diff --git a/zh-CN/Menus/ComfyUI-BiRefNet-Hugo.json b/zh-CN/Menus/ComfyUI-BiRefNet-Hugo.json new file mode 100644 index 0000000..f6b4680 --- /dev/null +++ b/zh-CN/Menus/ComfyUI-BiRefNet-Hugo.json @@ -0,0 +1,28 @@ +{ + "transparency": "透明", + "green": "绿", + "white": "白", + "red": "红", + "yellow": "黄", + "blue": "蓝", + "black": "黑", + "pink": "粉红", + "purple": "紫", + "brown": "棕", + "violet": "蓝紫", + "wheat": "小麦", + "whitesmoke": "烟白", + "yellowgreen": "黄绿", + "turquoise": "宝石绿", + "tomato": "番茄红", + "thistle": "苍紫", + "teal": "蓝绿", + "tan": "棕褐", + "steelblue": "钢蓝", + "springgreen": "春绿", + "snow": "雪白", + "slategrey": "灰石", + "slateblue": "灰蓝", + "skyblue": "天蓝", + "orange": "橙色" +} \ No newline at end of file diff --git a/zh-CN/Nodes/ComfyUI-AutomaticCFG.json b/zh-CN/Nodes/ComfyUI-AutomaticCFG.json index 12ea8be..424b194 100644 --- a/zh-CN/Nodes/ComfyUI-AutomaticCFG.json +++ b/zh-CN/Nodes/ComfyUI-AutomaticCFG.json @@ -39,6 +39,15 @@ "MODEL": "模型" } }, + "Automatic CFG - Warp Drive": { + "title": "自动CFG(Warp Drive)", + "inputs": { + "model": "模型" + }, + "outputs": { + "MODEL": "模型" + } + }, "Automatic CFG - Preset Loader": { "title": "自动CFG(预设组)", "inputs": { diff --git a/zh-CN/Nodes/ComfyUI-BiRefNet-Hugo.json b/zh-CN/Nodes/ComfyUI-BiRefNet-Hugo.json new file mode 100644 index 0000000..001c93d --- /dev/null +++ b/zh-CN/Nodes/ComfyUI-BiRefNet-Hugo.json @@ -0,0 +1,16 @@ +{ + "BiRefNet_Hugo": { + "title": "🔥BiRefNet", + "inputs": { + "image": "图像" + }, + "widgets": { + "background_color_name": "背景色", + "device": "设备" + }, + "outputs": { + "image": "图像", + "mask": "遮罩" + } + } +} \ No newline at end of file diff --git a/zh-CN/Nodes/ComfyUI-BrushNet.json b/zh-CN/Nodes/ComfyUI-BrushNet.json index 4945f6c..3bb5297 100644 --- a/zh-CN/Nodes/ComfyUI-BrushNet.json +++ b/zh-CN/Nodes/ComfyUI-BrushNet.json @@ -95,6 +95,15 @@ "latent": "Latent" } }, + "RAUNet": { + "title": "RAUNet", + "inputs": { + "model": "模型" + }, + "outputs": { + "model": "模型" + } + }, "BrushNetInpaint": { "title": "BrushNet局部重绘", "inputs": { diff --git a/zh-CN/Nodes/ComfyUI-KJNodes.json b/zh-CN/Nodes/ComfyUI-KJNodes.json index 2b4b0f7..3f4abc7 100644 --- a/zh-CN/Nodes/ComfyUI-KJNodes.json +++ b/zh-CN/Nodes/ComfyUI-KJNodes.json @@ -317,7 +317,7 @@ "mask": "遮罩", "mask_inverted": "反转遮罩" }, - "description": "\n生成指定形状的遮罩或遮罩批次,位置参数为中心位置。" + "description": "生成指定形状的遮罩或遮罩批次,位置参数为中心位置。" }, "CreateTextOnPath": { "title": "创建文本", @@ -385,7 +385,7 @@ "outputs": { "masks": "遮罩" }, - "description": "\n合并多个遮罩为遮罩批次。可以通过“输入数量”设置输入接口数量,点击更新刷新接口。" + "description": "合并多个遮罩为遮罩批次。可以通过“输入数量”设置输入接口数量,点击更新刷新接口。" }, "ColorToMask": { "title": "图像颜色到遮罩", @@ -414,7 +414,8 @@ }, "outputs": { "image": "图像" - } + }, + "description": "color-matcher(图像调色)可以在转换图像之间的色彩样式,用于照片、绘画、序列帧的自动调色以及光场定格修正。\n\n基于 Reinhard 等算法,Pitie 等人提出的 Monge-Kantorovich Linearization (MKL) 算法以及我们结合经典直方图匹配对 Multi-Variate Gaussian Distribution (MVGD)算法的分析解决方案。如下所示,我们的 HM-MVGD-HM 符合方法优于现有方法。\n\nhttps://github.com/hahnec/color-matcher/" }, "BatchCropFromMask": { "title": "遮罩裁剪", @@ -614,7 +615,8 @@ }, "outputs": { "mask": "遮罩" - } + }, + "description": "用于桥接 AudioScheduler 插件的节点:\n\nhttps://github.com/a1lazydog/ComfyUI-AudioScheduler\n\n基于规格化振幅偏移遮罩。" }, "RemapMaskRange": { "title": "重映射遮罩范围", @@ -657,7 +659,8 @@ }, "outputs": { "image": "图像" - } + }, + "description": "按屏幕坐标捕捉区域。\n\n用于实时采样。" }, "PlotCoordinates": { "title": "坐标图", @@ -679,7 +682,7 @@ "bbox_height": "BBox高度", "bbox_width": "BBox宽度" }, - "description": "\n使用 Matplotlib 制作坐标图表序列。" + "description": "使用 Matplotlib 制作坐标图表序列。" }, "InterpolateCoords": { "title": "坐标插值", @@ -690,7 +693,32 @@ "outputs": { "coordinates": "坐标" }, - "description": "\n依据曲线插入坐标" + "description": "依据曲线插入坐标" + }, + "PointsEditor": { + "title": "点编辑器", + "inputs": { + "bg_image": "背景图" + }, + "widgets": { + "points_store": "点位置", + "bbox_store": "BBox位置", + "bbox_format": "BBox格式", + "width": "宽度", + "height": "高度", + "normalize": "规格化", + "New canvs": "新画布", + "Load Image": "加载图像", + "Clear Image": "清除图像" + }, + "outputs": { + "positive_coords": "正面坐标", + "negative_coords": "负面坐标", + "bbox": "BBox", + "bbox_mask": "BBox遮罩", + "cropped_image": "裁剪图像" + }, + "description": "# 开发中 \n尽量不要在工作流中使用这个节点,可能会遇到大量bug并且不稳定!! \n\n## 创建坐标的图形编辑器\n\n**Shift + 左键** 添加正面(绿色)的坐标点。