├── .cache └── .cache_directory ├── .github └── workflows │ └── publish.yml ├── .gitignore ├── README.md ├── README_en.md ├── __init__.py ├── docs ├── 3DImage.md ├── AB SamplerCustom (experimental).md ├── ACN_AdvancedControlNetApply.md ├── ACN_DefaultUniversalWeights.md ├── ACN_ReferenceControlNet.md ├── ACN_ReferenceControlNetFinetune.md ├── ACN_ReferencePreprocessor.md ├── ACN_SparseCtrlIndexMethodNode.md ├── ACN_SparseCtrlLoaderAdvanced.md ├── ACN_SparseCtrlMergedLoaderAdvanced.md ├── ACN_SparseCtrlRGBPreprocessor.md ├── ACN_SparseCtrlSpreadMethodNode.md ├── ADE_AdjustPEFullStretch.md ├── ADE_AdjustPEManual.md ├── ADE_AdjustPESweetspotStretch.md ├── ADE_AdjustWeightAllAdd.md ├── ADE_AdjustWeightAllMult.md ├── ADE_AdjustWeightIndivAdd.md ├── ADE_AdjustWeightIndivAttnAdd.md ├── ADE_AdjustWeightIndivAttnMult.md ├── ADE_AdjustWeightIndivMult.md ├── ADE_AnimateDiffCombine.md ├── ADE_AnimateDiffKeyframe.md ├── ADE_AnimateDiffLoRALoader.md ├── ADE_AnimateDiffLoaderGen1.md ├── ADE_AnimateDiffLoaderV1Advanced.md ├── ADE_AnimateDiffLoaderWithContext.md ├── ADE_AnimateDiffModelSettings.md ├── ADE_AnimateDiffModelSettingsAdvancedAttnStrengths.md ├── ADE_AnimateDiffModelSettingsSimple.md ├── ADE_AnimateDiffModelSettings_Release.md ├── ADE_AnimateDiffSamplingSettings.md ├── ADE_AnimateDiffSettings.md ├── ADE_AnimateDiffUniformContextOptions.md ├── ADE_AnimateDiffUnload.md ├── ADE_ApplyAnimateDiffModel.md ├── ADE_ApplyAnimateDiffModelSimple.md ├── ADE_ApplyAnimateDiffModelWithCameraCtrl.md ├── ADE_ApplyAnimateLCMI2VModel.md ├── ADE_AttachLoraHookToCLIP.md ├── ADE_AttachLoraHookToConditioning.md ├── ADE_BatchedContextOptions.md ├── ADE_CameraCtrlAnimateDiffKeyframe.md ├── ADE_CameraManualPoseAppend.md ├── ADE_CameraPoseAdvanced.md ├── ADE_CameraPoseBasic.md ├── ADE_CameraPoseCombo.md ├── ADE_CombineLoraHooks.md ├── ADE_CombineLoraHooksEight.md ├── ADE_CombineLoraHooksFour.md ├── ADE_ConditioningSetMask.md ├── ADE_ConditioningSetMaskAndCombine.md ├── ADE_ConditioningSetUnmaskedAndCombine.md ├── ADE_CustomCFG.md ├── ADE_CustomCFGKeyframe.md ├── ADE_EmptyLatentImageLarge.md ├── ADE_InjectI2VIntoAnimateDiffModel.md ├── ADE_IterationOptsDefault.md ├── ADE_IterationOptsFreeInit.md ├── ADE_LoadAnimateDiffModel.md ├── ADE_LoadAnimateDiffModelWithCameraCtrl.md ├── ADE_LoadAnimateLCMI2VModel.md ├── ADE_LoadCameraPoses.md ├── ADE_LoopedUniformContextOptions.md ├── ADE_LoopedUniformViewOptions.md ├── ADE_LoraHookKeyframe.md ├── ADE_LoraHookKeyframeFromStrengthList.md ├── ADE_LoraHookKeyframeInterpolation.md ├── ADE_MultivalDynamic.md ├── ADE_MultivalScaledMask.md ├── ADE_NoiseLayerAdd.md ├── ADE_NoiseLayerAddWeighted.md ├── ADE_NoiseLayerReplace.md ├── ADE_PairedConditioningSetMask.md ├── ADE_PairedConditioningSetMaskAndCombine.md ├── ADE_PairedConditioningSetUnmaskedAndCombine.md ├── ADE_RawSigmaSchedule.md ├── ADE_RegisterLoraHook.md ├── ADE_RegisterLoraHookModelOnly.md ├── ADE_RegisterModelAsLoraHook.md ├── ADE_RegisterModelAsLoraHookModelOnly.md ├── ADE_ReplaceCameraParameters.md ├── ADE_ReplaceOriginalPoseAspectRatio.md ├── ADE_SetLoraHookKeyframe.md ├── ADE_SigmaSchedule.md ├── ADE_SigmaScheduleSplitAndCombine.md ├── ADE_SigmaScheduleWeightedAverage.md ├── ADE_SigmaScheduleWeightedAverageInterp.md ├── ADE_StandardStaticContextOptions.md ├── ADE_StandardStaticViewOptions.md ├── ADE_StandardUniformContextOptions.md ├── ADE_StandardUniformViewOptions.md ├── ADE_TimestepsConditioning.md ├── ADE_UpscaleAndVAEEncode.md ├── ADE_UseEvolvedSampling.md ├── ADE_ViewsOnlyContextOptions.md ├── AIGC-Grounding-SAM.md ├── AIO_Preprocessor.md ├── AMT VFI.md ├── APISR_Lterative_Zho.md ├── APISR_ModelLoader_Zho.md ├── APISR_Zho.md ├── APersonMaskGenerator.md ├── AV_CheckpointLoader.md ├── AV_CheckpointMerge.md ├── AV_CheckpointModelsToParametersPipe.md ├── AV_CheckpointSave.md ├── AV_ClaudeApi.md ├── AV_ControlNetEfficientLoader.md ├── AV_ControlNetEfficientLoaderAdvanced.md ├── AV_ControlNetEfficientStacker.md ├── AV_ControlNetEfficientStackerSimple.md ├── AV_ControlNetLoader.md ├── AV_ControlNetPreprocessor.md ├── AV_FaceDetailer.md ├── AV_FaceDetailerPipe.md ├── AV_IPAdapter.md ├── AV_IPAdapterPipeline.md ├── AV_LLMApiConfig.md ├── AV_LLMChat.md ├── AV_LLMMessage.md ├── AV_LoraListLoader.md ├── AV_LoraListStacker.md ├── AV_LoraLoader.md ├── AV_OpenAIApi.md ├── AV_ParametersPipeToCheckpointModels.md ├── AV_ParametersPipeToPrompts.md ├── AV_PromptsToParametersPipe.md ├── AV_SAMLoader.md ├── AV_StyleApply.md ├── AV_VAELoader.md ├── AbsCosWave.md ├── AbsSinWave.md ├── AdainImage.md ├── AdainLatent.md ├── AdaptiveThresholding.md ├── Add String To Many.md ├── Add To Playlist (mtb).md ├── AddAlpha.md ├── AddLabel.md ├── AddMask.md ├── AddMetaData.md ├── AddNoise.md ├── AddTool.md ├── AdjectiveStyler.md ├── AdjectiveStylerAdvanced.md ├── AdjustRect.md ├── AlignYourStepsScheduler.md ├── AlphaChanelAdd.md ├── AlphaChanelAddByMask.md ├── AlphaChanelAsMask.md ├── AlphaChanelRemove.md ├── AlphaChanelRestore.md ├── AlphaClean.md ├── AlphaMatte.md ├── Analyze Palette [Dream].md ├── AnimalPosePreprocessor.md ├── AnimateDiffCombine.md ├── AnimateDiffLoaderV1.md ├── AnimateDiffLoraLoader.md ├── AnimateDiffModuleLoader.md ├── AnimateDiffSampler.md ├── AnimateDiffSlidingWindowOptions.md ├── Animation Builder (mtb).md ├── AnimeFace_SemSegPreprocessor.md ├── AnimeLineArtPreprocessor.md ├── AnimeLineArt_Preprocessor_Provider_for_SEGS %2F%2FInspire.md ├── AnimeLineArt_Preprocessor_Provider_for_SEGS __Inspire.md ├── Any Switch (rgthree).md ├── Any To String (mtb).md ├── AnyToAny.md ├── Anything Everywhere%3F.md ├── Anything Everywhere.md ├── Anything Everywhere3.md ├── AppInfo.md ├── Apply ControlNet Stack.md ├── Apply Text Template (mtb).md ├── ApplyInstantID.md ├── ApplyInstantIDAdvanced.md ├── ApplyInstantIDControlNet.md ├── ApplyRegionalIPAdapters %2F%2FInspire.md ├── ApplyRegionalIPAdapters __Inspire.md ├── ApplyScaleUModelNode.md ├── ApplyStableSRUpscaler.md ├── AreaToMask.md ├── ArgosTranslateCLIPTextEncodeNode.md ├── ArgosTranslateTextNode.md ├── ArithmeticBlend.md ├── ArtistStyler.md ├── ArtistStylerAdvanced.md ├── AsciiArt.md ├── AspectRatioSelector.md ├── Asymmetric Tiled KSampler.md ├── Auto Pan Equilateral (mtb).md ├── AutoNegativePrompt.md ├── Automatic CFG - Advanced.md ├── Automatic CFG - Fastest.md ├── Automatic CFG - Negative.md ├── Automatic CFG - Post rescale only.md ├── Automatic CFG.md ├── AzazealStylesStyler.md ├── AzazealStylesStylerAdvanced.md ├── BAE-NormalMapPreprocessor.md ├── BBoxListItemSelect(FaceParsing).md ├── BBoxResize(FaceParsing).md ├── BLIP Analyze Image.md ├── BLIP Model Loader.md ├── BLIPCaption.md ├── BLIPLoader.md ├── BLVAEEncode.md ├── BNK_AddCLIPSDXLParams.md ├── BNK_AddCLIPSDXLRParams.md ├── BNK_CLIPTextEncodeAdvanced.md ├── BNK_CLIPTextEncodeSDXLAdvanced.md ├── BNK_GetSigma.md ├── BNK_InjectNoise.md ├── BNK_NoisyLatentImage.md ├── BNK_SlerpLatent.md ├── BNK_TiledKSampler.md ├── BNK_TiledKSamplerAdvanced.md ├── BNK_Unsampler.md ├── BRIAAI Matting.md ├── Banana_StylesStyler.md ├── Banana_StylesStylerAdvanced.md ├── BaseModel_Loader_local.md ├── BasicGuider.md ├── BasicPipeToDetailerPipe.md ├── BasicPipeToDetailerPipeSDXL.md ├── BasicScheduler.md ├── Batch Crop Image.md ├── Batch Crop Resize Inplace.md ├── Batch Float (mtb).md ├── Batch Float Assemble (mtb).md ├── Batch Float Fill (mtb).md ├── Batch Float Fit (mtb).md ├── Batch Float Normalize (mtb).md ├── Batch Load Images.md ├── Batch Make (mtb).md ├── Batch Merge (mtb).md ├── Batch Resize Image for SDXL.md ├── Batch Shake (mtb).md ├── Batch Shape (mtb).md ├── Batch Time Wrap (mtb).md ├── Batch Transform (mtb).md ├── Batch Unsampler(ttulttul%2FComfyUI-Iterative-Mixer).md ├── Batch Unsampler.md ├── BatchAlign.md ├── BatchAverageImage.md ├── BatchAverageUnJittered.md ├── BatchCLIPSeg.md ├── BatchCount+.md ├── BatchCreativeInterpolation.md ├── BatchCropFromMask.md ├── BatchCropFromMaskAdvanced.md ├── BatchNormalizeImage.md ├── BatchNormalizeLatent.md ├── BatchPromptSchedule.md ├── BatchPromptScheduleEncodeSDXL.md ├── BatchPromptScheduleLatentInput.md ├── BatchPromptScheduleSDXLLatentInput.md ├── BatchStringSchedule.md ├── BatchUncrop.md ├── BatchUncropAdvanced.md ├── BatchValueSchedule.md ├── BatchValueScheduleLatentInput.md ├── Bbox (mtb).md ├── Bbox From Mask (mtb).md ├── BboxDetectorCombined_v2.md ├── BboxDetectorSEGS.md ├── BboxToInt.md ├── BboxVisualize.md ├── Beat Curve [Dream].md ├── BetterFilmGrain.md ├── BiRefNet_Loader.md ├── BiRefNet_Remove_Background.md ├── Big Float Switch [Dream].md ├── Big Image Switch [Dream].md ├── Big Int Switch [Dream].md ├── Big Latent Switch [Dream].md ├── Big Palette Switch [Dream].md ├── Big Text Switch [Dream].md ├── BinaryPreprocessor.md ├── BindImageListPromptList %2F%2FInspire.md ├── BindImageListPromptList __Inspire.md ├── BitwiseAndMask.md ├── BitwiseAndMaskForEach.md ├── Blend Latents (PPF Noise).md ├── Blend Latents.md ├── Blend.md ├── Blur (mtb).md ├── Blur(EllangoK%2FComfyUI-post-processing-nodes).md ├── Blur.md ├── BlurImageFast.md ├── BlurMaskFast.md ├── Bool.md ├── Boolean To Float [Dream].md ├── Boolean To Int [Dream].md ├── Boolean To Text.md ├── BooleanPrimitive.md ├── Bounded Image Blend with Mask.md ├── Bounded Image Blend.md ├── Bounded Image Crop with Mask.md ├── Bounded Image Crop.md ├── BoundingRect (contours).md ├── Breast_StateStyler.md ├── Breast_StateStylerAdvanced.md ├── BrushMotion.md ├── Build Filename String (WLSH).md ├── Build Prompt [Dream].md ├── BuildColorRangeAdvanced (hsv).md ├── BuildColorRangeHSV (hsv).md ├── Bus Node.md ├── CAIN VFI.md ├── CCSR_Model_Select.md ├── CCSR_Upscale.md ├── CFGGuider.md ├── CLAHE.md ├── CLIP +%2F- w%2FText Unified (WLSH).md ├── CLIP Input Switch.md ├── CLIP Positive-Negative (WLSH).md ├── CLIP Positive-Negative XL (WLSH).md ├── CLIP Positive-Negative XL w%2FText (WLSH).md ├── CLIP Positive-Negative w%2FText (WLSH).md ├── CLIP Vision Input Switch.md ├── CLIPAttentionMultiply.md ├── CLIPEncodeMultiple.md ├── CLIPEncodeMultipleAdvanced.md ├── CLIPLoader.md ├── CLIPMergeAdd.md ├── CLIPMergeSimple.md ├── CLIPMergeSubtract.md ├── CLIPSave.md ├── CLIPSeg Batch Masking.md ├── CLIPSeg Masking.md ├── CLIPSeg Model Loader.md ├── CLIPSegDetectorProvider.md ├── CLIPSeg_.md ├── CLIPSetLastLayer.md ├── CLIPTextEncode (BlenderNeko Advanced + NSP).md ├── CLIPTextEncode (NSP).md ├── CLIPTextEncode SDXL Plus (JPS).md ├── CLIPTextEncode.md ├── CLIPTextEncodeControlnet.md ├── CLIPTextEncodeList.md ├── CLIPTextEncodeSDXL+.md ├── CLIPTextEncodeSDXL.md ├── CLIPTextEncodeSDXLRefiner.md ├── CLIPTextEncodeSequence2.md ├── CLIPTextEncodeWithWeight %2F%2FInspire.md ├── CLIPTextEncodeWithWeight __Inspire.md ├── CLIPVisionEncode.md ├── CLIPVisionLoader.md ├── CM_BoolBinaryOperation.md ├── CM_BoolToInt.md ├── CM_BoolUnaryOperation.md ├── CM_BreakoutVec2.md ├── CM_BreakoutVec3.md ├── CM_BreakoutVec4.md ├── CM_ComposeVec2.md ├── CM_ComposeVec3.md ├── CM_ComposeVec4.md ├── CM_FloatBinaryCondition.md ├── CM_FloatBinaryOperation.md ├── CM_FloatToInt.md ├── CM_FloatToNumber.md ├── CM_FloatUnaryCondition.md ├── CM_FloatUnaryOperation.md ├── CM_IntBinaryCondition.md ├── CM_IntBinaryOperation.md ├── CM_IntToBool.md ├── CM_IntToFloat.md ├── CM_IntToNumber.md ├── CM_IntUnaryCondition.md ├── CM_IntUnaryOperation.md ├── CM_NearestSDXLResolution.md ├── CM_NumberBinaryCondition.md ├── CM_NumberBinaryOperation.md ├── CM_NumberToFloat.md ├── CM_NumberToInt.md ├── CM_NumberUnaryCondition.md ├── CM_NumberUnaryOperation.md ├── CM_SDXLResolution.md ├── CM_Vec2BinaryCondition.md ├── CM_Vec2BinaryOperation.md ├── CM_Vec2ScalarOperation.md ├── CM_Vec2ToScalarBinaryOperation.md ├── CM_Vec2ToScalarUnaryOperation.md ├── CM_Vec2UnaryCondition.md ├── CM_Vec2UnaryOperation.md ├── CM_Vec3BinaryCondition.md ├── CM_Vec3BinaryOperation.md ├── CM_Vec3ScalarOperation.md ├── CM_Vec3ToScalarBinaryOperation.md ├── CM_Vec3ToScalarUnaryOperation.md ├── CM_Vec3UnaryCondition.md ├── CM_Vec3UnaryOperation.md ├── CM_Vec4BinaryCondition.md ├── CM_Vec4BinaryOperation.md ├── CM_Vec4ScalarOperation.md ├── CM_Vec4ToScalarBinaryOperation.md ├── CM_Vec4ToScalarUnaryOperation.md ├── CM_Vec4UnaryCondition.md ├── CM_Vec4UnaryOperation.md ├── CR 8 Channel In.md ├── CR 8 Channel Out.md ├── CR Apply ControlNet.md ├── CR Apply LoRA Stack.md ├── CR Apply Model Merge.md ├── CR Apply Multi Upscale.md ├── CR Apply Multi-ControlNet.md ├── CR Aspect Ratio Banners.md ├── CR Aspect Ratio SDXL.md ├── CR Aspect Ratio Social Media.md ├── CR Aspect Ratio.md ├── CR Batch Images From List.md ├── CR Batch Process Switch.md ├── CR Binary Pattern.md ├── CR Binary To Bit List.md ├── CR Bit Schedule.md ├── CR Central Schedule.md ├── CR Checker Pattern.md ├── CR Clamp Value.md ├── CR Clip Input Switch.md ├── CR Color Bars.md ├── CR Color Gradient.md ├── CR Color Panel.md ├── CR Color Tint.md ├── CR Combine Prompt.md ├── CR Combine Schedules.md ├── CR Comic Panel Templates.md ├── CR Composite Text.md ├── CR Conditioning Input Switch.md ├── CR Conditioning Mixer.md ├── CR ControlNet Input Switch.md ├── CR Current Frame.md ├── CR Cycle Images Simple.md ├── CR Cycle Images.md ├── CR Cycle LoRAs.md ├── CR Cycle Models.md ├── CR Cycle Text Simple.md ├── CR Cycle Text.md ├── CR Data Bus In.md ├── CR Data Bus Out.md ├── CR Debatch Frames.md ├── CR Diamond Panel.md ├── CR Draw Pie.md ├── CR Draw Shape.md ├── CR Draw Text.md ├── CR Encode Scheduled Prompts.md ├── CR Feathered Border.md ├── CR Float Range List.md ├── CR Float To Integer.md ├── CR Float To String.md ├── CR Font File List.md ├── CR Get Parameter From Prompt.md ├── CR Gradient Float.md ├── CR Gradient Integer.md ├── CR Half Drop Panel.md ├── CR Halftone Filter.md ├── CR Halftone Grid.md ├── CR Hires Fix Process Switch.md ├── CR Image Border.md ├── CR Image Grid Panel.md ├── CR Image Input Switch (4 way).md ├── CR Image Input Switch.md ├── CR Image List Simple.md ├── CR Image List.md ├── CR Image Output.md ├── CR Image Panel.md ├── CR Image Pipe Edit.md ├── CR Image Pipe In.md ├── CR Image Pipe Out.md ├── CR Image Size.md ├── CR Img2Img Process Switch.md ├── CR Increment Float.md ├── CR Increment Integer.md ├── CR Index Increment.md ├── CR Index Multiply.md ├── CR Index Reset.md ├── CR Index.md ├── CR Integer Multiple.md ├── CR Integer Range List.md ├── CR Integer To String.md ├── CR Interpolate Latents.md ├── CR Intertwine Lists.md ├── CR Keyframe List.md ├── CR Latent Batch Size.md ├── CR Latent Input Switch.md ├── CR LoRA List.md ├── CR LoRA Stack.md ├── CR Load Animation Frames.md ├── CR Load Flow Frames.md ├── CR Load GIF As List.md ├── CR Load Image List Plus.md ├── CR Load Image List.md ├── CR Load LoRA.md ├── CR Load Schedule From File.md ├── CR Load Scheduled LoRAs.md ├── CR Load Scheduled Models.md ├── CR Load Text List.md ├── CR Mask Text.md ├── CR Math Operation.md ├── CR Model Input Switch.md ├── CR Model List.md ├── CR Model Merge Stack.md ├── CR Module Input.md ├── CR Module Output.md ├── CR Module Pipe Loader.md ├── CR Multi Upscale Stack.md ├── CR Multi-ControlNet Stack.md ├── CR Multiline Text.md ├── CR Output Flow Frames.md ├── CR Output Schedule To File.md ├── CR Overlay Text.md ├── CR Overlay Transparent Image.md ├── CR Page Layout.md ├── CR Pipe Switch.md ├── CR Polygons.md ├── CR Prompt List Keyframes.md ├── CR Prompt List.md ├── CR Prompt Scheduler.md ├── CR Prompt Text.md ├── CR Radial Gradient.md ├── CR Random Hex Color.md ├── CR Random LoRA Stack.md ├── CR Random Multiline Colors.md ├── CR Random Multiline Values.md ├── CR Random Panel Codes.md ├── CR Random RGB Gradient.md ├── CR Random RGB.md ├── CR Random Shape Pattern.md ├── CR Random Weight LoRA.md ├── CR Repeater.md ├── CR SD1.5 Aspect Ratio.md ├── CR SDXL Aspect Ratio.md ├── CR SDXL Base Prompt Encoder.md ├── CR SDXL Prompt Mix Presets.md ├── CR SDXL Prompt Mixer.md ├── CR SDXL Style Text.md ├── CR Save Text To File.md ├── CR Schedule Input Switch.md ├── CR Seamless Checker.md ├── CR Seed to Int.md ├── CR Seed.md ├── CR Select Font.md ├── CR Select ISO Size.md ├── CR Select Model.md ├── CR Select Resize Method.md ├── CR Set Switch From String.md ├── CR Set Value On Binary.md ├── CR Set Value On Boolean.md ├── CR Set Value on String.md ├── CR Simple Banner.md ├── CR Simple Binary Pattern.md ├── CR Simple Image Compare.md ├── CR Simple List.md ├── CR Simple Meme Template.md ├── CR Simple Prompt List Keyframes.md ├── CR Simple Prompt List.md ├── CR Simple Prompt Scheduler.md ├── CR Simple Schedule.md ├── CR Simple Text Panel.md ├── CR Simple Text Scheduler.md ├── CR Simple Text Watermark.md ├── CR Simple Value Scheduler.md ├── CR Split String.md ├── CR Starburst Colors.md ├── CR Starburst Lines.md ├── CR String To Boolean.md ├── CR String To Combo.md ├── CR String To Number.md ├── CR Style Bars.md ├── CR Switch Model and CLIP.md ├── CR Text Blacklist.md ├── CR Text Concatenate.md ├── CR Text Cycler.md ├── CR Text Input Switch (4 way).md ├── CR Text Input Switch.md ├── CR Text Length.md ├── CR Text List Simple.md ├── CR Text List To String.md ├── CR Text List.md ├── CR Text Operation.md ├── CR Text Replace.md ├── CR Text Scheduler.md ├── CR Text.md ├── CR Thumbnail Preview.md ├── CR Trigger.md ├── CR Upscale Image.md ├── CR VAE Decode.md ├── CR VAE Input Switch.md ├── CR Value Cycler.md ├── CR Value Scheduler.md ├── CR Value.md ├── CR Vignette Filter.md ├── CR XY From Folder.md ├── CR XY Index.md ├── CR XY Interpolate.md ├── CR XY List.md ├── CR XY Product.md ├── CR XY Save Grid Image.md ├── CR_Aspect Ratio For Print.md ├── CSV Curve [Dream].md ├── CSV Generator [Dream].md ├── Cache Node.md ├── CacheBackendData %2F%2FInspire.md ├── CacheBackendData __Inspire.md ├── CacheBackendDataList %2F%2FInspire.md ├── CacheBackendDataList __Inspire.md ├── CacheBackendDataNumberKey %2F%2FInspire.md ├── CacheBackendDataNumberKey __Inspire.md ├── CacheBackendDataNumberKeyList %2F%2FInspire.md ├── CacheBackendDataNumberKeyList __Inspire.md ├── CalculateFrameOffset.md ├── Calculation [Dream].md ├── CameraPoseVisualizer.md ├── CameraStyler.md ├── CameraStylerAdvanced.md ├── Camera_AnglesStyler.md ├── Camera_AnglesStylerAdvanced.md ├── Canny.md ├── CannyEdgeMask.md ├── CannyEdgePreprocessor.md ├── Canny_Preprocessor_Provider_for_SEGS %2F%2FInspire.md ├── Canny_Preprocessor_Provider_for_SEGS __Inspire.md ├── Canvas_Tab.md ├── CenterImage.md ├── Cfg Literal.md ├── CfgScheduleHookProvider.md ├── ChameleonMask.md ├── Change Channel Count.md ├── ChangeImageBatchSize %2F%2FInspire.md ├── ChangeImageBatchSize __Inspire.md ├── ChangeLatentBatchSize __Inspire.md ├── ChangeSystemMessage.md ├── CharacterInText.md ├── ChatGPTOpenAI.md ├── Checkpoint Loader (Simple).md ├── Checkpoint Loader Simple Mikey.md ├── Checkpoint Loader w%2FName (WLSH).md ├── Checkpoint Loader.md ├── Checkpoint Selector.md ├── CheckpointHash.md ├── CheckpointLoader (dirty).md ├── CheckpointLoader%7Cpysssss.md ├── CheckpointLoader.md ├── CheckpointLoaderSimple (dirty).md ├── CheckpointLoaderSimple.md ├── CheckpointLoaderSimpleShared %2F%2FInspire.md ├── CheckpointLoaderSimpleShared __Inspire.md ├── CheckpointLoaderSimpleWithNoiseSelect.md ├── CheckpointNameSelector.md ├── CheckpointSave.md ├── ChromaticAberration.md ├── CinematicLook.md ├── Circular VAEDecode.md ├── CircularVAEDecode(jags111%2FComfyUI_Jags_VectorMagic).md ├── CircularVAEDecode.md ├── CkptNames_.md ├── ClampOutliers.md ├── ClearMemory.md ├── ClipClamp.md ├── ClipVisionClamp.md ├── ClipVisionOutputClamp.md ├── Clothing_StateStyler.md ├── Clothing_StateStylerAdvanced.md ├── Clothing_StyleStyler.md ├── Clothing_StyleStylerAdvanced.md ├── Color (RGB).md ├── Color (hexadecimal).md ├── Color Clip (advanced).md ├── Color Clip ADE20k.md ├── Color Clip.md ├── Color Correct (mtb).md ├── Color.md ├── ColorAdjust(FaceParsing).md ├── ColorBlend.md ├── ColorCorrect(EllangoK%2FComfyUI-post-processing-nodes).md ├── ColorCorrect.md ├── ColorDictionary (custom).md ├── ColorDictionary.md ├── ColorMatch.md ├── ColorMatchImage.md ├── ColorPreprocessor.md ├── ColorTint.md ├── ColorToMask.md ├── Color_Preprocessor_Provider_for_SEGS %2F%2FInspire.md ├── Color_Preprocessor_Provider_for_SEGS __Inspire.md ├── Colored Image (mtb).md ├── ColorizeDepthmap.md ├── Combine Masks.md ├── CombineMasks_.md ├── CombineRegionalPrompts.md ├── ComfyWordCloud.md ├── Common Frame Dimensions [Dream].md ├── Compare Palettes [Dream].md ├── Compare.md ├── CompositeMotionBrush.md ├── CompositeMotionBrushWithoutModel.md ├── CompositionStyler.md ├── CompositionStylerAdvanced.md ├── Concat Images (mtb).md ├── ConcatConditioningsWithMultiplier %2F%2FInspire.md ├── ConcatConditioningsWithMultiplier __Inspire.md ├── ConcatStringSingle.md ├── CondPassThrough.md ├── Conditioning Grid (cond).md ├── Conditioning Grid (string) Advanced.md ├── Conditioning Grid (string).md ├── Conditioning Input Switch.md ├── Conditioning Switch (JPS).md ├── ConditioningAverage.md ├── ConditioningBlend.md ├── ConditioningClamp.md ├── ConditioningCombine.md ├── ConditioningCombineMultiple+.md ├── ConditioningConcat.md ├── ConditioningMultiCombine.md ├── ConditioningSetArea.md ├── ConditioningSetAreaPercentage.md ├── ConditioningSetAreaStrength.md ├── ConditioningSetMask.md ├── ConditioningSetMaskAndCombine.md ├── ConditioningSetMaskAndCombine3.md ├── ConditioningSetMaskAndCombine4.md ├── ConditioningSetMaskAndCombine5.md ├── ConditioningSetTimestepRange.md ├── ConditioningZeroOut.md ├── ConsoleDebug+.md ├── Constant (mtb).md ├── Constant Mask.md ├── Constant Number.md ├── ConstrainImage%7Cpysssss.md ├── ConstrainImage.md ├── ConstrainImageforVideo%7Cpysssss.md ├── Context (rgthree).md ├── Context Big (rgthree).md ├── Context Merge (rgthree).md ├── Context Merge Big (rgthree).md ├── Context Switch (rgthree).md ├── Context Switch Big (rgthree).md ├── Contour To Mask.md ├── Contours.md ├── Control Net Model Input Switch.md ├── Control