Add Output To Text Converter utility node for flexible data conversion

modules/utils/output_converter.py

@@ -0,0 +1,117 @@
+# -*- coding: utf-8 -*-
+# Filename: output_converter.py
+# Developer: jammyfu
+# Category: 🎨Painting👓Coder/🛠️Utils
+
+import json
+import torch
+import numpy as np
+from PIL import Image
+
+class AnyType(str):
+    """自定义任意类型"""
+    def __ne__(self, __value: object) -> bool:
+        return False
+
+any_type = AnyType("*")
+
+class OutputToTextConverter:
+    """通用输出转文本转换器"""
+    
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "any_input": (any_type,),  # 使用自定义的any_type
+                "format": (["Auto", "JSON", "Plain Text", "Raw"],),
+                "indent": ("INT", {"default": 2, "min": 0, "max": 8, "step": 1}),
+            },
+        }
+
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("text",)
+    FUNCTION = "convert"
+    CATEGORY = "🎨Painting👓Coder/🛠️Utils"
+
+    def convert(self, any_input, format="Auto", indent=2):
+        """将任何输入转换为文本"""
+        try:
+            # 如果输入为None
+            if any_input is None:
+                return ("None",)
+
+            # 如果输入已经是字符串
+            if isinstance(any_input, str):
+                return (any_input,)
+
+            # 根据不同类型进行转换
+            if format == "Auto":
+                text = self._auto_convert(any_input, indent)
+            elif format == "JSON":
+                text = self._to_json(any_input, indent)
+            elif format == "Plain Text":
+                text = str(any_input)
+            else:  # Raw
+                text = repr(any_input)
+
+            print(f"[OutputConverter] Converted {type(any_input).__name__} to text")
+            return (text,)
+
+        except Exception as e:
+            print(f"[OutputConverter] Error converting output: {str(e)}")
+            return (f"Error: {str(e)}",)
+
+    def _auto_convert(self, obj, indent):
+        """自动选择最合适的转换方式"""
+        # 处理常见的数据类型
+        if isinstance(obj, (dict, list, tuple, set)):
+            return self._to_json(obj, indent)
+        elif isinstance(obj, (int, float, bool)):
+            return str(obj)
+        elif isinstance(obj, (torch.Tensor, np.ndarray)):
+            return self._tensor_to_text(obj)
+        elif isinstance(obj, Image.Image):
+            return self._image_to_text(obj)
+        else:
+            # 尝试JSON序列化，如果失败则使用str
+            try:
+                return self._to_json(obj, indent)
+            except:
+                return str(obj)
+
+    def _to_json(self, obj, indent):
+        """转换为JSON格式"""
+        def default_converter(o):
+            if isinstance(o, (torch.Tensor, np.ndarray)):
+                return self._tensor_to_text(o)
+            elif isinstance(o, Image.Image):
+                return self._image_to_text(o)
+            elif hasattr(o, '__dict__'):
+                return o.__dict__
+            return str(o)
+
+        return json.dumps(obj, indent=indent, default=default_converter)
+
+    def _tensor_to_text(self, tensor):
+        """转换张量为文本描述"""
+        if isinstance(tensor, np.ndarray):
+            shape = tensor.shape
+            dtype = str(tensor.dtype)
+        else:  # torch.Tensor
+            shape = tuple(tensor.size())
+            dtype = str(tensor.dtype)
+
+        return f"Tensor(shape={shape}, dtype={dtype})"
+
+    def _image_to_text(self, image):
+        """转换图像为文本描述"""
+        return f"Image(size={image.size}, mode={image.mode})"
+
+# 注册节点
+NODE_CLASS_MAPPINGS = {
+    "PaintingCoder::OutputToTextConverter": OutputToTextConverter,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "PaintingCoder::OutputToTextConverter": "Output To Text 📝",
+}