\n\n**Shift + 右键** 添加负面(红色)的坐标点。\n\n**Ctrl + 左键** 绘制方框。\n\n**右键坐标点** 删除该点,不能删除点数组的起点/终点。\n\n要添加图像,选择节点并粘贴或拖入图像。\n\n或从 背景图 接口输入,使用输入图像的第一帧。\n\n**图像会保存到节点和工作流中**\n右键菜单可以清除图像。\n" }, "SoundReactive": { "title": "音频反馈", @@ -707,7 +735,8 @@ "outputs": { "sound_level": "音量图", "sound_level_int": "音量整数" - } + }, + "description": "反馈输入音频的音量。\n\n使用浏览器音频输入。\n\n用于实时采样。" }, @@ -953,7 +982,7 @@ "outputs": { "string": "字符串" }, - "description": "\n合并多个字符串为字符串批次或字符串列表。可以通过“输入数量”设置输入接口数量,点击更新刷新接口。" + "description": "合并多个字符串为字符串批次或字符串列表。可以通过“输入数量”设置输入接口数量,点击更新刷新接口。" }, "EmptyLatentImagePresets": { "title": "空Latent预设", @@ -971,15 +1000,18 @@ "GetImageRangeFromBatch": { "title": "获取图像范围", "inputs": { - "images": "图像" + "images": "图像", + "masks": "遮罩" }, "widgets": { "start_index": "起始编号", "num_frames": "帧数" }, "outputs": { - "IMAGE": "图像" - } + "IMAGE": "图像", + "MASK": "遮罩" + }, + "description": "根据输入图像批次以及参数,创建新图像批次。" }, "ImageAddMulti": { "title": "图像混合(多重)", @@ -1003,7 +1035,7 @@ "outputs": { "images": "图像" }, - "description": "\n混合多个图像。可以通过“输入数量”设置输入接口数量,点击更新刷新接口。" + "description": "混合多个图像。可以通过“输入数量”设置输入接口数量,点击更新刷新接口。" }, "ImageBatchMulti": { "title": "图像组合批次(多重)", @@ -1027,7 +1059,7 @@ "outputs": { "images": "图像" }, - "description": "\n合并多个图像为图像批次。可以通过“输入数量”设置输入接口数量,点击更新刷新接口。" + "description": "合并多个图像为图像批次。可以通过“输入数量”设置输入接口数量,点击更新刷新接口。" }, "ReverseImageBatch": { "title": "反转图像批次", @@ -1048,7 +1080,8 @@ }, "outputs": { "IMAGE": "图像" - } + }, + "description": "将 4 个输入图像合并为 2x2 表格。" }, "ImageGridComposite3x3": { "title": "图像栅格合并3x3", @@ -1065,7 +1098,21 @@ }, "outputs": { "IMAGE": "图像" - } + }, + "description": "将 9 个输入图像合并为 3x3 表格。" + }, + "ImageGridToBatch": { + "title": "图像表格到批次", + "inputs": { + "image": "图像" + }, + "widgets": { + "columns": "列数" + }, + "outputs": { + "IMAGE": "图像" + }, + "description": "将图表转换为单个图像批次。" }, "ImageConcanate": { "title": "图像联结", @@ -1078,7 +1125,40 @@ }, "outputs": { "IMAGE": "图像" - } + }, + "description": "按方向合并两个图像。" + }, + "ImageConcatFromBatch": { + "title": "图像联结(批次)", + "inputs": { + "images": "图像" + }, + "widgets": { + "num_columns": "列数", + "match_image_size": "匹配尺寸", + "max_resolution": "最大分辨率" + }, + "outputs": { + "IMAGE": "图像" + }, + "description": "从图像批次中获取图像,然后按照列数排列为单个图像。" + }, + "ImageConcatMulti": { + "title": "图像联结(多个)", + "inputs": { + "image_1": "图像_1", + "image_2": "图像_2" + }, + "widgets": { + "inputcount": "输入数量", + "direction": "方向", + "match_image_size": "匹配尺寸", + "Update inputs": "更新输入" + }, + "outputs": { + "images": "图像" + }, + "description": "按方向合并多个图像。单击更新以更新输入数量。" }, "ImageBatchTestPattern": { "title": "图像批次图案", @@ -1137,7 +1217,7 @@ "image": "图像", "mask": "遮罩" }, - "description": "\n生成指定形状的图像或图像批次,位置参数为中心位置。" + "description": "生成指定形状的图像或图像批次,位置参数为中心位置。" }, "CreateGradientFromCoords": { "title": "从坐标创建渐变图像", @@ -1154,7 +1234,7 @@ "outputs": { "image": "图像" }, - "description": "\n在坐标位置创建渐变图像。" + "description": "在坐标位置创建渐变图像。" }, "GradientToFloat": { "title": "渐变到浮点", @@ -1168,7 +1248,7 @@ "float_x": "浮点_X", "float_y": "浮点_Y" }, - "description": "\n计算图像浮点列表" + "description": "计算图像浮点列表" }, "WidgetToString": { "title": "组件到字符串", @@ -1280,7 +1360,8 @@ "positive": "正面条件", "negative": "负面条件", "latent": "Latent" - } + }, + "description": "使用插值调度安排 SV3D 的方位角和俯仰角数值。\n\n注意 SV3D 是视频模型,所以调度值必须递进。\n\nhttps://huggingface.co/stabilityai/sv3d" }, "GLIGENTextBoxApplyBatch": { "title": "GLIGEN文本框应用(批次)", @@ -1288,7 +1369,9 @@ "conditioning_to": "条件", "clip": "CLIP", "gligen_textbox_model": "GLIGEN模型", - "latents": "Latent" + "latents": "Latent", + "coordinates": "坐标", + "size_multiplier": "尺寸乘数" }, "widgets": { "text": "文本", @@ -1333,7 +1416,72 @@ "conditioning": "条件", "coord_preview": "坐标预览" }, - "description": "\n这个节点允许在批次中调度 GLIGEN 文本框的位置,和 AnimateDiff-Evolved 一起使用。