
-      "type": "EmptyLatentImage",
-      "pos": [
-        801,
-        1097
-      ],
-      "size": [
-        315,
-        106
-      ],
-      "flags": {},
-      "order": 5,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "batch_size",
-          "type": "INT",
-          "link": 35,
-          "widget": {
-            "name": "batch_size"
-          }
-        }
-      ],
-      "outputs": [
-        {
-          "name": "LATENT",
-          "type": "LATENT",
-          "links": [
-            2
-          ],
-          "slot_index": 0
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "EmptyLatentImage"
-      },
-      "widgets_values": [
-        512,
-        512,
-        6
-      ]
-    },
     {
       "id": 6,
       "type": "CLIPTextEncode",
@@ -135,7 +92,7 @@
         "1": 164.31304931640625
       },
       "flags": {},
-      "order": 7,
+      "order": 4,
       "mode": 0,
       "inputs": [
         {
@@ -220,170 +177,6 @@
         1
       ]
     },
-    {
-      "id": 12,
-      "type": "LoadImage",
-      "pos": [
-        311,
-        270
-      ],
-      "size": {
-        "0": 315,
-        "1": 314
-      },
-      "flags": {},
-      "order": 0,
-      "mode": 0,
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            25
-          ],
-          "shape": 3,
-          "slot_index": 0
-        },
-        {
-          "name": "MASK",
-          "type": "MASK",
-          "links": null,
-          "shape": 3
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "LoadImage"
-      },
-      "widgets_values": [
-        "warrior_woman.png",
-        "image"
-      ]
-    },
-    {
-      "id": 17,
-      "type": "PrepImageForClipVision",
-      "pos": [
-        797,
-        87
-      ],
-      "size": {
-        "0": 315,
-        "1": 106
-      },
-      "flags": {},
-      "order": 3,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "link": 25
-        }
-      ],
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            30
-          ],
-          "shape": 3,
-          "slot_index": 0
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "PrepImageForClipVision"
-      },
-      "widgets_values": [
-        "LANCZOS",
-        "top",
-        0.15
-      ]
-    },
-    {
-      "id": 20,
-      "type": "IPAdapterWeights",
-      "pos": [
-        757,
-        318
-      ],
-      "size": [
-        263.5047280787487,
-        183.75987616018006
-      ],
-      "flags": {},
-      "order": 4,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "frames",
-          "type": "INT",
-          "link": 34,
-          "widget": {
-            "name": "frames"
-          },
-          "slot_index": 0
-        }
-      ],
-      "outputs": [
-        {
-          "name": "FLOAT",
-          "type": "FLOAT",
-          "links": [
-            32
-          ],
-          "shape": 3,
-          "slot_index": 0
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "IPAdapterWeights"
-      },
-      "widgets_values": [
-        "1.0,0.0",
-        "linear",
-        6,
-        0,
-        9999
-      ]
-    },
-    {
-      "id": 21,
-      "type": "PrimitiveNode",
-      "pos": [
-        340,
-        1093
-      ],
-      "size": {
-        "0": 210,
-        "1": 82
-      },
-      "flags": {},
-      "order": 1,
-      "mode": 0,
-      "outputs": [
-        {
-          "name": "INT",
-          "type": "INT",
-          "links": [
-            34,
-            35
-          ],
-          "widget": {
-            "name": "frames"
-          },
-          "slot_index": 0
-        }
-      ],
-      "title": "frames",
-      "properties": {
-        "Run widget replace on values": false
-      },
-      "widgets_values": [
-        6,
-        "fixed"
-      ]
-    },
     {
       "id": 19,
       "type": "IPAdapterBatch",
@@ -391,10 +184,10 @@
         1173,
         251
       ],
-      "size": [
-        315,
-        254
-      ],
+      "size": {
+        "0": 315,
+        "1": 254
+      },
       "flags": {},
       "order": 9,
       "mode": 0,
@@ -432,7 +225,7 @@
         {
           "name": "weight",
           "type": "FLOAT",
-          "link": 32,
+          "link": 38,
           "widget": {
             "name": "weight"
           },
@@ -473,7 +266,7 @@
         "1": 78
       },
       "flags": {},
-      "order": 6,
+      "order": 3,
       "mode": 0,
       "inputs": [
         {
