commit ImageBatchToList and ImageListToBatch nodes
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chflame163
@@ -147,6 +147,7 @@ When this error has occurred, please check the network environment.
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<font size="4">**If the dependency package error after updating, please double clicking ```repair_dependency.bat``` (for Official ComfyUI Protable) or ```repair_dependency_aki.bat``` (for ComfyUI-aki-v1.x) in the plugin folder to reinstall the dependency packages. </font><br />
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* Commit [ImageBatchToList](#ImageBatchToList) and [ImageListToBatch](#ImageListToBatch) nodes, Used for converting single batches of images into multiple small batches and vice versa, with option to define the maximum number of images in each small batch.
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* Commit [DistortDisplace](#DistortDisplace) node, Generate displacement deformation effects for material images.
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* Commit [MaskEdgeUltraDetailV3](#MaskEdgeUltraDetailV3) node, By processing different partitions through inputting a trimap mask, a more refined overall mask including translucent parts is generated.
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* Commit [ImageCompositeHandleMask](#ImageCompositeHandleMask) node, used to generate local feathering masks and cropping data.
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@@ -1835,6 +1836,21 @@ Outputs:
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* file_name: Output a list of file names corresponding to the images.
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* frame_count: Output the total number of images.
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### <a id="table1">ImageBatchToList</a>
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Convert a batch of images into multiple smaller batches, with option to define the maximum number of images in each small batch.
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Node Options:
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_node.jpg)
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* batch_size: The maximum number of images in each small batch.
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### <a id="table1">ImageListToBatch</a>
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Merge multiple small batches of images into one large batch.
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_node.jpg)
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# <a id="table1">LayerMask</a>
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@@ -128,6 +128,7 @@ os.environ['HF_ENDPOINT'] = 'https://hf-mirror.com'
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## 更新说明
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<font size="4">**如果本插件更新后出现依赖包错误，请双击运行插件目录下的```install_requirements.bat```(官方便携包)，或 ```install_requirements_aki.bat```(秋叶整合包) 重新安装依赖包。
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* 添加 [ImageBatchToList](#ImageBatchToList) 和 [ImageListToBatch](#ImageListToBatch) 节点， 用于图片单个大批次和多个小批次互相转换，支持定义小批次数量。
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* 添加 [DistortDisplace](#DistortDisplace) 节点， 为材质图片生成置换变形效果。
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* 添加 [MaskEdgeUltraDetailV3](#MaskEdgeUltraDetailV3) 节点， 通过输入trimap遮罩对不同分区处理，生成包括更加精细半透明部分的整体遮罩。
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* 添加 [ImageCompositeHandleMask](#ImageCompositeHandleMask) 节点， 用于生成局部羽化遮罩以及对应的裁切数据。
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@@ -1646,6 +1647,18 @@ BooleanOperator的升级版，增加了节点内数值输入，增加了大于
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* file_name: 输出图片对应的文件名列表。
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* frame_count: 输出图片总数。
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### <a id="table1">ImageBatchToList</a>
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将一个图片大批次转换为若干小批次，可定义每个小批次的图片数量上限。
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节点选项说明:
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_node.jpg)
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* batch_size: 每个小批次的图片数量上限。
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### <a id="table1">ImageListToBatch</a>
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将多个图片小批次合并为一个大批次。
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_node.jpg)
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# <a id="table1">LayerMask</a>
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+97
-2
@@ -1,3 +1,4 @@
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import torch
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from .imagefunc import AnyType, log, extract_all_numbers_from_str
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@@ -461,6 +462,95 @@ class QueueStopNode():
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return (any,)
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class LS_ImageBatchToMultiList:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"image": ("IMAGE",),
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"batch_size": ("INT", {
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"default": 6,
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"min": 1,
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"max": 64,
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"step": 1
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}),
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}
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}
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("image", )
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OUTPUT_IS_LIST = (True,)
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FUNCTION = "image_batch_to_multi_list"
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CATEGORY = '😺dzNodes/LayerUtility/Data'
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def image_batch_to_multi_list(self, image, batch_size):
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"""
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image: [B, H, W, C]
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输出: list of IMAGE batch，每个 batch 大小 <= batch_size
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"""
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B = image.shape[0]
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out = []
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for i in range(0, B, batch_size):
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batch = image[i:i + batch_size]
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out.append(batch)
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return (out,)
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class LS_MultiImageListToBatch:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"image": ("IMAGE",),
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}
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}
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("image", )
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INPUT_IS_LIST = True
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FUNCTION = "multi_image_list_to_batch"
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CATEGORY = '😺dzNodes/LayerUtility/Data'
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def multi_image_list_to_batch(self, image):
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"""
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image: list of IMAGE batch
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每个元素 shape 为 [Bi, Hi, Wi, C]
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输出: 单一 IMAGE batch [sum(Bi), H, W, C]
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"""
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# 以第一个 batch 的第一张图作为基准尺寸
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base_h, base_w = image[0].shape[1:3]
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out = []
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for batch in image:
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# batch: [B, H, W, C]
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if batch.shape[1:3] != (base_h, base_w):
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# 转成 [B, C, H, W]
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batch = batch.permute(0, 3, 1, 2)
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batch = comfy.utils.common_upscale(
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batch,
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base_w,
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base_h,
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upscale_method="bicubic",
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crop="center"
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)
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# 转回 [B, H, W, C]
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batch = batch.permute(0, 2, 3, 1)
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out.append(batch)
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# 沿 batch 维拼接
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out = torch.cat(out, dim=0)
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return (out,)
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NODE_CLASS_MAPPINGS = {
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"LayerUtility: QueueStop": QueueStopNode,
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"LayerUtility: SwitchCase": SwitchCaseNode,
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@@ -475,7 +565,10 @@ NODE_CLASS_MAPPINGS = {
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"LayerUtility: Integer": IntegerNode,
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"LayerUtility: Float": FloatNode,
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"LayerUtility: Boolean": BooleanNode,
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"LayerUtility: Seed": SeedNode
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"LayerUtility: Seed": SeedNode,
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"LayerUtility: ImageBatchToList": LS_ImageBatchToMultiList,
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"LayerUtility: ImageListToBatch": LS_MultiImageListToBatch,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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@@ -492,5 +585,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"LayerUtility: Integer": "LayerUtility: Integer",
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"LayerUtility: Float": "LayerUtility: Float",
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"LayerUtility: Boolean": "LayerUtility: Boolean",
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"LayerUtility: Seed": "LayerUtility: Seed"
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"LayerUtility: Seed": "LayerUtility: Seed",
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"LayerUtility: ImageBatchToList": "LayerUtility: Image Batch To List(Multi)",
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"LayerUtility: ImageListToBatch": "LayerUtility: Image List To Batch(Multi)",
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}
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+1
-1
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[project]
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name = "comfyui_layerstyle"
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description = "A set of nodes for ComfyUI it generate image like Adobe Photoshop's Layer Style. the Drop Shadow is first completed node, and follow-up work is in progress."
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version = "2.0.35"
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version = "2.0.36"
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license = {text = "MIT License"}
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dependencies = ["numpy", "pillow", "torch", "matplotlib", "Scipy", "scikit_image", "scikit_learn", "opencv-contrib-python", "pymatting", "timm", "colour-science", "transformers", "blend_modes", "huggingface_hub", "loguru"]
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