建议和 曲线编辑器 节点一起使用。\n\n GLIGEN模型可以在 管理器 的 “安装模型” 中下载。或直接在:https://huggingface.co/comfyanonymous/GLIGEN_pruned_safetensors/tree/main 下载。 \n \n 输入: \n- **Latent** 输入用于计算批次大小 \n- **CLIP** 是文本编码器,与其他CLIP输入相同 \n- **GLIGEN模型** 连接到 GLIGEN加载器 节点 \n- **坐标** 接收坐标点json字符串,和 曲线编辑器 节点兼容。 \n- **文本** 文本框位置的提示词 \n- **宽度** 和 **高度** 设置 GLIGEN文本框 的尺寸 \n \n输出:\n- **条件** 连接到 CLIP文本编码 和 采样器 中间 \n- **坐标预览** 用于预览坐标和BBox \n\n" + "description": "这个节点允许在批次中调度 GLIGEN 文本框的位置,和 AnimateDiff-Evolved 一起使用。建议和 曲线编辑器 节点一起使用。\n\n GLIGEN模型可以在 管理器 的 “安装模型” 中下载。或直接在:https://huggingface.co/comfyanonymous/GLIGEN_pruned_safetensors/tree/main 下载。 \n \n 输入: \n- **Latent** 输入用于计算批次大小 \n- **CLIP** 是文本编码器,与其他CLIP输入相同 \n- **GLIGEN模型** 连接到 GLIGEN加载器 节点 \n- **坐标** 接收坐标点json字符串,和 曲线编辑器 节点兼容。 \n- **文本** 文本框位置的提示词 \n- **宽度** 和 **高度** 设置 GLIGEN文本框 的尺寸 \n \n输出:\n- **条件** 连接到 CLIP文本编码 和 采样器 中间 \n- **坐标预览** 用于预览坐标和BBox \n\n" + }, + "CheckpointPerturbWeights": { + "title": "Checkpoint参数扰动", + "inputs": { + "model": "模型" + }, + "widgets": { + "joint_blocks": "joint_blocks", + "final_layer": "final_layer", + "rest_of_the_blocks": "rest_of_the_blocks", + "seed": "随机种", + "control_before_generate": "运行前操作" + }, + "outputs": { + "MODEL": "模型" + } + }, + "Screencap_mss": { + "title": "屏幕捕捉MSS", + "widgets": { + "x": "X", + "y": "Y", + "width": "宽度", + "height": "高度", + "num_frames": "帧数", + "delay": "延迟" + }, + "outputs": { + "images": "图像" + }, + "description": "按屏幕坐标捕捉区域。\n\n用于实时采样。" + }, + "WebcamCaptureCV2": { + "title": "相机捕捉CV2", + "widgets": { + "x": "X", + "y": "Y", + "width": "宽度", + "height": "高度", + "cam_index": "相机序号", + "release": "release" + }, + "outputs": { + "image": "图像" + }, + "description": "使用 CV2 调用网页相机捕捉屏幕。\n\n用于实时采样。" + }, + "FluxBlockLoraLoader": { + "title": "Flux Block LoRA 加载器", + "inputs": { + "model": "模型", + "blocks": "block", + "opt_lora_path": "LoRA路径(可选)" + }, + "widgets": { + "strength_model": "模型强度", + "lora_name": "LoRA名称" + }, + "outputs": { + "model": "模型", + "rank": "rank" + } + }, + "FluxBlockLoraSelect": { + "title": "Flux Block LoRA 选择" }, "LoadICLightUnet": { "title": "加载ICLightUnet", @@ -1346,7 +1494,7 @@ "outputs": { "MODEL": "模型" }, - "description": "\n加载ICLightUnet:加载一个 ICLightUnet 模型。(实验性)开发中 \n 另一种不好用但可以用的方法是在 https://huggingface.co/Kijai/iclight-comfy/blob/main/iclight_fc_converted.safetensors 下载模型,然后和 InstructPixToPix条件 节点一起使用。" + "description": "加载ICLightUnet:加载一个 ICLightUnet 模型。(实验性)开发中 \n 另一种不好用但可以用的方法是在 https://huggingface.co/Kijai/iclight-comfy/blob/main/iclight_fc_converted.safetensors 下载模型,然后和 InstructPixToPix条件 节点一起使用。" }, "StabilityAPI_SD3": { "title": "StabilityAPI SD3", @@ -1367,7 +1515,8 @@ }, "outputs": { "IMAGE": "图像" - } + }, + "description": "# 调用 Stability API\n\n尽量使用同一个key调用API,无论账号有多少个key。\n\n在 https://platform.stability.ai/account/keys 获取key,推荐创建包含key的 config.json 文件然后放到插件目录下。\n\n# 警告:\n\n即使开启了 disable_metadata(禁用元数据),如果工作流程中包含与此节点不同的保存节点,API 密钥也可能被保存到元数据中。\n\nSD3 每次生成需要 6.5 点数\n\nSD3-Turbo 每次生成需要 4 点数\n\n如果不连接图像输入,则使用 文生图 模式" }, "GetImagesFromBatchIndexed": { "title": "从批次获取图像", @@ -1379,7 +1528,8 @@ }, "outputs": { "IMAGE": "图像" - } + }, + "description": "按索引编号选择图像。" }, "InsertImagesToBatchIndexed": { "title": "插入图像到索引批次", @@ -1425,7 +1575,7 @@ "blue": "蓝色", "mask": "遮罩" }, - "description": "\n分离图像为单通道图像,alpha通道分离为遮罩。" + "description": "分离图像为单通道图像,alpha通道分离为遮罩。" }, "MergeImageChannels": { "title": "合并图像通道", @@ -1438,7 +1588,7 @@ "outputs": { "image": "图像" }, - "description": "\n合并通道为图像" + "description": "合并通道为图像" }, "PreviewAnimation": { "title": "预览动画", @@ -1460,7 +1610,8 @@ }, "outputs": { "IMAGE": "图像" - } + }, + "description": "按指定次数复制批次中的图像。