diff --git a/None b/None
new file mode 100644
index 0000000..b06ffb5
--- /dev/null
+++ b/None
@@ -0,0 +1 @@
+{"height": 1600, "width": 512, "keypoints": [[246.62915205022568, 269.60325614215964], [253.44882580389572, 441.06933909157897], [130.87622018158436, 441.06933909157897], [85.6552588840326, 660.0339937955141], [73.75500591099262, 855.1981425533693], [376.0214314262071, 441.06933909157897], [418.8623421291509, 669.5541961739459], [430.76259510219097, 857.5781931479771], [176.0971814791361, 814.7372824450335], [187.9974344521761, 1152.7044668793678], [195.13758623600006, 1459.7309935837984], [333.1805207232634, 812.3572318504253], [321.2802677502235, 1152.7044668793678], [316.5201665610075, 1464.491094773014], [220.44859550953777, 248.18280079068774], [272.8097085909135, 250.5628513852958], [191.8879883742419, 279.12345852059167], [308.51046751003344, 279.12345852059167], [190.37748504678405, 222.10468438764406], [190.37748504678405, 236.384987955292], [192.7575356413921, 253.045342117548], [197.517636830608, 267.3256456851959], [199.89768742521608, 279.2258986582358], 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\ No newline at end of file
diff --git a/__init__.py b/__init__.py
index fd7299f..c5ecf32 100644
--- a/__init__.py
+++ b/__init__.py
@@ -2377,7 +2377,41 @@ class HistogramEqualization:
 
         return (blended_image_tensor,)
 
+class TRI3DCompositeImageSplitter:
+    """
+    This node splits composite (horizontally concatenated) image into half.
+    """
+    def __init__(self):
+        pass
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        """
+        Input Types
+        """
+        return {
+            "required": {
+                "image": ("IMAGE",)
+            },
+        }
 
+    RETURN_TYPES = ("IMAGE","IMAGE")
+    RETURN_NAMES = ("image1","image2")
+    FUNCTION = "main"
+
+    CATEGORY = "TRI3D"
+
+    def main(self, image):
+        image = from_torch_image(image)
+        h,w,_ = image.shape
+        image1 = image[:,:w//2,:]
+        image2 = image[:,w//2:,:]
+
+        image1 = torch.from_numpy(image1.astype(np.float32)/255.0)[None,]
+        image2 = torch.from_numpy(image2.astype(np.float32)/255.0)[None,]
+
+        return (image1, image2)
+    
 # A dictionary that contains all nodes you want to export with their names
 # NOTE: names should be globally unique
 NODE_CLASS_MAPPINGS = {
@@ -2403,6 +2437,7 @@ NODE_CLASS_MAPPINGS = {
     "tri3d-clipdrop-bgremove-api": TRI3D_clipdrop_bgremove_api,
     "tri3d-adjust-neck": TRI3DAdjustNeck,
     "tri3d-HistogramEqualization": HistogramEqualization,
+    "tri3d-composite-image-splitter": TRI3DCompositeImageSplitter
 }
 
 VERSION = "2.7.0"
@@ -2432,4 +2467,5 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "tri3d-clipdrop-bgremove-api": "RemBG ClipDrop" + " v" + VERSION,
     "tri3d-adjust-neck": "Adjust Neck" + " v" + VERSION,
     "tri3d-HistogramEqualization": "Adjust Neck" + " v" + VERSION,
+    "tri3d-composite-image-splitter": "Composite Image Splitter" + " v" + VERSION
 }