@@ -525,7 +318,7 @@
         "1": 98
       },
       "flags": {},
-      "order": 2,
+      "order": 0,
       "mode": 0,
       "outputs": [
         {
@@ -561,6 +354,47 @@
         "sd15/realisticVisionV51_v51VAE.safetensors"
       ]
     },
+    {
+      "id": 17,
+      "type": "PrepImageForClipVision",
+      "pos": [
+        788,
+        43
+      ],
+      "size": {
+        "0": 315,
+        "1": 106
+      },
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 25
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            30
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "PrepImageForClipVision"
+      },
+      "widgets_values": [
+        "LANCZOS",
+        "top",
+        0.15
+      ]
+    },
     {
       "id": 9,
       "type": "SaveImage",
@@ -568,10 +402,10 @@
         1770,
         710
       ],
-      "size": [
-        556.2374508110479,
-        892.1895739499892
-      ],
+      "size": {
+        "0": 556.2374267578125,
+        "1": 892.1895751953125
+      },
       "flags": {},
       "order": 12,
       "mode": 0,
@@ -586,6 +420,203 @@
       "widgets_values": [
         "IPAdapter"
       ]
+    },
+    {
+      "id": 12,
+      "type": "LoadImage",
+      "pos": [
+        311,
+        270
+      ],
+      "size": {
+        "0": 315,
+        "1": 314
+      },
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            25
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "warrior_woman.png",
+        "image"
+      ]
+    },
+    {
+      "id": 5,
+      "type": "EmptyLatentImage",
+      "pos": [
+        801,
+        1097
+      ],
+      "size": [
+        309.1109879864148,
+        82
+      ],
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "batch_size",
+          "type": "INT",
+          "link": 35,
+          "widget": {
+            "name": "batch_size"
+          }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": [
+            2
+          ],
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "EmptyLatentImage"
+      },
+      "widgets_values": [
+        512,
+        512,
+        6
+      ]
+    },
+    {
+      "id": 21,
+      "type": "PrimitiveNode",
+      "pos": [
+        340,
+        1093
+      ],
+      "size": {
+        "0": 210,
+        "1": 82
+      },
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "INT",
+          "type": "INT",
+          "links": [
+            35,
+            40
+          ],
+          "widget": {
+            "name": "batch_size"
+          },
+          "slot_index": 0
+        }
+      ],
+      "title": "frames",
+      "properties": {
+        "Run widget replace on values": false
+      },
+      "widgets_values": [
+        6,
+        "fixed"
+      ]
+    },
+    {
+      "id": 22,
+      "type": "IPAdapterWeights",
+      "pos": [
+        761,
+        208
+      ],
+      "size": [
+        299.9049990375719,
+        324.00000762939453
+      ],
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": null
+        },
+        {
+          "name": "frames",
+          "type": "INT",
+          "link": 40,
+          "widget": {
+            "name": "frames"
+          }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "weights",
+          "type": "FLOAT",
+          "links": [
+            38
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "weights_invert",
+          "type": "FLOAT",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "total_frames",
+          "type": "INT",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "image_1",
+          "type": "IMAGE",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "image_2",
+          "type": "IMAGE",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "IPAdapterWeights"
+      },
+      "widgets_values": [
+        "1.0, 0.0",
+        "linear",
+        6,
+        0,
+        9999,
+        0,
+        0,
+        "full batch"
+      ]
     }
   ],
   "links": [
@@ -685,22 +716,6 @@
       0,
       "MODEL"
     ],
-    [
-      32,
-      20,
-      0,
-      19,
-      6,
-      "FLOAT"
-    ],
-    [
-      34,
-      21,
-      0,
-      20,
-      0,
-      "INT"
-    ],
     [
       35,
       21,
@@ -724,6 +739,22 @@
       19,
       0,
       "MODEL"
+    ],
+    [
+      38,
+      22,
+      0,
+      19,
+      6,
+      "FLOAT"
+    ],
+    [
+      40,
+      21,
+      0,
+      22,
+      1,
+      "INT"
     ]
   ],
   "groups": [],