\n\n例如包含 5 个图像的批次:0,1,2,3,4\n\n重复 2 次后变为:0,0,1,1,2,2,3,3,4,4" }, "ImageTransformByNormalizedAmplitude": { "title": "按规格化幅度变换图像", @@ -1474,7 +1625,8 @@ }, "outputs": { "IMAGE": "图像" - } + }, + "description": "用于桥接 AudioScheduler 插件的节点:\n\nhttps://github.com/a1lazydog/ComfyUI-AudioScheduler\n\n基于规格化振幅变换图像。" }, "GetLatentsFromBatchIndexed": { "title": "按索引获取Latent", @@ -1534,7 +1686,8 @@ }, "outputs": { "MASK": "遮罩" - } + }, + "description": "用于桥接 AudioScheduler 插件的节点:\n\nhttps://github.com/a1lazydog/ComfyUI-AudioScheduler\n\n基于规格化振幅创建遮罩。" }, "NormalizedAmplitudeToFloatList": { "title": "规格化振幅到浮点列表", @@ -1544,7 +1697,7 @@ "outputs": { "FLOAT": "浮点" }, - "description": "\n连接“音频调度”的桥接节点:https://github.com/a1lazydog/ComfyUI-AudioScheduler \n,从规格化振幅建立一个浮点列表。" + "description": "用于桥接 AudioScheduler 插件的节点:\n\nhttps://github.com/a1lazydog/ComfyUI-AudioScheduler\n\n基于规格化振幅创建浮点列表。" }, "ScaleBatchPromptSchedule": { "title": "缩放提示词批次调度", @@ -1573,7 +1726,8 @@ }, "outputs": { "IMAGE": "图像" - } + }, + "description": "规格化图像到 [-1,1]" }, "ImagePass": { "title": "图像桥接", @@ -1583,13 +1737,13 @@ "outputs": { "IMAGE": "图像" }, - "description": "\n传递图像到下一个节点" + "description": "传递图像到下一个节点" }, "ImageResizeKJ": { "title": "图像缩放(KJ)", "inputs": { "image": "图像", - "get_image_size": "参考图像大小", + "get_image_size": "参考图像", "width_input": "宽度", "height_input": "高度" }, @@ -1598,14 +1752,16 @@ "height": "高度", "upscale_method": "缩放方法", "keep_proportions": "固定宽高比", - "divisible_by": "因数" + "keep_proportion": "固定宽高比", + "divisible_by": "因数", + "crop": "裁剪" }, "outputs": { "IMAGE": "图像", "width": "宽度", "height": "高度" }, - "description": "\n按指定宽高缩放图像。尺寸可由输入指定,最终输出优先级按以下规则排列:\n- 参考图像尺寸 \n- 宽度-输入 和 高度-输入 \n- 宽度 和 高度 \n \n固定宽高比会按最高尺寸固定宽高比。" + "description": "按指定宽高缩放图像。尺寸可由输入指定,最终输出优先级按以下规则排列:\n- 参考图像尺寸 \n- 宽度-输入 和 高度-输入 \n- 宽度 和 高度 \n \n固定宽高比会按最高尺寸固定宽高比。" }, "CameraPoseVisualizer": { "title": "相机姿态预览", @@ -1666,7 +1822,7 @@ "outputs": { "composite": "图像" }, - "description": "\n预览图像或遮罩,同时输入图像和遮罩时会合并遮罩到图像上。\n当 穿透 开启时将禁用合成,用于通过合并为视频节点的预览。" + "description": "预览图像或遮罩,同时输入图像和遮罩时会合并遮罩到图像上。\n当 穿透 开启时将禁用合成,用于通过合并为视频节点的预览。" }, "MaskOrImageToWeight": { "title": "遮罩或图像到权重", @@ -1680,7 +1836,7 @@ "outputs": { "FLOAT": "浮点" }, - "description": "\n获取遮罩或图像批次的平均值,并按 输出类型 输出结果。" + "description": "获取遮罩或图像批次的平均值,并按 输出类型 输出结果。" }, "MaskOrImageToWeigh": { "title": "遮罩或图像到权重", @@ -1763,7 +1919,7 @@ "outputs": { "clipseg_model": "CLIPSeg模型" }, - "description": "\n使用 huggingface_hub 下载 CLIPSeg 模型到 Comfy/models/clip_seg" + "description": "使用 huggingface_hub 下载 CLIPSeg 模型到 Comfy/models/clip_seg" }, "GetMaskSizeAndCount": { "title": "获取遮罩尺寸数量", @@ -1776,7 +1932,7 @@ "height": "高度", "count": "数量" }, - "description": "\n输出遮罩的宽度、高度、批次大小" + "description": "输出遮罩的宽度、高度、批次大小" }, "GetImageSizeAndCount": { "title": "获取图像尺寸数量", @@ -1789,7 +1945,7 @@ "height": "高度", "count": "数量" }, - "description": "\n输出图像的宽度、高度、批次大小" + "description": "输出图像的宽度、高度、批次大小" }, "ModelPassThrough": { "title": "模型桥接", @@ -1799,7 +1955,7 @@ "outputs": { "model": "模型" }, - "description": "\n将模型传递到下一个节点" + "description": "将模型传递到下一个节点" }, "FloatToSigmas": { "title": "浮点到Sigmas", @@ -1809,7 +1965,7 @@ "outputs": { "SIGMAS": "Sigmas" }, - "description": "\n从浮点列表创建sigmas tensor" + "description": "从浮点列表创建sigmas tensor" }, "WeightScheduleExtend": { "title": "权重调度扩展", @@ -1823,7 +1979,7 @@ "outputs": { "FLOAT": "浮点" }, - "description": "\n扩展不同的值列表/系列,并根据需要进行转换" + "description": "扩展不同的值列表/系列,并根据需要进行转换" }, "SplineEditor": { "title": "曲线编辑器", @@ -1848,6 +2004,36 @@ "count": "数量", "normalized_str": "规格化字符串" }, - "description": "\n# 开发中 \n不要在工作流中经常使用这个节点,可能会遇到大量bug并且不稳定!! \n \n##用于创建各类值调度的图形化编辑器 \n\n**Shift+左键单击** 添加新控制点,**Ctrl+左键单击** 创建中间控制点,**右键单击** 移除控制点。\n不能删除端点。\n\n 右键背景会调出菜单:一些视觉设置,不影响输出效果:\n - 控制柄可见性 \n - 显示采样点 \n\n**采样精度** 设置采样点数量,从样条线本身返回采样点,和实际控制点无关,由插值类型决定。\n采样方法:\n - 时间:沿时间轴采样,用于调度 \n - 路径:沿曲线路径采样,用于坐标 \n\n 输出:\n - 遮罩批次 \n 适用于任何接收遮罩的节点 \n - 浮点列表 \n 适用于 IPAdapter权重组 \n - pandas series \n 适用于 适用于接收 Fizz批次调度 节点 的节点 \n - torch tensor \n 适用于不明节点" + "description": "# 开发中 \n尽量不要在工作流中使用这个节点,可能会遇到大量bug并且不稳定!! \n \n##用于创建各类值调度的图形化编辑器 \n\n**Shift+左键单击** 添加新控制点,**Ctrl+左键单击** 创建中间控制点,**右键单击** 移除控制点。\n不能删除端点。\n\n 右键背景会调出菜单:一些视觉设置,不影响输出效果:\n - 控制柄可见性 \n - 显示采样点 \n\n**采样精度** 设置采样点数量,从样条线本身返回采样点,和实际控制点无关,由插值类型决定。