Add MaskBatchMulti -node

nodes.py

@@ -1080,7 +1080,7 @@ class ImageBatchMulti:
     RETURN_TYPES = ("IMAGE",)
     RETURN_NAMES = ("images",)
     FUNCTION = "combine"
-    CATEGORY = "KJNodes/masking/conditioning"
+    CATEGORY = "KJNodes/image"
     DESCRIPTION = """
 Creates an image batch from multiple images.  
 You can set how many inputs the node has,  
@@ -1094,7 +1094,37 @@ with the **inputcount** and clicking update.
         for c in range(1, inputcount):
             new_image = kwargs[f"image_{c + 1}"]
             image, = image_batch_node.batch(new_image, image)
-        return (image, inputcount,)
+        return (image,)
+
+class MaskBatchMulti:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "inputcount": ("INT", {"default": 2, "min": 2, "max": 1000, "step": 1}),
+                "mask_1": ("MASK", ),
+                "mask_2": ("MASK", ),
+            },
+    }
+
+    RETURN_TYPES = ("MASK",)
+    RETURN_NAMES = ("masks",)
+    FUNCTION = "combine"
+    CATEGORY = "KJNodes/masking"
+    DESCRIPTION = """
+Creates an image batch from multiple masks.  
+You can set how many inputs the node has,  
+with the **inputcount** and clicking update.
+"""
+
+    def combine(self, inputcount, **kwargs):
+        mask = kwargs["mask_1"]
+        for c in range(1, inputcount):
+            new_mask = kwargs[f"mask_{c + 1}"]
+            if mask.shape[1:] != new_mask.shape[1:]:
+                new_mask = F.interpolate(new_mask.unsqueeze(1), size=(mask.shape[1], mask.shape[2]), mode="bicubic").squeeze(1)
+            mask = torch.cat((mask, new_mask), dim=0)
+        return (mask,)
 
 class CondPassThrough:
     @classmethod
@@ -5145,6 +5175,7 @@ NODE_CLASS_MAPPINGS = {
     "INTConstant": INTConstant,
     "FloatConstant": FloatConstant,
     "ImageBatchMulti": ImageBatchMulti,
+    "MaskBatchMulti": MaskBatchMulti,
     "ConditioningMultiCombine": ConditioningMultiCombine,
     "ConditioningSetMaskAndCombine": ConditioningSetMaskAndCombine,
     "ConditioningSetMaskAndCombine3": ConditioningSetMaskAndCombine3,
@@ -5233,6 +5264,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "INTConstant": "INT Constant",
     "FloatConstant": "Float Constant",
     "ImageBatchMulti": "Image Batch Multi",
+    "MaskBatchMulti": "Mask Batch Multi",
     "ConditioningMultiCombine": "Conditioning Multi Combine",
     "ConditioningSetMaskAndCombine": "ConditioningSetMaskAndCombine",
     "ConditioningSetMaskAndCombine3": "ConditioningSetMaskAndCombine3",

web/js/jsnodes.js

@@ -48,6 +48,28 @@ app.registerExtension({
 					});
 					}
 					break;
+					case "MaskBatchMulti":
+					nodeType.prototype.onNodeCreated = function () {
+					this._type = "MASK"
+					this.inputs_offset = nodeData.name.includes("selective")?1:0
+					this.addWidget("button", "Update inputs", null, () => {
+						if (!this.inputs) {
+							this.inputs = [];
+						}
+						const target_number_of_inputs = this.widgets.find(w => w.name === "inputcount")["value"];
+							if(target_number_of_inputs===this.inputs.length)return; // already set, do nothing
+	
+							if(target_number_of_inputs < this.inputs.length){
+								for(let i = this.inputs.length; i>=this.inputs_offset+target_number_of_inputs; i--)
+									  this.removeInput(i)
+							}
+							else{
+								for(let i = this.inputs.length+1-this.inputs_offset; i <= target_number_of_inputs; ++i)
+									this.addInput(`mask_${i}`, this._type)
+							}
+					});
+					}
+					break;
 			case "SoundReactive":
 				nodeType.prototype.onNodeCreated = function () {
 					let audioContext;