feat: Add LoadImageWithName node to output filename without extension
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@@ -19,6 +19,7 @@ Rui-Node🐶 是一个功能丰富的 ComfyUI 节点集合,提供图像处理
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### 📁 文件存储与加载类
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- [按路径加载图像 / Load Image By Path](#3-按路径加载图像--load-image-by-path)
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- [加载图像(带文件名) / Load Image With Name](#16-加载图像带文件名--load-image-with-name)
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### 🤖 AI模型类
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- [千问编辑图像生成 / Qwen Edit Image Generation](#4-千问编辑图像生成--qwen-edit-image-generation)
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@@ -494,6 +495,28 @@ Rui-Node🐶 是一个功能丰富的 ComfyUI 节点集合,提供图像处理
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---
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### 16. 加载图像(带文件名) / Load Image With Name
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**分类**: `Rui-Node🐶/文件存储与加载📁`
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**功能描述**:
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基础功能与 ComfyUI 原生的 "Load Image" 节点完全一致,支持从 ComfyUI 的 `input` 目录中选择图像,并支持拖拽上传。区别在于本节点额外提供了一个字符串输出端口,用于输出图像的文件名。
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**输入参数**:
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- `image` (下拉选择): 从 `input` 目录中选择图像文件,或通过按钮上传
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**输出**:
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- `IMAGE`: 图像数据
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- `MASK`: 图像的 Alpha 通道遮罩
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- `filename` (STRING): 图像的文件名(不包含后缀,例如上传了 `test_image.png`,则输出 `test_image`)
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**使用场景**:
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- 批量处理图像时,希望以原文件名保存处理后的结果
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- 需要将当前图像的文件名作为提示词或其他参数传递给下游节点
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- 建立更规范的自动化工作流
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---
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## 🔧 依赖库
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主要依赖库包括:
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@@ -5,6 +5,8 @@ from .flip_node import NODE_CLASS_MAPPINGS as FLIP_NODE_CLASS_MAPPINGS
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from .flip_node import NODE_DISPLAY_NAME_MAPPINGS as FLIP_NODE_DISPLAY_NAME_MAPPINGS
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from .load_image_node import NODE_CLASS_MAPPINGS as LOAD_NODE_CLASS_MAPPINGS
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from .load_image_node import NODE_DISPLAY_NAME_MAPPINGS as LOAD_NODE_DISPLAY_NAME_MAPPINGS
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from .load_image_with_name_node import NODE_CLASS_MAPPINGS as LOAD_NAME_NODE_CLASS_MAPPINGS
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from .load_image_with_name_node import NODE_DISPLAY_NAME_MAPPINGS as LOAD_NAME_NODE_DISPLAY_NAME_MAPPINGS
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from .qwenedit_node import NODE_CLASS_MAPPINGS as QWEN_NODE_CLASS_MAPPINGS
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from .qwenedit_node import NODE_DISPLAY_NAME_MAPPINGS as QWEN_NODE_DISPLAY_NAME_MAPPINGS
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from .shot_splitter_node import NODE_CLASS_MAPPINGS as SHOT_NODE_CLASS_MAPPINGS
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@@ -36,6 +38,7 @@ NODE_CLASS_MAPPINGS = {}
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NODE_CLASS_MAPPINGS.update(SAT_NODE_CLASS_MAPPINGS)
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NODE_CLASS_MAPPINGS.update(FLIP_NODE_CLASS_MAPPINGS)
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NODE_CLASS_MAPPINGS.update(LOAD_NODE_CLASS_MAPPINGS)
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NODE_CLASS_MAPPINGS.update(LOAD_NAME_NODE_CLASS_MAPPINGS)
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NODE_CLASS_MAPPINGS.update(QWEN_NODE_CLASS_MAPPINGS)
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NODE_CLASS_MAPPINGS.update(SHOT_NODE_CLASS_MAPPINGS)
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NODE_CLASS_MAPPINGS.update(DIALOGUE_NODE_CLASS_MAPPINGS)
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@@ -54,6 +57,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {}
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NODE_DISPLAY_NAME_MAPPINGS.update(SAT_NODE_DISPLAY_NAME_MAPPINGS)
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NODE_DISPLAY_NAME_MAPPINGS.update(FLIP_NODE_DISPLAY_NAME_MAPPINGS)
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NODE_DISPLAY_NAME_MAPPINGS.update(LOAD_NODE_DISPLAY_NAME_MAPPINGS)
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NODE_DISPLAY_NAME_MAPPINGS.update(LOAD_NAME_NODE_DISPLAY_NAME_MAPPINGS)
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NODE_DISPLAY_NAME_MAPPINGS.update(QWEN_NODE_DISPLAY_NAME_MAPPINGS)
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NODE_DISPLAY_NAME_MAPPINGS.update(SHOT_NODE_DISPLAY_NAME_MAPPINGS)
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NODE_DISPLAY_NAME_MAPPINGS.update(DIALOGUE_NODE_DISPLAY_NAME_MAPPINGS)
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@@ -0,0 +1,84 @@
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import os
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import torch
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import numpy as np
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import hashlib
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from PIL import Image, ImageOps, ImageSequence
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import folder_paths
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class LoadImageWithNameNode:
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"""
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基础功能与 ComfyUI 的通用图像加载节点相同,但额外输出图像的文件名(不带后缀)。
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"""
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@classmethod
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def INPUT_TYPES(s):
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input_dir = folder_paths.get_input_directory()
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files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f))]
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return {"required":
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{"image": (sorted(files), {"image_upload": True})},
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}
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CATEGORY = "Rui-Node🐶/文件存储与加载📁"
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RETURN_TYPES = ("IMAGE", "MASK", "STRING")
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RETURN_NAMES = ("IMAGE", "MASK", "filename")
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FUNCTION = "load_image"
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def load_image(self, image):
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image_path = folder_paths.get_annotated_filepath(image)
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img = Image.open(image_path)
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# 提取不带后缀的文件名
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filename = os.path.splitext(os.path.basename(image_path))[0]
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output_images = []
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output_masks = []
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for i in ImageSequence.Iterator(img):
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i = ImageOps.exif_transpose(i)
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if i.mode == 'I':
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i = i.point(lambda i: i * (1 / 255))
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image_rgba = i.convert("RGBA")
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image_rgb = image_rgba.convert("RGB")
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image_np = np.array(image_rgb).astype(np.float32) / 255.0
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output_images.append(image_np)
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if 'A' in i.getbands():
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mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
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mask = 1. - mask
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else:
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mask = np.zeros((image_np.shape[0], image_np.shape[1]), dtype=np.float32)
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output_masks.append(mask)
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if len(output_images) > 1:
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output_image = torch.from_numpy(np.stack(output_images))
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output_mask = torch.from_numpy(np.stack(output_masks))
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else:
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output_image = torch.from_numpy(output_images[0])[None,]
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output_mask = torch.from_numpy(output_masks[0])[None,]
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return (output_image, output_mask, filename)
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@classmethod
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def IS_CHANGED(s, image):
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image_path = folder_paths.get_annotated_filepath(image)
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m = hashlib.sha256()
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with open(image_path, 'rb') as f:
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m.update(f.read())
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return m.digest().hex()
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@classmethod
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def VALIDATE_INPUTS(s, image):
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if not folder_paths.exists_annotated_filepath(image):
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return "Invalid image file: {}".format(image)
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return True
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NODE_CLASS_MAPPINGS = {
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"LoadImageWithName": LoadImageWithNameNode
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"LoadImageWithName": "加载图像(带文件名) / Load Image With Name"
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}
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