\n采样方法:\n - 时间:沿时间轴采样,用于调度 \n - 路径:沿曲线路径采样,用于坐标 \n\n 输出:\n - 遮罩批次 \n 适用于任何接收遮罩的节点 \n - 浮点列表 \n 适用于 IPAdapter权重组 \n - pandas series \n 适用于 适用于接收 Fizz批次调度 节点 的节点 \n - torch tensor \n 适用于不明节点" + }, + + "DifferentialDiffusionAdvanced": { + "title": "差异扩散(高级)", + "inputs": { + "model": "模型", + "samples": "Latent", + "mask": "遮罩" + }, + "widgets": { + "multiplier": "乘数" + }, + "outputs": { + "MODEL": "模型", + "LATENT": "Latent" + } + }, + "LoadImagesFromFolderKJ": { + "title": "加载图像(文件夹)", + "widgets": { + "folder": "文件夹", + "image_load_cap": "加载上限", + "start_index": "起始编号" + }, + "outputs": { + "image": "图像", + "mask": "遮罩", + "count": "数量", + "image_path": "图像路径" + } } } \ No newline at end of file diff --git a/zh-CN/Nodes/ComfyUI-Marigold.json b/zh-CN/Nodes/ComfyUI-Marigold.json index c09cd5e..1299518 100644 --- a/zh-CN/Nodes/ComfyUI-Marigold.json +++ b/zh-CN/Nodes/ComfyUI-Marigold.json @@ -7,7 +7,7 @@ "outputs": { "marigold_model": "Marigold模型" }, - "description": "\n基于扩散的单目深度推算: \nhttps://github.com/prs-eth/Marigold  \n  \n使用 Diffusers 0.28.0 Marigold 管线。模型会自动下载到 ComfyUI/Models/diffusers 文件夹内" + "description": "\n基于扩散的单目深度推算: https://github.com/prs-eth/Marigold  \n\n 使用 Diffusers 0.28.0 Marigold 框架。模型会自动下载到 ComfyUI/Models/diffusers 文件夹内" }, "MarigoldDepthEstimation_v2": { "title": "Marigold_v2深度推算", @@ -28,9 +28,9 @@ "outputs": { "image": "图像" }, - "description": "\n基于扩散的单目深度推算: \nhttps://github.com/prs-eth/Marigold  \n  \n使用 Diffusers 0.28.0 Marigold 管线。" + "description": "\n基于扩散的单目深度推算: https://github.com/prs-eth/Marigold  \n\n 使用 Diffusers 0.28.0 Marigold 框架。" }, - "MarigoldDepthEstimation_v2_Video": { + "MarigoldDepthEstimation_v2_video": { "title": "Marigold_v2深度推算视频", "inputs": { "marigold_model": "Marigold模型", @@ -48,7 +48,7 @@ "outputs": { "image": "图像" }, - "description": "\n基于扩散的单目深度推算: \nhttps://github.com/prs-eth/Marigold  \n  \n使用 Diffusers 0.28.0 Marigold 管线。\n这个节点使用上一帧作为初始Latent,用以平滑视频。" + "description": "\n基于扩散的单目深度推算: https://github.com/prs-eth/Marigold  \n\n使用 Diffusers 0.28.0 Marigold 框架。\n\n这个节点使用上一帧作为初始Latent,用以平滑视频。" }, "MarigoldDepthEstimation": { "title": "Marigold深度推算", diff --git a/zh-CN/Nodes/ComfyUI-SUPIR.json b/zh-CN/Nodes/ComfyUI-SUPIR.json index bcde0b6..c272f57 100644 --- a/zh-CN/Nodes/ComfyUI-SUPIR.json +++ b/zh-CN/Nodes/ComfyUI-SUPIR.json @@ -30,6 +30,25 @@ "SUPIR_VAE": "SUPIR_VAE" } }, + "SUPIR_model_loader_v2_clip": { + "title": "SUPIR模型加载器_V2()", + "inputs": { + "model": "模型", + "clip_l": "CLIP_L", + "clip_g": "CLIP_G", + "vae": "VAE" + }, + "widgets": { + "supir_model": "SUPIR模型", + "fp8_unet": "fp8_unet", + "diffusion_dtype": "剪枝类型", + "high_vram": "高显存" + }, + "outputs": { + "SUPIR_MODEL": "SUPIR模型", + "SUPIR_VAE": "SUPIR_VAE" + } + }, "SUPIR_encode": { "title": "SUPIR编码", "inputs": { diff --git a/zh-CN/Nodes/ComfyUI-Tripo.json b/zh-CN/Nodes/ComfyUI-Tripo.json index fd26d2d..1364ae2 100644 --- a/zh-CN/Nodes/ComfyUI-Tripo.json +++ b/zh-CN/Nodes/ComfyUI-Tripo.json @@ -45,6 +45,17 @@ "API_KEY": "APIKey" } }, + "TripoRefineModel": { + "title": "TripoAPI优化模型", + "inputs": { + "apikey": "APIKey", + "model_task_id": "模型任务ID" + }, + "outputs": { + "MESH": "网格", + "MODEL_TASK_ID": "模型任务ID" + } + }, "TripoAnimateRigNode": { "title": "Tripo绑骨模型", "inputs": { diff --git a/zh-CN/Nodes/ComfyUI_IPAdapter_plus.json b/zh-CN/Nodes/ComfyUI_IPAdapter_plus.json index 6541583..08f724c 100644 --- a/zh-CN/Nodes/ComfyUI_IPAdapter_plus.json +++ b/zh-CN/Nodes/ComfyUI_IPAdapter_plus.json @@ -1,4 +1,83 @@ { + "IPAdapterMS": { + "title": "应用IPAdapter Mad Scientist", + "inputs": { + "model": "模型", + "ipadapter": "IPAdapter", + "image": "图像", + "image_negative": "负面图像", + "attn_mask": "关注层遮罩", + "clip_vision": "CLIP视觉", + "insightface": "InsightFace" + }, + "widgets": { + "weight": "权重", + "weight_faceidv2": "FaceID_V2权重", + "weight_type": "权重类型", + "combine_embeds": "合并嵌入组", + "start_at": "开始应用位置", + "end_at": "结束应用位置", + "embeds_scaling": "嵌入组缩放", + "layer_weights": "层权重" + }, + "outputs": { + "MODEL": "模型" + } + }, + "IPAdapterClipVisionEnhancer": { + "title": "应用IPAdapter CLIP Vision 