t8mars--comfyui-megastyle-t8
wehub-resource-sync
154 行
4.5 KiB
Python
154 行
4.5 KiB
Python
"""MetaStyle T8 节点核心逻辑
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输入:
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- style_key (string): 选中的风格 key，前端 widget 写入
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- output_size (combo): 输出尺寸 original / 512 / 1024
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- seed (int): 预留
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输出:
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- IMAGE 风格代表图 (BHWC float32 0~1)
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- style_name 风格全名
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- category 大类（中文）
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- sample_prompt 示例提示词（可直接接 CLIPTextEncode）
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- sample_id 数据集原始 id
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- meta_json 全量元数据 JSON 字符串
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"""
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import json
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import os
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from pathlib import Path
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import numpy as np
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import torch
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from PIL import Image
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ROOT = Path(__file__).resolve().parent
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DATA = ROOT / "data"
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_meta_cache = None
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_catalog_cache = None
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_lite_cache = None
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def load_meta() -> dict:
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global _meta_cache
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if _meta_cache is None:
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p = DATA / "styles_meta.json"
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_meta_cache = json.loads(p.read_text(encoding="utf-8")) if p.exists() else {}
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return _meta_cache
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def load_catalog() -> dict:
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global _catalog_cache
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if _catalog_cache is None:
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p = DATA / "catalog.json"
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_catalog_cache = json.loads(p.read_text(encoding="utf-8")) if p.exists() else {}
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return _catalog_cache
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def load_lite() -> list:
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global _lite_cache
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if _lite_cache is None:
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p = DATA / "styles_lite.json"
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_lite_cache = json.loads(p.read_text(encoding="utf-8")) if p.exists() else []
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return _lite_cache
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def pil_to_tensor(im: Image.Image) -> torch.Tensor:
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"""PIL -> ComfyUI 标准 IMAGE tensor: shape (1, H, W, 3), float32 0~1"""
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if im.mode != "RGB":
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im = im.convert("RGB")
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arr = np.asarray(im).astype(np.float32) / 255.0
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return torch.from_numpy(arr)[None, ...]
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def empty_image(w: int = 512, h: int = 512) -> torch.Tensor:
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return torch.zeros((1, h, w, 3), dtype=torch.float32)
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class MetaStyleT8Picker:
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"""T8 风格选择器：按风格挑选代表图与示例提示词。"""
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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# 由前端 widget 维护的字符串：选中的 style key
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"style_key": ("STRING", {
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"default": "",
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"multiline": False,
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"metastyle_picker": True, # 给前端 JS 识别用
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}),
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"output_size": (["original", "512", "768", "1024"],
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{"default": "original"}),
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},
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"optional": {
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"seed": ("INT", {
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"default": 0, "min": 0, "max": 0xFFFFFFFF
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}),
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},
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}
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RETURN_TYPES = (
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"IMAGE", "STRING", "STRING", "STRING", "STRING", "STRING",
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)
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RETURN_NAMES = (
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"image", "style_name", "category",
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"sample_prompt", "sample_id", "meta_json",
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)
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FUNCTION = "pick"
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CATEGORY = "T8/Style"
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def pick(self, style_key: str, output_size: str, seed: int = 0):
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meta = load_meta()
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style_key = (style_key or "").strip()
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info = meta.get(style_key)
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if not info:
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# 未选中或 key 无效 → 返回空图，提示文字
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return (
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empty_image(),
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style_key,
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"",
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"",
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"",
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json.dumps({"error": "style_key not found", "key": style_key},
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ensure_ascii=False),
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)
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img_path = ROOT / "data" / info["image"]
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try:
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with Image.open(img_path) as im:
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im.load()
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if output_size != "original":
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target = int(output_size)
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im = im.copy()
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im.thumbnail((target, target), Image.LANCZOS)
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tensor = pil_to_tensor(im)
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except Exception as e:
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return (
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empty_image(),
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style_key,
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info.get("category", ""),
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info.get("sample_content", ""),
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info.get("sample_id", ""),
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json.dumps({"error": str(e), "key": style_key},
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ensure_ascii=False),
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)
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return (
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tensor,
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info.get("style_full", style_key),
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info.get("category", ""),
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info.get("sample_content", ""),
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info.get("sample_id", ""),
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json.dumps(info, ensure_ascii=False),
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)
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NODE_CLASS_MAPPINGS = {
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"MetaStyleT8Picker": MetaStyleT8Picker,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"MetaStyleT8Picker": "MetaStyle T8 风格选择器",
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}
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