Update appendage_editor_nodes.py

remove pose render node cause there is already having a separate one

appendage_editor_nodes.py

@@ -323,87 +323,3 @@ class AppendageEditorNode:
                 new_keypoints.extend([x, y, conf])
         
         return new_keypoints
-
-
-class PoseRendererNode:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {
-            "required": {
-                "POSE_KEYPOINT": ("POSE_KEYPOINT",),
-            },
-            "optional": {
-                "show_body": ("BOOLEAN", {"default": True}),
-                "show_face": ("BOOLEAN", {"default": True}),
-                "show_hands": ("BOOLEAN", {"default": True}),
-                "resolution_x": ("INT", {
-                    "default": -1,
-                    "min": -1,
-                    "max": 12800
-                }),
-                "pose_marker_size": ("INT", {
-                    "default": 4,
-                    "min": 0,
-                    "max": 100
-                }),
-                "face_marker_size": ("INT", {
-                    "default": 3,
-                    "min": 0,
-                    "max": 100
-                }),
-                "hand_marker_size": ("INT", {
-                    "default": 2,
-                    "min": 0,
-                    "max": 100
-                }),
-            },
-        }
-
-    RETURN_NAMES = ("IMAGE",)
-    RETURN_TYPES = ("IMAGE",)
-    FUNCTION = "render_pose"
-    CATEGORY = "ultimate-openpose"
-
-    def render_pose(self, POSE_KEYPOINT, show_body=True, show_face=True, show_hands=True, resolution_x=-1, pose_marker_size=4, face_marker_size=3, hand_marker_size=2):
-        if POSE_KEYPOINT is None:
-            # Create default blank image
-            W, H = 512, 768
-            W_scaled = resolution_x if resolution_x >= 64 else W
-            H_scaled = int(H * (W_scaled * 1.0 / W))
-            blank_img = np.zeros((H_scaled, W_scaled, 3), dtype=np.uint8)
-            pose_img_np = np.array([blank_img]).astype(np.float32) / 255
-            return (torch.from_numpy(pose_img_np),)
-        
-        # Convert pose keypoints to JSON string for rendering
-        if isinstance(POSE_KEYPOINT, list):
-            pose_json = json.dumps(POSE_KEYPOINT)
-        else:
-            pose_json = json.dumps([POSE_KEYPOINT])
-        
-        # Use existing draw_pose_json function to render
-        pose_imgs = draw_pose_json(
-            pose_json, 
-            resolution_x, 
-            show_body, 
-            show_face, 
-            show_hands, 
-            pose_marker_size, 
-            face_marker_size, 
-            hand_marker_size, 
-            1.0,  # hands_scale
-            1.0,  # body_scale  
-            1.0,  # head_scale
-            1.0   # overall_scale
-        )
-        
-        if pose_imgs:
-            pose_imgs_np = np.array(pose_imgs).astype(np.float32) / 255
-            return (torch.from_numpy(pose_imgs_np),)
-        
-        # Create default blank image if rendering fails
-        W, H = 512, 768
-        W_scaled = resolution_x if resolution_x >= 64 else W
-        H_scaled = int(H * (W_scaled * 1.0 / W))
-        blank_img = np.zeros((H_scaled, W_scaled, 3), dtype=np.uint8)
-        pose_img_np = np.array([blank_img]).astype(np.float32) / 255
-        return (torch.from_numpy(pose_img_np),)