增强", + "inputs": { + "model": "模型", + "ipadapter": "IPAdapter", + "image": "图像", + "image_negative": "负面图像", + "attn_mask": "关注层遮罩", + "clip_vision": "CLIP视觉", + "insightface": "InsightFace" + }, + "widgets": { + "weight": "权重", + "weight_faceidv2": "FaceID_V2权重", + "weight_type": "权重类型", + "combine_embeds": "合并嵌入组", + "start_at": "开始应用位置", + "end_at": "结束应用位置", + "embeds_scaling": "嵌入组缩放", + "enhance_tiles": "增强分块", + "enhance_ratio": "增强比率" + }, + "outputs": { + "MODEL": "模型" + } + }, + "IPAdapterClipVisionEnhancerBatch": { + "title": "应用IPAdapter CLIP Vision 批次增强", + "inputs": { + "model": "模型", + "ipadapter": "IPAdapter", + "image": "图像", + "image_negative": "负面图像", + "attn_mask": "关注层遮罩", + "clip_vision": "CLIP视觉", + "insightface": "InsightFace" + }, + "widgets": { + "weight": "权重", + "weight_faceidv2": "FaceID_V2权重", + "weight_type": "权重类型", + "combine_embeds": "合并嵌入组", + "start_at": "开始应用位置", + "end_at": "结束应用位置", + "embeds_scaling": "嵌入组缩放", + "enhance_tiles": "增强分块", + "enhance_ratio": "增强比率" + }, + "outputs": { + "MODEL": "模型" + } + }, + + "IPAdapterApply": { "title": "IPAdapter应用", "inputs": { @@ -23,7 +102,7 @@ } }, "IPAdapterApplyFaceID": { - "title": "IPAdapter应用(FaceID)", + "title": "IPAdapter应用(FaceID)", "inputs": { "ipadapter": "IPAdapter", "clip_vision": "CLIP视觉", @@ -47,7 +126,7 @@ } }, "IPAdapterApplyEncoded": { - "title": "IPAdapter应用(已编码)", + "title": "IPAdapter应用(已编码)", "inputs": { "ipadapter": "IPAdapter", "embeds": "嵌入组", @@ -121,7 +200,7 @@ } }, "IPAdapterAdvanced": { - "title": "应用IPAdapter(高级)", + "title": "应用IPAdapter(高级)", "inputs": { "model": "模型", "ipadapter": "IPAdapter", @@ -143,7 +222,7 @@ } }, "IPAdapterBatch": { - "title": "应用IPAdapter(批次)", + "title": "应用IPAdapter(批次)", "inputs": { "model": "模型", "ipadapter": "IPAdapter", @@ -187,8 +266,32 @@ "MODEL": "模型" } }, + "IPAdapterFaceIDKolors": { + "title": "应用IPAdapterFaceID(Kolors)", + "inputs": { + "model": "模型", + "ipadapter": "IPAdapter", + "image": "正面图像", + "image_negative": "负面图像", + "attn_mask": "关注层遮罩", + "clip_vision": "CLIP视觉", + "insightface": "InsightFace" + }, + "widgets": { + "weight": "权重", + "weight_faceidv2": "FaceID_V2权重", + "weight_type": "权重类型", + "combine_embeds": "合并嵌入组", + "start_at": "开始应用位置", + "end_at": "结束应用位置", + "embeds_scaling": "嵌入组缩放" + }, + "outputs": { + "MODEL": "模型" + } + }, "IPAdapterFaceIDBatch": { - "title": "应用IPAdapterFaceID(批次)", + "title": "应用IPAdapterFaceID(批次)", "inputs": { "model": "模型", "ipadapter": "IPAdapter", @@ -212,7 +315,7 @@ } }, "IPAAdapterFaceIDBatch": { - "title": "应用IPAdapterFaceID(批次)", + "title": "应用IPAdapterFaceID(批次)", "inputs": { "model": "模型", "ipadapter": "IPAdapter", @@ -236,7 +339,7 @@ } }, "IPAdapterTiled": { - "title": "应用IPAdapter(分块)", + "title": "应用IPAdapter(分块)", "inputs": { "model": "模型", "ipadapter": "IPAdapter", @@ -261,7 +364,7 @@ } }, "IPAdapterTiledBatch": { - "title": "应用IPAdapter(分块批次)", + "title": "应用IPAdapter(分块批次)", "inputs": { "model": "模型", "ipadapter": "IPAdapter", @@ -285,7 +388,7 @@ } }, "IPAdapterEmbeds": { - "title": "应用IPAdapter(嵌入组)", + "title": "应用IPAdapter(嵌入组)", "inputs": { "model": "模型", "ipadapter": "IPAdapter", @@ -305,6 +408,119 @@ "MODEL": "模型" } }, + "IPAdapterEmbedsBatch": { + "title": "应用IPAdapter(批次嵌入组)", + "inputs": { + "model": "模型", + "ipadapter": "IPAdapter", + "pos_embed": "正面嵌入组", + "neg_embed": "负面嵌入组", + "attn_mask": "关注层遮罩", + "clip_vision": "CLIP视觉" + }, + "widgets": { + "weight": "权重", + "weight_type": "权重类型", + "start_at": "开始应用位置", + "end_at": "结束应用位置", + "embeds_scaling": "嵌入组缩放" + }, + "outputs": { + "MODEL": "模型" + } + }, + "IPAdapterPreciseStyleTransfer": { + "title": "应用IPAdapter精确风格迁移", + "inputs": { + "model": "模型", + "ipadapter": "IPAdapter", + "image": "图像", + "image_negative": "负面图像", + "attn_mask": "关注层遮罩", + "clip_vision": "CLIP视觉", + "insightface": "InsightFace" + }, + "widgets": { + "weight": "权重", + "style_boost": "风格增强", + "combine_embeds": "合并嵌入组", + "start_at": "开始应用位置", + "end_at": "结束应用位置", + "embeds_scaling": "嵌入组缩放" + }, + "outputs": { + "MODEL": "模型" + } + }, + "IPAdapterPreciseStyleTransferBatch": { + "title": "应用IPAdapter精确风格迁移(批次)", + "inputs": { + "model": "模型", + "ipadapter": "IPAdapter", + "image": "图像", + "image_negative": "负面图像", + "attn_mask": "关注层遮罩", + "clip_vision": "CLIP视觉", + "insightface": "InsightFace" + }, + "widgets": { + "weight": "权重", + "style_boost": "风格增强", + "combine_embeds": "合并嵌入组", + "start_at": "开始应用位置", + "end_at": "结束应用位置", + "embeds_scaling": "嵌入组缩放" + }, + "outputs": { + "MODEL": "模型" + } + }, + "IPAdapterPreciseComposition": { + "title": "应用IPAdapter精确合成", + "inputs": { + "model": "模型", + "ipadapter": "IPAdapter", + "image": "图像", + "image_negative": "负面图像", + "attn_mask": "关注层遮罩", + "clip_vision": "CLIP视觉", + "insightface": "InsightFace" + }, + "widgets": { + "weight": "权重", + "composition_boost": "合成增强", + "combine_embeds": "合并嵌入组", + "start_at": "开始应用位置", + "end_at": "结束应用位置", + "embeds_scaling": "嵌入组缩放" + }, + "outputs": { + "MODEL": "模型" + } + }, + "IPAdapterPreciseCompositionBatch": { + "title": "应用IPAdapter精确合成(批次)", + "inputs": { + "model": "模型", + "ipadapter": "IPAdapter", + "image": "图像", + "image_negative": "负面图像", + "attn_mask": "关注层遮罩", + "clip_vision": "CLIP视觉", + "insightface": "InsightFace" + }, + "widgets": { + "weight": "权重", + "style_boost": "风格增强", + "combine_embeds": "合并嵌入组", + "start_at": "开始应用位置", + "end_at": "结束应用位置", + "embeds_scaling": "嵌入组缩放" + }, + "outputs": { + "MODEL": "模型" + } + }, "IPAdapterUnifiedLoader": { "title": "IPAdapter加载器", "inputs": { @@ -354,7 +570,7 @@ } }, "IPAdapterUnifiedLoaderCommunity": { - "title": "IPAdapter加载器(社区)", + "title": "IPAdapter加载器(社区)", "inputs": { "model": "模型", "ipadapter": "IPAdapter" @@ -368,7 +584,7 @@ } }, "IPAdapterFromParams": { - "title": "应用IPAdapter(参数组)", + "title": "应用IPAdapter(参数组)", "inputs": { "model": "模型", "ipadapter": "IPAdapter", @@ -441,7 +657,7 @@ } }, "IPAdapterStyleCompositionBatch": { - "title": "IPAdapter风格合成SDXL(批次)", + "title": "IPAdapter风格合成SDXL(批次)", "inputs": { "model": "模型", "ipadapter": "IPAdapter", diff --git a/zh-CN/Nodes/PuLID_ComfyUI.json b/zh-CN/Nodes/PuLID_ComfyUI.json index 51b41db..384da91 100644 --- a/zh-CN/Nodes/PuLID_ComfyUI.json +++ b/zh-CN/Nodes/PuLID_ComfyUI.json @@ -30,7 +30,8 @@ "pulid": "PuLID", "eva_clip": "EVA_CLIP", "face_analysis": "面部分析模型", - "image": "图像" + "image": "图像", + "attn_mask": "关注层遮罩" }, "widgets": { "method": "方法", @@ -41,5 +42,27 @@ "outputs": { "MODEL": "模型" } + }, + "ApplyPulidAdvanced": { + "title": "应用PuLID(高级)", + "inputs": { + "model": "模型", + "pulid": "PuLID", + "eva_clip": "EVA_CLIP", + "face_analysis": "面部分析模型", + "image": "图像", + "attn_mask": "关注层遮罩" + }, + "widgets": { + "weight": "权重", + "projection": "预测", + "fidelity": "精确度", + "noise": "噪波", + "start_at": "开始应用位置", + "end_at": "结束应用位置" + }, + "outputs": { + "MODEL": "模型" + } } } \ No newline at end of file diff --git a/zh-CN/Nodes/comfy_mtb.json b/zh-CN/Nodes/comfy_mtb.json index f66e226..84d3811 100644 --- a/zh-CN/Nodes/comfy_mtb.json +++ b/zh-CN/Nodes/comfy_mtb.json @@ -37,6 +37,47 @@ "images": "图像" } }, + + + "Audio Sequence (mtb)": { + "title": "音频序列", + "inputs": { + "audio_1": "音频_1" + }, + "widgets": { + "silence_duration": "静音时长" + }, + "outputs": { + "sequenced_audio": "音频序列" + }, + "description": "按序排列所有输入的音频\n\n- 在每段之间添加静音时长,用于抑制片段重复以及控制时长。\n- 根据最高采样率重新采样所有音频,\n- 如果其中一个输入为立体声,则将所有音频转换为立体声。" + }, + "Audio Stack (mtb)": { + "title": "音频堆栈", + "inputs": { + "audio_1": "音频_1" + }, + "outputs": { + "stacked_audio": "音频堆栈" + }, + "description": "堆叠/重叠所有输入的音频\n\n- 音频长度取决于最长的输入项。\n\n- 重采样为输入中的最高采样率。\n\n- 如果其中一个输入为立体声,则将所有音频转换为立体声。" + }, + "Audio Cut (mtb)": { + "title": "音频裁剪", + "inputs": { + "audio": "音频" + }, + "widgets": { + "length": "长度", + "offset": "偏移" + }, + "outputs": { + "cut_audio": "裁剪音频" + }, + "description": "裁剪音频,单位为毫秒ms。" + }, + + "Batch Float (mtb)": { "title": "浮点批次", "widgets": { @@ -263,6 +304,36 @@ "STRING": "字符串" } }, + + "Extract Coordinates From Image (mtb)": { + "title": "从图像解析坐标", + "inputs": { + "image": "图像", + "mask": "遮罩" + }, + "widgets": { + "threshold": "阈值", + "max_points": "坐标点上限" + }, + "outputs": { + "BATCH_COORDNATES": "坐标批次", + "IMAGE": "图像" + }, + "description": "从图像批次中按照阈值解析出 2D 坐标点。" + }, + "Coordinates To String (mtb)": { + "title": "坐标批次到字符串", + "inputs": { + "coordinates": "坐标批次" + }, + "widgets": { + "frame": "帧数" + }, + "outputs": { + "STRING": "字符串" + } + }, + "Bbox From Mask (mtb)": { "title": "遮罩提取BBox", "inputs": { @@ -322,6 +393,19 @@ "IMAGE": "图像" } }, + "Split Bbox (mtb)": { + "title": "解析BBox", + "inputs": { + "bbox": "BBox" + }, + "outputs": { + "x": "X", + "y": "Y", + "width": "宽度", + "height": "高度" + }, + "description": "解析bbox" + }, "Curve (mtb)": { "title": "浮点曲线", "outputs": { @@ -626,7 +710,30 @@ }, "outputs": { "IMAGE": "图像" - } + }, + "description": "各类颜色校正方案" + }, + "Color Correct GPU (mtb)": { + "title": "颜色校正GPU", + "inputs": { + "image": "图像", + "mask": "遮罩" + }, + "widgets": { + "force_gpu": "强制GPU", + "clamp": "钳制", + "gamma": "伽马", + "contrast": "对比度", + "exposure": "曝光", + "offset": "偏移", + "hue": "色相", + "saturation": "饱和度", + "value": "明度" + }, + "outputs": { + "IMAGE": "图像" + }, + "description": "各类颜色校正方案(使用torch)" }, "Blur (mtb)": { "title": "模糊", diff --git a/zh-CN/Nodes/comfyui-inpaint-nodes.json b/zh-CN/Nodes/comfyui-inpaint-nodes.json index f480710..078fa49 100644 --- a/zh-CN/Nodes/comfyui-inpaint-nodes.json +++ b/zh-CN/Nodes/comfyui-inpaint-nodes.json @@ -101,5 +101,18 @@ "outputs": { "MASK": "遮罩" } + }, + "INPAINT_ExpandMask": { + "title": "扩展遮罩", + "inputs": { + "mask": "遮罩" + }, + "widgets": { + "grow": "生长", + "blur": "模糊" + }, + "outputs": { + "MASK": "遮罩" + } } } \ No newline at end of file diff --git a/zh-CN/Nodes/internal.json b/zh-CN/Nodes/internal.json index 2baa311..002aac5 100644 --- a/zh-CN/Nodes/internal.json +++ b/zh-CN/Nodes/internal.json @@ -227,6 +227,12 @@ "SAMPLER": "采样器" } }, + "SamplerDPMPP_2S_Ancestral": { + "title": "DPMPP_2S_Ancestral采样器", + "outputs": { + "SAMPLER": "采样器" + } + }, "SamplerEulerAncestral": { "title": "Euler_A采样器", "widgets": { @@ -465,7 +471,8 @@ }, "outputs": { "MODEL": "模型" - } + }, + "description": "用于微调扩散模型和 CLIP 模型,改变 Latent 降噪的效果,实现控制风格等功能。多个 LoRA 可以直接连接到一起。" }, @@ -1229,7 +1236,8 @@ "outputs": { "IMAGE": "图像", "The decoded image.": "解码后的图像" - } + }, + "description": "将 Latent 图像解码为像素空间的图像。" }, "VAEEncode": { "title": "VAE编码", @@ -1674,6 +1682,17 @@ "IMAGE": "图像" } }, + "WebcamCapture": { + "title": "网页镜头捕捉", + "widgets": { + "width": "宽度", + "height": "高度", + "capture_on_queue": "执行时捕捉" + }, + "outputs": { + "IMAGE": "图像" + } + }, "SaveImageWithAlpha": { "title": "保存图像(Alpha)", "inputs": { @@ -2089,7 +2108,8 @@ }, "widgets": { "samples": "Latent", - "latent": "Latent" + "latent": "Latent", + "filename_prefix": "文件名前缀" } }, "LoadLatent": { @@ -2293,7 +2313,8 @@ "CLIPLoader": { "title": "CLIP加载器", "widgets": { - "clip_name": "CLIP名称" + "clip_name": "CLIP名称", + "type": "类型" }, "outputs": { "CLIP": "CLIP" @@ -2559,6 +2580,15 @@ "filename_prefix": "文件名前缀" } }, + "ModelSave": { + "title": "保存模型", + "inputs": { + "model": "模型" + }, + "widgets": { + "filename_prefix": "文件名前缀" + } + }, "CLIPSave": { "title": "保存CLIP", "inputs": { diff --git a/zh-CN/Nodes/sd-perturbed-attention.json b/zh-CN/Nodes/sd-perturbed-attention.json index e52faa9..5af6b34 100644 --- a/zh-CN/Nodes/sd-perturbed-attention.json +++ b/zh-CN/Nodes/sd-perturbed-attention.json @@ -1,6 +1,6 @@ { "PerturbedAttention": { - "title": "PAG注意力引导(高级)", + "title": "PAG注意力引导(高级)", "inputs": { "model": "模型" }, @@ -13,5 +13,25 @@ "outputs": { "MODEL": "模型" } + }, + "SmoothedEnergyGuidanceAdvanced": { + "title": "SEG引导(高级)", + "inputs": { + "model": "模型" + }, + "widgets": { + "scale": "缩放", + "blur_sigma": "模糊Sigma", + "unet_block": "UNet块", + "unet_block_id": "UNet块ID", + "sigma_start": "Sigma初始", + "sigma_end": "Sigma结束", + "rescale": "重缩放", + "rescale_mode": "重缩放模式", + "unet_block_list": "UNet块列表" + }, + "outputs": { + "MODEL": "模型" + } } } \ No newline at end of file