Net Stacker.md ├── ControlLoraSave.md ├── ControlNet Switch (JPS).md ├── ControlNetApply.md ├── ControlNetApplyAdvanced.md ├── ControlNetClamp.md ├── ControlNetHadamard (manual).md ├── ControlNetHadamard.md ├── ControlNetLoader.md ├── ControlNetLoaderAdvanced.md ├── ControlNetPreprocessorSelector.md ├── ConversableAgentCreator.md ├── ConversableAgentCreatorAdvanced.md ├── Convert Color Space.md ├── Convert Masks to Images.md ├── ConvertAgentAsTool.md ├── ConvertAgentToLlamaindex.md ├── ConvertImg.md ├── ConvertNormals.md ├── CopyMakeBorder.md ├── CoreMLDetailerHookProvider.md ├── CosWave.md ├── Create Grid Image from Batch.md ├── Create Grid Image.md ├── Create Morph Image from Path.md ├── Create Morph Image.md ├── Create QR Code.md ├── Create Rect Mask.md ├── Create Video from Path.md ├── CreateAudioMask.md ├── CreateFadeMask.md ├── CreateFadeMaskAdvanced.md ├── CreateFluidMask.md ├── CreateGradientMask.md ├── CreateMagicMask.md ├── CreatePromptVariant.md ├── CreateRequestMetadata.md ├── CreateShapeMask.md ├── CreateShapeMaskOnPath.md ├── CreateTavilySearchTool.md ├── CreateTextMask.md ├── CreateVoronoiMask.md ├── Crop (mtb).md ├── Crop Image Pipe (JPS).md ├── Crop Image Settings (JPS).md ├── Crop Image Square (JPS).md ├── Crop Image TargetSize (JPS).md ├── CropFace.md ├── CropMask.md ├── Cross Fade Image Batches (SuperBeasts.AI).md ├── Cross-Hatch Power Fractal (PPF Noise).md ├── Cross-Hatch Power Fractal Settings (PPF Noise).md ├── CrossFadeImages.md ├── CtrlNet CannyEdge Pipe (JPS).md ├── CtrlNet CannyEdge Settings (JPS).md ├── CtrlNet MiDaS Pipe (JPS).md ├── CtrlNet MiDaS Settings (JPS).md ├── CtrlNet OpenPose Pipe (JPS).md ├── CtrlNet OpenPose Settings (JPS).md ├── CtrlNet ZoeDepth Pipe (JPS).md ├── CtrlNet ZoeDepth Settings (JPS).md ├── Curve (mtb).md ├── Curve To Float (mtb).md ├── CustomControlNetWeights.md ├── CustomSigmas.md ├── CustomT2IAdapterWeights.md ├── Cut By Mask.md ├── DF_Absolute_value.md ├── DF_Ceil.md ├── DF_Conditioning_area_scale_by_ratio.md ├── DF_Cosines.md ├── DF_Divide.md ├── DF_DynamicPrompts_Text_Box.md ├── DF_Float.md ├── DF_Floor.md ├── DF_Get_image_size.md ├── DF_Get_latent_size.md ├── DF_Image_scale_by_ratio.md ├── DF_Image_scale_to_side.md ├── DF_Int_to_Float.md ├── DF_Integer.md ├── DF_Latent_Scale_by_ratio.md ├── DF_Latent_Scale_to_side.md ├── DF_Logic_node.md ├── DF_Multiply.md ├── DF_Power.md ├── DF_Random.md ├── DF_Sinus.md ├── DF_Square_root.md ├── DF_String_Concatenate.md ├── DF_String_Replace.md ├── DF_Subtract.md ├── DF_Sum.md ├── DF_Tangent.md ├── DF_Text.md ├── DF_Text_Box.md ├── DF_To_text_(Debug).md ├── DPCombinatorialGenerator.md ├── DPFeelingLucky.md ├── DPJinja.md ├── DPMagicPrompt.md ├── DPOutput.md ├── DPRandomGenerator.md ├── DSINE-NormalMapPreprocessor.md ├── DWPreprocessor.md ├── DWPreprocessor_Provider_for_SEGS %2F%2FInspire.md ├── DWPreprocessor_Provider_for_SEGS __Inspire.md ├── DZ_Face_Detailer.md ├── Debug (mtb).md ├── Debug Number to Console.md ├── DebugInput.md ├── DebugPrint.md ├── DebugTensorShape+.md ├── Deep Bump (mtb).md ├── DeepDanbooruCaption.md ├── DeepTranslatorCLIPTextEncodeNode.md ├── DeepTranslatorTextNode.md ├── Deflicker (SuperBeasts.AI).md ├── Demofusion From Single File.md ├── Demofusion.md ├── DenoiseScheduleHookProvider.md ├── DenoiseSchedulerDetailerHookProvider.md ├── DensePosePreprocessor.md ├── Densepose Subject Estimation.md ├── DependenciesEdit.md ├── DepthAnythingPreprocessor.md ├── DepthStyler.md ├── DepthStylerAdvanced.md ├── DetailerForEach.md ├── DetailerForEachDebug.md ├── DetailerForEachDebugPipe.md ├── DetailerForEachPipe.md ├── DetailerForEachPipeForAnimateDiff.md ├── DetailerHookCombine.md ├── DetailerPipeToBasicPipe.md ├── Dictionary to Console.md ├── DiffControlNetLoader.md ├── DiffControlNetLoaderAdvanced.md ├── DifferenceChecker.md ├── DifferentialDiffusion.md ├── Diffusers Hub Model Down-Loader.md ├── Diffusers Model Loader.md ├── DiffusersLoader.md ├── DiffusionEdge_Preprocessor.md ├── DilateErodeMask.md ├── Disable Enable Switch (JPS).md ├── DisableNoise.md ├── Display Any (rgthree).md ├── Display Int (rgthree).md ├── Dissolve.md ├── DistanceTransform.md ├── DodgeAndBurn.md ├── DownloadInstanceDiffusionModels.md ├── DragNUWA Run MotionBrush.md ├── DragNUWA Run.md ├── Draw Contour(s).md ├── DrawText+.md ├── DualCFGGuider.md ├── DualCLIPLoader.md ├── DummyLatentOut.md ├── DynamicDelayProcessor.md ├── DynamicThresholdingFull.md ├── DynamicThresholdingSimple.md ├── ELLATextEncode.md ├── ESAM_ModelLoader_Zho.md ├── EditBasicPipe.md ├── EditDetailerPipe.md ├── EditDetailerPipeSDXL.md ├── EditableCLIPEncode.md ├── Eff. Loader SDXL.md ├── Efficient Loader.md ├── EmbeddingPrompt.md ├── Empty Images.md ├── Empty Latent Ratio Custom SDXL.md ├── Empty Latent Ratio Select SDXL.md ├── Empty Latent by Pixels (WLSH).md ├── Empty Latent by Ratio (WLSH).md ├── Empty Latent by Size (WLSH).md ├── EmptyImage.md ├── EmptyLatentImage.md ├── EmptyLatentImagePresets.md ├── EmptyMotionData.md ├── EmptySegs.md ├── Enable Disable Switch (JPS).md ├── EnhanceDetail.md ├── EnhanceImage.md ├── EnvironmentStyler.md ├── EnvironmentStylerAdvanced.md ├── EqualizeHistogram.md ├── Esheep_Split_Image.md ├── EvalFloats.md ├── Evaluate Floats.md ├── Evaluate Integers.md ├── Evaluate Strings.md ├── ExponentialScheduler.md ├── Export API.md ├── Export With Ffmpeg (mtb).md ├── ExportSMPLTo3DSoftware.md ├── Export_SMPLMultipleSubjects_To_3DSoftware.md ├── ExposureAdjust.md ├── ExtendColorList.md ├── ExtendCondList.md ├── ExtendFloatList.md ├── ExtendImageList.md ├── ExtendIntList.md ├── ExtendLatentList.md ├── ExtendMaskList.md ├── ExtendModelList.md ├── ExtendStringList.md ├── ExtractKeyframes+.md ├── FFMPEG Video Encoder [Dream].md ├── FILM VFI.md ├── FLAVR VFI.md ├── FL_Ascii.md ├── FL_AudioConverter.md ├── FL_AudioFrameCalculator.md ├── FL_AudioPreview.md ├── FL_CodeNode.md ├── FL_DirectoryCrawl.md ├── FL_Glitch.md ├── FL_HexagonalPattern.md ├── FL_ImageCaptionSaver.md ├── FL_ImageDimensionDisplay.md ├── FL_ImageDurationSync.md ├── FL_ImagePixelator.md ├── FL_ImageRandomizer.md ├── FL_PixelSort.md ├── FL_Ripple.md ├── Face Swap (mtb).md ├── FaceAnalysisModels.md ├── FaceBBoxDetect(FaceParsing).md ├── FaceBBoxDetectorLoader(FaceParsing).md ├── FaceBoundingBox.md ├── FaceDetailer.md ├── FaceDetailerPipe.md ├── FaceEmbedDistance.md ├── FaceFixerOpenCV.md ├── FaceKeypointsPreprocessor.md ├── FaceParse(FaceParsing).md ├── FaceParsingModelLoader(FaceParsing).md ├── FaceParsingProcessorLoader(FaceParsing).md ├── FaceParsingResultsParser(FaceParsing).md ├── FaceRestoreCFWithModel.md ├── FaceRestoreModelLoader.md ├── FaceStyler.md ├── FaceStylerAdvanced.md ├── FaceToMask.md ├── FacialPartColoringFromPoseKps.md ├── FadeMaskEdges.md ├── FakeScribblePreprocessor.md ├── FakeScribblePreprocessor_Provider_for_SEGS %2F%2FInspire.md ├── FakeScribblePreprocessor_Provider_for_SEGS __Inspire.md ├── Fans Prompt Styler Negative.md ├── Fans Prompt Styler Positive.md ├── Fans Styler.md ├── Fans Text Concatenate.md ├── FeatherMask.md ├── FeatheredMask.md ├── File Count [Dream].md ├── FileNamePrefix.md ├── FileNamePrefixDateDirFirst.md ├── Film Interpolation (mtb).md ├── FilmGrain.md ├── Filter Contour.md ├── Filter Z (mtb).md ├── Filter.md ├── FilterSchedule.md ├── FilterStyler.md ├── FilterStylerAdvanced.md ├── FilterZeroMasksAndCorrespondingImages.md ├── Finalize Prompt [Dream].md ├── FindComplementaryColor.md ├── FindThreshold.md ├── Fit Number (mtb).md ├── FizzFrame.md ├── FizzFrameConcatenate.md ├── FlatLatentsIntoSingleGrid.md ├── FlipSigmas.md ├── FlipSigmasAdjusted.md ├── Float Input [Dream].md ├── Float To Floats (mtb).md ├── Float To Number (mtb).md ├── Float to Log Entry [Dream].md ├── Float to String.md ├── Float.md ├── FloatConstant.md ├── FloatRange %2F%2FInspire.md ├── FloatRange __Inspire.md ├── FloatSlider.md ├── FloatToMask.md ├── FloatToSigmas.md ├── Floats To Float (mtb).md ├── Floats To Ints (mtb).md ├── FocalPointStyler.md ├── FocalPointStylerAdvanced.md ├── FocusStyler.md ├── FocusStylerAdvanced.md ├── Font.md ├── FooocusPromptExpansion.md ├── Fooocus_KSampler.md ├── Fooocus_KSamplerAdvanced.md ├── Fooocus_KSamplerEfficient.md ├── Fooocus_KSamplerEfficientAdvanced.md ├── Frame Count Calculator [Dream].md ├── Frame Counter (Directory) [Dream].md ├── Frame Counter (Simple) [Dream].md ├── Frame Counter Info [Dream].md ├── Frame Counter Offset [Dream].md ├── Frame Counter Time Offset [Dream].md ├── Framed Mask Grab Cut 2.md ├── Framed Mask Grab Cut.md ├── FreeU (Advanced).md ├── FreeU.md ├── FreeU_V2 (Advanced).md ├── FreeU_V2.md ├── FromBasicPipe.md ├── FromBasicPipe_v2.md ├── FromDetailerPipe.md ├── FromDetailerPipeSDXL.md ├── FromDetailerPipe_v2.md ├── FromIPAdapterPipe %2F%2FInspire.md ├── FromIPAdapterPipe __Inspire.md ├── FromListGet1Color.md ├── FromListGet1Cond.md ├── FromListGet1Float.md ├── FromListGet1Image.md ├── FromListGet1Int.md ├── FromListGet1Latent.md ├── FromListGet1Mask.md ├── FromListGet1Model.md ├── FromListGet1String.md ├── FromListGetColors.md ├── FromListGetConds.md ├── FromListGetFloats.md ├── FromListGetImages.md ├── FromListGetInts.md ├── FromListGetLatents.md ├── FromListGetMasks.md ├── FromListGetModels.md ├── FromListGetStrings.md ├── GLIGENLoader.md ├── GLIGENTextBoxApply.md ├── GLIGENTextBoxApplyBatch.md ├── GLIGENTextBoxApplyBatchCoords.md ├── GMFSS Fortuna VFI.md ├── Generate Border Mask (WLSH).md ├── GenerateNoise.md ├── GenerateReply.md ├── Generation TXT IMG Settings (JPS).md ├── Get Batch From History (mtb).md ├── Get Contour from list.md ├── Get Date Time String (JPS).md ├── Get First Image.md ├── Get Image Size (JPS).md ├── Get Image Size.md ├── Get Last Image.md ├── Get Models.md ├── Get Prompt.md ├── Get resolution [Crystools].md ├── GetBoolFromJson.md ├── GetFloatFromJson.md ├── GetImageRangeFromBatch.md ├── GetImageSize+.md ├── GetImageSize.md ├── GetImageSize_.md ├── GetImagesFromBatchIndexed.md ├── GetIntFromJson.md ├── GetLatentsFromBatchIndexed.md ├── GetObjectFromJson.md ├── GetSAMEmbedding.md ├── GetSigma.md ├── GetTextFromJson.md ├── GligenClamp.md ├── GlobalSampler %2F%2FInspire.md ├── GlobalSampler __Inspire.md ├── GlobalSeed %2F%2FInspire.md ├── GlobalSeed __Inspire.md ├── Glow.md ├── GoogleTranslateCLIPTextEncodeNode.md ├── GoogleTranslateTextNode.md ├── GradientImage.md ├── Grayscale Image (WLSH).md ├── GridOutput.md ├── GroundingDinoModelLoader (segment anything).md ├── GroundingDinoSAMSegment (segment anything).md ├── GroupChat.md ├── GroupChatAdvanced.md ├── GroupChatManagerCreator.md ├── GrowMask.md ├── GrowMaskWithBlur.md ├── GuidedFilter(FaceParsing).md ├── GuidedFilterAlpha.md ├── HDR Effects (SuperBeasts.AI).md ├── HEDPreprocessor.md ├── HEDPreprocessor_Provider_for_SEGS %2F%2FInspire.md ├── HEDPreprocessor_Provider_for_SEGS __Inspire.md ├── HSVThresholdMask.md ├── HaldCLUT .md ├── HighRes-Fix Script.md ├── Hina.PoseEditor3D.md ├── HintImageEnchance.md ├── Human4D_Img2SMPL.md ├── Humans4DLoader.md ├── HyperTile %2F%2FInspire.md ├── HyperTile __Inspire.md ├── HyperTile.md ├── HypernetworkLoader (dirty).md ├── HypernetworkLoader.md ├── ICLightAppply.md ├── IFRNet VFI.md ├── IFUnet VFI.md ├── IF_ChatPrompt.md ├── IF_DisplayText.md ├── IF_ImagePrompt.md ├── IF_PromptMkr.md ├── IF_SaveText.md ├── IG Analyze SSIM.md ├── IG Cross Fade Images.md ├── IG Explorer.md ├── IG Float.md ├── IG Folder.md ├── IG Int.md ├── IG Load Image.md ├── IG Load Images.md ├── IG Multiply.md ├── IG Path Join.md ├── IG String.md ├── IG ZFill.md ├── INPAINT_ApplyFooocusInpaint.md ├── INPAINT_DenoiseToCompositingMask.md ├── INPAINT_InpaintWithModel.md ├── INPAINT_LoadFooocusInpaint.md ├── INPAINT_LoadInpaintModel.md ├── INPAINT_MaskedBlur.md ├── INPAINT_MaskedFill.md ├── INPAINT_VAEEncodeInpaintConditioning.md ├── INTConstant.md ├── IP Adapter Settings (JPS).md ├── IP Adapter Settings Pipe (JPS).md ├── IP Adapter Tiled Settings (JPS).md ├── IP Adapter Tiled Settings Pipe (JPS).md ├── IPA Switch (JPS).md ├── IPAAdapterFaceIDBatch.md ├── IPAdapter.md ├── IPAdapterAdvanced.md ├── IPAdapterBatch.md ├── IPAdapterCombineEmbeds.md ├── IPAdapterCombineParams.md ├── IPAdapterCombineWeights.md ├── IPAdapterEmbeds.md ├── IPAdapterEncoder.md ├── IPAdapterFaceID.md ├── IPAdapterFromParams.md ├── IPAdapterInsightFaceLoader.md ├── IPAdapterLoadEmbeds.md ├── IPAdapterMS.md ├── IPAdapterModelHelper %2F%2FInspire.md ├── IPAdapterModelHelper __Inspire.md ├── IPAdapterModelLoader.md ├── IPAdapterNoise.md ├── IPAdapterPromptScheduleFromWeightsStrategy.md ├── IPAdapterRegionalConditioning.md ├── IPAdapterSaveEmbeds.md ├── IPAdapterStyleComposition.md ├── IPAdapterStyleCompositionBatch.md ├── IPAdapterTiled.md ├── IPAdapterTiledBatch.md ├── IPAdapterUnifiedLoader.md ├── IPAdapterUnifiedLoaderCommunity.md ├── IPAdapterUnifiedLoaderFaceID.md ├── IPAdapterWeights.md ├── IPAdapterWeightsFromStrategy.md ├── ISNetLoader.md ├── ISNetSegment.md ├── If ANY execute A else B.md ├── Image Analyze.md ├── Image Aspect Ratio.md ├── Image Batch Manager (SuperBeasts.AI).md ├── Image Batch.md ├── Image Blank.md ├── Image Blend by Mask.md ├── Image Blend.md ├── Image Blending Mode.md ├── Image Bloom Filter.md ├── Image Bounds to Console.md ├── Image Bounds.md ├── Image Brightness Adjustment [Dream].md ├── Image Canny Filter.md ├── Image Caption.md ├── Image Chromatic Aberration.md ├── Image Color Palette.md ├── Image Color Shift [Dream].md ├── Image Compare (mtb).md ├── Image Comparer (rgthree).md ├── Image Contrast Adjustment [Dream].md ├── Image Crop Face.md ├── Image Crop Location.md ├── Image Crop Square Location.md ├── Image Displacement Warp.md ├── Image Dragan Photography Filter.md ├── Image Edge Detection Filter.md ├── Image Film Grain.md ├── Image Filter Adjustments.md ├── Image Flip.md ├── Image Generate Gradient.md ├── Image Gradient Map.md ├── Image High Pass Filter.md ├── Image History Loader.md ├── Image Input Switch.md ├── Image Inset Crop (rgthree).md ├── Image Levels Adjustment.md ├── Image Load with Metadata (WLSH).md ├── Image Load.md ├── Image Lucy Sharpen.md ├── Image Median Filter.md ├── Image Mix RGB Channels.md ├── Image Monitor Effects Filter.md ├── Image Motion [Dream].md ├── Image Nova Filter.md ├── Image Overlay.md ├── Image Padding.md ├── Image Paste Crop by Location.md ├── Image Paste Crop.md ├── Image Paste Face.md ├── Image Perlin Noise.md ├── Image Perlin Power Fractal.md ├── Image Pixelate.md ├── Image Power Noise.md ├── Image Premultiply (mtb).md ├── Image Prepare Pipe (JPS).md ├── Image Prepare Settings (JPS).md ├── Image Rembg (Remove Background).md ├── Image Remove Background (Alpha).md ├── Image Remove Background Rembg (mtb).md ├── Image Remove Color.md ├── Image Resize Factor (mtb).md ├── Image Resize.md ├── Image Rotate Hue.md ├── Image Rotate.md ├── Image SSAO (Ambient Occlusion).md ├── Image SSDO (Direct Occlusion).md ├── Image Save with Prompt (WLSH).md ├── Image Save with Prompt%2FInfo File (WLSH).md ├── Image Save.md ├── Image Scale By Factor (WLSH).md ├── Image Scale by Shortside (WLSH).md ├── Image Seamless Texture.md ├── Image Select Channel.md ├── Image Select Color.md ├── Image Sequence Blend [Dream].md ├── Image Sequence Loader [Dream].md ├── Image Sequence Saver [Dream].md ├── Image Sequence Tweening [Dream].md ├── Image Shadows and Highlights.md ├── Image Size to Number.md ├── Image Stitch.md ├── Image Style Filter.md ├── Image Switch (JPS).md ├── Image Threshold.md ├── Image Tile Offset (mtb).md ├── Image Tiled.md ├── Image To Mask.md ├── Image Transpose.md ├── Image Voronoi Noise Filter.md ├── Image fDOF Filter.md ├── Image to Latent Mask.md ├── Image to Noise.md ├── Image to Seed.md ├── ImageAlphaComposite.md ├── ImageAndMaskPreview.md ├── ImageApplyChannel.md ├── ImageApplyLUT+.md ├── ImageBatch.md ├── ImageBatchCopy.md ├── ImageBatchFork.md ├── ImageBatchGet.md ├── ImageBatchJoin.md ├── ImageBatchMulti.md ├── ImageBatchMultiple+.md ├── ImageBatchPermute.md ├── ImageBatchRemove.md ├── ImageBatchRepeatInterleaving.md ├── ImageBatchSplitter %2F%2FInspire.md ├── ImageBatchSplitter __Inspire.md ├── ImageBatchTestPattern.md ├── ImageBatchToList.md ├── ImageBlend.md ├── ImageBlur.md ├── ImageBorder.md ├── ImageCASharpening+.md ├── ImageClamp.md ├── ImageColorToMask.md ├── ImageColorTransfer.md ├── ImageCompositeAbsolute.md ├── ImageCompositeAbsoluteByContainer.md ├── ImageCompositeFromMaskBatch+.md ├── ImageCompositeMasked.md ├── ImageCompositeRelative.md ├── ImageCompositeRelativeByContainer.md ├── ImageConcanate.md ├── ImageConstant.md ├── ImageConstantHSV.md ├── ImageContainer.md ├── ImageContainerInheritanceAdd.md ├── ImageContainerInheritanceMax.md ├── ImageContainerInheritanceScale.md ├── ImageContainerInheritanceSum.md ├── ImageCrop+.md ├── ImageCrop.md ├── ImageCropByAlpha.md ├── ImageCropWithBBox(FaceParsing).md ├── ImageDesaturate+.md ├── ImageDirIterator.md ├── ImageDrawArc.md ├── ImageDrawArcByContainer.md ├── ImageDrawChord.md ├── ImageDrawChordByContainer.md ├── ImageDrawEllipse.md ├── ImageDrawEllipseByContainer.md ├── ImageDrawLine.md ├── ImageDrawLineByContainer.md ├── ImageDrawPieslice.md ├── ImageDrawPiesliceByContainer.md ├── ImageDrawPolygon.md ├── ImageDrawRectangle.md ├── ImageDrawRectangleByContainer.md ├── ImageDrawRectangleRounded.md ├── ImageDrawRectangleRoundedByContainer.md ├── ImageDuplicator.md ├── ImageEffectsAdjustment.md ├── ImageEffectsGrayscale.md ├── ImageEffectsLensBokeh.md ├── ImageEffectsLensChromaticAberration.md ├── ImageEffectsLensOpticAxis.md ├── ImageEffectsLensVignette.md ├── ImageEffectsLensZoomBurst.md ├── ImageEffectsNegative.md ├── ImageEffectsSepia.md ├── ImageEnhanceDifference+.md ├── ImageExpandBatch+.md ├── ImageExtractChannel.md ├── ImageFilterBilateralBlur.md ├── ImageFilterBlur.md ├── ImageFilterBoxBlur.md ├── ImageFilterContour.md ├── ImageFilterDetail.md ├── ImageFilterEdgeEnhance.md ├── ImageFilterEdgeEnhanceMore.md ├── ImageFilterEmboss.md ├── ImageFilterFindEdges.md ├── ImageFilterGaussianBlur.md ├── ImageFilterGaussianBlurAdvanced.md ├── ImageFilterMax.md ├── ImageFilterMedianBlur.md ├── ImageFilterMin.md ├── ImageFilterMode.md ├── ImageFilterRank.md ├── ImageFilterSharpen.md ├── ImageFilterSmooth.md ├── ImageFilterSmoothMore.md ├── ImageFilterStackBlur.md ├── ImageFlip+.md ├── ImageFromBatch+.md ├── ImageFromBatch.md ├── ImageFromURL.md ├── ImageGaussianBlur.md ├── ImageGenResolutionFromImage.md ├── ImageGenResolutionFromLatent.md ├── ImageGrabPIL.md ├── ImageGridComposite2x2.md ├── ImageGridComposite3x3.md ├── ImageInsertWithBBox(FaceParsing).md ├── ImageIntensityDetector.md ├── ImageInvert.md ├── ImageListLoader.md ├── ImageListSelect(FaceParsing).md ├── ImageListToBatch+.md ├── ImageListToImageBatch.md ├── ImageLuminanceDetector.md ├── ImageMaskSwitch.md ├── ImageMuxer.md ├── ImageNoiseBeta.md ├── ImageNoiseBinomial.md ├── ImageNoiseBytes.md ├── ImageNoiseGaussian.md ├── ImageNormalize_Neg1_To_1.md ├── ImageOnlyCheckpointLoader.md ├── ImageOnlyCheckpointSave.md ├── ImageOverlay.md ├── ImagePadForOutpaint.md ├── ImagePadForOutpaintMasked.md ├── ImagePadWithBBox(FaceParsing).md ├── ImagePass.md ├── ImagePaste.md ├── ImagePosterize+.md ├── ImageQuantize.md ├── ImageRGBA2RGB.md ├── ImageReceiver.md ├── ImageRemoveBackground+.md ├── ImageRepeat.md ├── ImageResize+.md ├── ImageResize.md ├── ImageResizeCalculator(FaceParsing).md ├── ImageResizeWithBBox(FaceParsing).md ├── ImageScale.md ├── ImageScaleBy.md ├── ImageScaleDown.md ├── ImageScaleDownBy.md ├── ImageScaleDownToSize.md ├── ImageScaleToMegapixels.md ├── ImageScaleToTotalPixels.md ├── ImageSeamCarving+.md ├── ImageSegmentation.md ├── ImageSegmentationCustom.md ├── ImageSegmentationCustomAdvanced.md ├── ImageSelector.md ├── ImageSender.md ├── ImageSharpen.md ├── ImageSize(FaceParsing).md ├── ImageSizeAndBatchSize.md ├── ImageText.md ├── ImageTextMultiline.md ├── ImageTextMultilineOutlined.md ├── ImageTextOutlined.md ├── ImageToImage Pipe (JPS).md ├── ImageToImage Settings (JPS).md ├── ImageToMask.md ├── ImageTransformByNormalizedAmplitude.md ├── ImageTransformCropAbsolute.md ├── ImageTransformCropCorners.md ├── ImageTransformCropRelative.md ├── ImageTransformPaddingAbsolute.md ├── ImageTransformPaddingRelative.md ├── ImageTransformResizeAbsolute.md ├── ImageTransformResizeClip.md ├── ImageTransformResizeRelative.md ├── ImageTransformRotate.md ├── ImageTransformTranspose.md ├── ImageUpscaleWithModel.md ├── ImageUpscaleWithModelBatched.md ├── Images Masks MultiPipe (JPS).md ├── Images as Latents (PPF Noise).md ├── Images to Linear.md ├── Images to RGB.md ├── ImagesFromBatchSchedule.md ├── ImpactAssembleSEGS.md ├── ImpactCombineConditionings.md ├── ImpactCompare.md ├── ImpactConcatConditionings.md ├── ImpactConditionalBranch.md ├── ImpactConditionalBranchSelMode.md ├── ImpactConditionalStopIteration.md ├── ImpactControlBridge.md ├── ImpactControlNetApplyAdvancedSEGS.md ├── ImpactControlNetApplySEGS.md ├── ImpactControlNetClearSEGS.md ├── ImpactConvertDataType.md ├── ImpactDecomposeSEGS.md ├── ImpactDilateMask.md ├── ImpactDilateMaskInSEGS.md ├── ImpactDilate_Mask_SEG_ELT.md ├── ImpactDummyInput.md ├── ImpactEdit_SEG_ELT.md ├── ImpactFloat.md ├── ImpactFrom_SEG_ELT.md ├── ImpactFrom_SEG_ELT_bbox.md ├── ImpactFrom_SEG_ELT_crop_region.md ├── ImpactGaussianBlurMask.md ├── ImpactGaussianBlurMaskInSEGS.md ├── ImpactHFTransformersClassifierProvider.md ├── ImpactIPAdapterApplySEGS.md ├── ImpactIfNone.md ├── ImpactImageBatchToImageList.md ├── ImpactImageInfo.md ├── ImpactInt.md ├── ImpactInversedSwitch.md ├── ImpactIsNotEmptySEGS.md ├── ImpactKSamplerAdvancedBasicPipe.md ├── ImpactKSamplerBasicPipe.md ├── ImpactLatentInfo.md ├── ImpactLogger.md ├── ImpactLogicalOperators.md ├── ImpactMakeImageBatch.md ├── ImpactMakeImageList.md ├── ImpactMakeTileSEGS.md ├── ImpactMinMax.md ├── ImpactNeg.md ├── ImpactNodeSetMuteState.md ├── ImpactQueueTrigger.md ├── ImpactQueueTriggerCountdown.md ├── ImpactRemoteBoolean.md ├── ImpactRemoteInt.md ├── ImpactSEGSClassify.md ├── ImpactSEGSConcat.md ├── ImpactSEGSLabelAssign.md ├── ImpactSEGSLabelFilter.md ├── ImpactSEGSOrderedFilter.md ├── ImpactSEGSPicker.md ├── ImpactSEGSRangeFilter.md ├── ImpactSEGSToMaskBatch.md ├── ImpactSEGSToMaskList.md ├── ImpactScaleBy_BBOX_SEG_ELT.md ├── ImpactSchedulerAdapter.md ├── ImpactSegsAndMask.md ├── ImpactSegsAndMaskForEach.md ├── ImpactSetWidgetValue.md ├── ImpactSimpleDetectorSEGS.md ├── ImpactSimpleDetectorSEGSPipe.md ├── ImpactSimpleDetectorSEGS_for_AD.md ├── ImpactSleep.md ├── ImpactStringSelector.md ├── ImpactSwitch.md ├── ImpactValueReceiver.md ├── ImpactValueSender.md ├── ImpactWildcardEncode.md ├── ImpactWildcardProcessor.md ├── InRange (hsv).md ├── Inference_Core_AIO_Preprocessor.md ├── Inference_Core_AnimalPosePreprocessor.md ├── Inference_Core_AnimeFace_SemSegPreprocessor.md ├── Inference_Core_AnimeLineArtPreprocessor.md ├── Inference_Core_BAE-NormalMapPreprocessor.md ├── Inference_Core_BinaryPreprocessor.md ├── Inference_Core_CannyEdgePreprocessor.md ├── Inference_Core_ColorPreprocessor.md ├── Inference_Core_DWPreprocessor.md ├── Inference_Core_DensePosePreprocessor.md ├── Inference_Core_DepthAnythingPreprocessor.md ├── Inference_Core_DiffusionEdge_Preprocessor.md ├── Inference_Core_FacialPartColoringFromPoseKps.md ├── Inference_Core_FakeScribblePreprocessor.md ├── Inference_Core_HEDPreprocessor.md ├── Inference_Core_HintImageEnchance.md ├── Inference_Core_ImageGenResolutionFromImage.md ├── Inference_Core_ImageGenResolutionFromLatent.md ├── Inference_Core_ImageIntensityDetector.md ├── Inference_Core_ImageLuminanceDetector.md ├── Inference_Core_InpaintPreprocessor.md ├── Inference_Core_LayeredDiffusionApply.md ├── Inference_Core_LayeredDiffusionCondApply.md ├── Inference_Core_LayeredDiffusionCondJointApply.md ├── Inference_Core_LayeredDiffusionDecode.md ├── Inference_Core_LayeredDiffusionDecodeRGBA.md ├── Inference_Core_LayeredDiffusionDecodeSplit.md ├── Inference_Core_LayeredDiffusionDiffApply.md ├── Inference_Core_LayeredDiffusionJointApply.md ├── Inference_Core_LeReS-DepthMapPreprocessor.md ├── Inference_Core_LineArtPreprocessor.md ├── Inference_Core_LineartStandardPreprocessor.md ├── Inference_Core_M-LSDPreprocessor.md ├── Inference_Core_Manga2Anime_LineArt_Preprocessor.md ├── Inference_Core_MaskOptFlow.md ├── Inference_Core_MediaPipe-FaceMeshPreprocessor.md ├── Inference_Core_MeshGraphormer-DepthMapPreprocessor.md ├── Inference_Core_MiDaS-DepthMapPreprocessor.md ├── Inference_Core_MiDaS-NormalMapPreprocessor.md ├── Inference_Core_ModelMergeBlockNumber.md ├── Inference_Core_ModelMergeSDXL.md ├── Inference_Core_ModelMergeSDXLDetailedTransformers.md ├── Inference_Core_ModelMergeSDXLTransformers.md ├── Inference_Core_ModelSamplerTonemapNoiseTest.md ├── Inference_Core_OneFormer-ADE20K-SemSegPreprocessor.md ├── Inference_Core_OneFormer-COCO-SemSegPreprocessor.md ├── Inference_Core_OpenposePreprocessor.md ├── Inference_Core_PiDiNetPreprocessor.md ├── Inference_Core_PixelPerfectResolution.md ├── Inference_Core_PromptExpansion.md ├── Inference_Core_ReferenceOnlySimple.md ├── Inference_Core_RescaleClassifierFreeGuidanceTest.md ├── Inference_Core_SAMPreprocessor.md ├── Inference_Core_SavePoseKpsAsJsonFile.md ├── Inference_Core_ScribblePreprocessor.md ├── Inference_Core_Scribble_XDoG_Preprocessor.md ├── Inference_Core_SemSegPreprocessor.md ├── Inference_Core_ShufflePreprocessor.md ├── Inference_Core_TEEDPreprocessor.md ├── Inference_Core_TilePreprocessor.md ├── Inference_Core_TonemapNoiseWithRescaleCFG.md ├── Inference_Core_UniFormer-SemSegPreprocessor.md ├── Inference_Core_Unimatch_OptFlowPreprocessor.md ├── Inference_Core_Zoe-DepthMapPreprocessor.md ├── Inference_Core_Zoe_DepthAnythingPreprocessor.md ├── Init FizzFrame.md ├── InjectNoiseToLatent.md ├── Inpaint.md ├── InpaintModelConditioning.md ├── InpaintPreprocessor.md ├── InpaintPreprocessor_Provider_for_SEGS %2F%2FInspire.md ├── InpaintPreprocessor_Provider_for_SEGS __Inspire.md ├── Input Trigger.md ├── Input_String to Int Array.md ├── InsertImageBatchByIndexes.md ├── InsertImagesToBatchIndexed.md ├── Inset Image Bounds.md ├── InstanceDiffusionTrackingPrompt.md ├── InstantCameraMotionBrush.md ├── InstantID Mask Prepare Pipe (JPS).md ├── InstantID Mask Prepare Settings (JPS).md ├── InstantID Pipe (JPS).md ├── InstantID Pose Prepare Pipe (JPS).md ├── InstantID Pose Prepare Settings (JPS).md ├── InstantID Settings (JPS).md ├── InstantID Source Prepare Pipe (JPS).md ├── InstantID Source Prepare Settings (JPS).md ├── InstantIDAttentionPatch.md ├── InstantIDFaceAnalysis.md ├── InstantIDModelLoader.md ├── InstantObjectMotionBrush.md ├── InstructPixToPixConditioning.md ├── InstructPixToPixConditioningAdvanced.md ├── Int Input [Dream].md ├── Int Literal.md ├── Int To Bool (mtb).md ├── Int To Number (mtb).md ├── Int to Log Entry [Dream].md ├── Int to String.md ├── Int.md ├── IntNumber.md ├── Integer Switch (JPS).md ├── Integer place counter.md ├── Interpolate Clip Sequential (mtb).md ├── Intrinsic_lora_sampling.md ├── InvCosWave.md ├── InvSinWave.md ├── InvertMask (segment anything).md ├── InvertMask.md ├── IpaConfiguration.md ├── IsMaskEmpty.md ├── Iterative Mixing KSampler Advanced.md ├── Iterative Mixing KSampler(ttulttul%2FComfyUI-Iterative-Mixer).md ├── Iterative Mixing KSampler.md ├── IterativeImageUpscale.md ├── IterativeLatentUpscale.md ├── IterativeMixingSampler.md ├── IterativeMixingScheduler.md ├── IterativeMixingSchedulerAdvanced.md ├── JDC_AutoContrast.md ├── JDC_BlendImages.md ├── JDC_BrownNoise.md ├── JDC_Contrast.md ├── JDC_EqualizeGrey.md ├── JDC_GaussianBlur.md ├── JDC_GreyNoise.md ├── JDC_Greyscale.md ├── JDC_ImageLoader.md ├── JDC_ImageLoaderMeta.md ├── JDC_PinkNoise.md ├── JDC_Plasma.md ├── JDC_PlasmaSampler.md ├── JDC_PowerImage.md ├── JDC_RandNoise.md ├── JDC_ResizeFactor.md ├── JWDatetimeString.md ├── JWFloat.md ├── JWFloatAbsolute.md ├── JWFloatAdd.md ├── JWFloatDiv.md ├── JWFloatMax.md ├── JWFloatMin.md ├── JWFloatMul.md ├── JWFloatSub.md ├── JWFloatToInteger.md ├── JWFloatToString.md ├── JWImageBatchCount.md ├── JWImageContrast.md ├── JWImageExtractFromBatch.md ├── JWImageFlip.md ├── JWImageLevels.md ├── JWImageLoadRGB.md ├── JWImageLoadRGBA.md ├── JWImageLoadRGBIfExists.md ├── JWImageMix.md ├── JWImageResize.md ├── JWImageResizeByFactor.md ├── JWImageResizeByLongerSide.md ├── JWImageResizeByShorterSide.md ├── JWImageResizeToSquare.md ├── JWImageSaturation.md ├── JWImageSaveToPath.md ├── JWImageSequenceExtractFromBatch.md ├── JWImageStackChannels.md ├── JWInteger.md ├── JWIntegerAbsolute.md ├── JWIntegerAdd.md ├── JWIntegerDiv.md ├── JWIntegerMax.md ├── JWIntegerMin.md ├── JWIntegerMul.md ├── JWIntegerSub.md ├── JWIntegerToFloat.md ├── JWIntegerToString.md ├── JWLoadImageSequence.md ├── JWLoadImageSequenceWithStopIndex.md ├── JWLoadImagesFromString.md ├── JWLoopImageSequence.md ├── JWMaskLikeImageSize.md ├── JWMaskResize.md ├── JWMaskSequenceApplyToLatent.md ├── JWMaskSequenceFromMask.md ├── JWMaskSequenceJoin.md ├── JWSaveImageSequence.md ├── JWString.md ├── JWStringConcat.md ├── JWStringGetLine.md ├── JWStringMultiline.md ├── JWStringReplace.md ├── JWStringSplit.md ├── JWStringToFloat.md ├── JWStringToInteger.md ├── JWStringUnescape.md ├── JagsClipseg.md ├── JagsCombineMasks.md ├── JitterImage.md ├── Join Float Lists.md ├── Join Image Lists.md ├── Join XY Inputs of Same Type.md ├── JoinImageWithAlpha.md ├── JoinStrings.md ├── JoinWithDelimiter.md ├── Json comparator [Crystools].md ├── KMeansColor.md ├── KSampler %2F%2FInspire.md ├── KSampler (Efficient).md ├── KSampler (WAS).md ├── KSampler Adv. (Efficient).md ├── KSampler Config (rgthree).md ├── KSampler Cycle.md ├── KSampler Gradually Adding More Denoise (efficient).md ├── KSampler SDXL (Eff.).md ├── KSampler __Inspire.md ├── KSampler.md ├── KSamplerAdvanced %2F%2FInspire.md ├── KSamplerAdvanced (WLSH).md ├── KSamplerAdvanced __Inspire.md ├── KSamplerAdvanced.md ├── KSamplerAdvancedPipe %2F%2FInspire.md ├── KSamplerAdvancedPipe __Inspire.md ├── KSamplerAdvancedProgress %2F%2FInspire.md ├── KSamplerAdvancedProgress __Inspire.md ├── KSamplerAdvancedProvider.md ├── KSamplerPipe %2F%2FInspire.md ├── KSamplerPipe __Inspire.md ├── KSamplerProgress %2F%2FInspire.md ├── KSamplerProgress __Inspire.md ├── KSamplerProvider.md ├── KSamplerSelect.md ├── KSamplerSeq.md ├── KSamplerSeq2.md ├── KSamplerVariationsStochastic+.md ├── KSamplerVariationsWithNoise+.md ├── KarrasScheduler.md ├── KepStringList.md ├── KepStringListFromNewline.md ├── Kep_JoinListAny.md ├── Kep_RepeatList.md ├── Kep_ReverseList.md ├── Kep_VariableImageBuilder.md ├── Keyer.md ├── KfAddCurveToPGroup.md ├── KfAddCurveToPGroupx10.md ├── KfApplyCurveToCond.md ├── KfConditioningAdd.md ├── KfConditioningAddx10.md ├── KfCurveConstant.md ├── KfCurveDraw.md ├── KfCurveFromString.md ├── KfCurveFromYAML.md ├── KfCurvesAdd.md ├── KfCurvesAddx10.md ├── KfCurvesDivide.md ├── KfCurvesMultiply.md ├── KfCurvesMultiplyx10.md ├── KfCurvesSubtract.md ├── KfDebug_Clip.md ├── KfDebug_Cond.md ├── KfDebug_Curve.md ├── KfDebug_Float.md ├── KfDebug_Image.md ├── KfDebug_Int.md ├── KfDebug_Latent.md ├── KfDebug_Model.md ├── KfDebug_Segs.md ├── KfDebug_String.md ├── KfDebug_Vae.md ├── KfDrawSchedule.md ├── KfEvaluateCurveAtT.md ├── KfGetCurveFromPGroup.md ├── KfGetScheduleConditionAtTime.md ├── KfGetScheduleConditionSlice.md ├── KfKeyframedCondition.md ├── KfKeyframedConditionWithText.md ├── KfPGroupCurveAdd.md ├── KfPGroupCurveMultiply.md ├── KfPGroupDraw.md ├── KfPGroupSum.md ├── KfSetCurveLabel.md ├── KfSetKeyframe.md ├── KfSinusoidalAdjustAmplitude.md ├── KfSinusoidalAdjustFrequency.md ├── KfSinusoidalAdjustPhase.md ├── KfSinusoidalAdjustWavelength.md ├── KfSinusoidalEntangledZeroOneFromFrequencyx2.md ├── KfSinusoidalEntangledZeroOneFromFrequencyx3.md ├── KfSinusoidalEntangledZeroOneFromFrequencyx4.md ├── KfSinusoidalEntangledZeroOneFromFrequencyx5.md ├── KfSinusoidalEntangledZeroOneFromFrequencyx6.md ├── KfSinusoidalEntangledZeroOneFromFrequencyx7.md ├── KfSinusoidalEntangledZeroOneFromFrequencyx8.md ├── KfSinusoidalEntangledZeroOneFromFrequencyx9.md ├── KfSinusoidalEntangledZeroOneFromWavelengthx2.md ├── KfSinusoidalEntangledZeroOneFromWavelengthx3.md ├── KfSinusoidalEntangledZeroOneFromWavelengthx4.md ├── KfSinusoidalEntangledZeroOneFromWavelengthx5.md ├── KfSinusoidalEntangledZeroOneFromWavelengthx6.md ├── KfSinusoidalEntangledZeroOneFromWavelengthx7.md ├── KfSinusoidalEntangledZeroOneFromWavelengthx8.md ├── KfSinusoidalEntangledZeroOneFromWavelengthx9.md ├── KfSinusoidalGetAmplitude.md ├── KfSinusoidalGetFrequency.md ├── KfSinusoidalGetPhase.md ├── KfSinusoidalGetWavelength.md ├── KfSinusoidalWithFrequency.md ├── KfSinusoidalWithWavelength.md ├── KuwaharaBlur.md ├── LCMScheduler.md ├── LDSRModelLoader.md ├── LDSRUpscale.md ├── LDSRUpscaler.md ├── LLLiteLoader.md ├── LLMCLIPTextEncode.md ├── LLMCSVReader.md ├── LLMChat.md ├── LLMChatBot.md ├── LLMChatEngine.md ├── LLMChatMessageConcat.md ├── LLMChatMessages.md ├── LLMChatMessagesAdv.md ├── LLMComplete.md ├── LLMDirectoryReader.md ├── LLMDocumentListAppend.md ├── LLMDocxReader.md ├── LLMEpubReader.md ├── LLMFlatReader.md ├── LLMGeminiModel.md ├── LLMGroqModel.md ├── LLMHTMLTagReader.md ├── LLMHWPReader.md ├── LLMHtmlComposer.md ├── LLMHtmlRepair.md ├── LLMIPYNBReader.md ├── LLMImageCaptionReader.md ├── LLMImageTabularChartReader.md ├── LLMImageTextReader.md ├── LLMImageVisionLLMReader.md ├── LLMInputToDocuments.md ├── LLMJsonComposer.md ├── LLMJsonRepair.md ├── LLMLLaVANextImageEvaluator.md ├── LLMLLaVANextModelLoader.md ├── LLMLlamaCPPModel.md ├── LLMMarkdownComposer.md ├── LLMMarkdownReader.md ├── LLMMarkdownRepair.md ├── LLMMboxReader.md ├── LLMMistralAI.md ├── LLMNode.md ├── LLMOpenAIModel.md ├── LLMOpenAIModelOpts.md ├── LLMPDFReader.md ├── LLMPagedCSVReader.md ├── LLMPandasCSVReader.md ├── LLMParquetDatasetSearcher.md ├── LLMPostProcessDocuments.md ├── LLMPptxReader.md ├── LLMPyMuPDFReader.md ├── LLMQueryEngine.md ├── LLMQueryEngineAdv.md ├── LLMQueryEngineAsTool.md ├── LLMRTFReader.md ├── LLMRegexCreator.md ├── LLMRegexRepair.md ├── LLMRssReaderNode.md ├── LLMSaltWebCrawler.md ├── LLMScaleSERPSearch.md ├── LLMSemanticSplitterNodeParser.md ├── LLMSentenceSplitterNodeCreator.md ├── LLMServiceContextAdv.md ├── LLMServiceContextDefault.md ├── LLMSimpleWebPageReader.md ├── LLMSimpleWebPageReaderAdv.md ├── LLMSummaryIndex.md ├── LLMTavilyResearch.md ├── LLMTrafilaturaWebReader.md ├── LLMTrafilaturaWebReaderAdv.md ├── LLMTreeIndex.md ├── LLMUnstructuredReader.md ├── LLMVectorStoreIndex.md ├── LLMVectorStoreIndexAdv.md ├── LLMVideoAudioReader.md ├── LLMXMLReader.md ├── LLMYamlComposer.md ├── LLMYamlRepair.md ├── LMStudioPrompt.md ├── LaMaInpaint.md ├── Laboratory [Dream].md ├── Largest Int (JPS).md ├── Latent Adjustment (PPF Noise).md ├── Latent Batch Comparison Plot.md ├── Latent Batch Statistics Plot.md ├── Latent Batch.md ├── Latent Input Switch.md ├── Latent Lerp (mtb).md ├── Latent Noise Injection.md ├── Latent Size to Number.md ├── Latent Switch (JPS).md ├── Latent Upscale by Factor (WAS).md ├── LatentAdd.md ├── LatentBatch.md ├── LatentBatchSeedBehavior.md ├── LatentBatchSplitter %2F%2FInspire.md ├── LatentBatchSplitter __Inspire.md ├── LatentBlend.md ├── LatentClamp.md ├── LatentComposite.md ├── LatentCompositeMasked.md ├── LatentCrop.md ├── LatentDuplicator.md ├── LatentFlip.md ├── LatentFromBatch.md ├── LatentInterpolate.md ├── LatentKeyframe.md ├── LatentKeyframeBatchedGroup.md ├── LatentKeyframeGroup.md ├── LatentKeyframeTiming.md ├── LatentMultiply.md ├── LatentNormalizeShuffle.md ├── LatentPixelScale.md ├── LatentReceiver.md ├── LatentRotate.md ├── LatentSelector.md ├── LatentSender.md ├── LatentStats.md ├── LatentSubtract.md ├── LatentSwitch.md ├── LatentUpscale.md ├── LatentUpscaleBy.md ├── Latents to CPU (PPF Noise).md ├── LayerColor%3A AutoAdjust.md ├── LayerColor%3A AutoBrightness.md ├── LayerColor%3A Brightness %26 Contrast.md ├── LayerColor%3A Brightness & Contrast.md ├── LayerColor%3A Color of Shadow %26 Highlight.md ├── LayerColor%3A Color of Shadow & Highlight.md ├── LayerColor%3A ColorAdapter.md ├── LayerColor%3A ColorBalance.md ├── LayerColor%3A ColorTemperature.md ├── LayerColor%3A Exposure.md ├── LayerColor%3A Gamma.md ├── LayerColor%3A HSV.md ├── LayerColor%3A LAB.md ├── LayerColor%3A LUT Apply.md ├── LayerColor%3A Levels.md ├── LayerColor%3A RGB.md ├── LayerColor%3A YUV.md ├── LayerFilter%3A AddGrain.md ├── LayerFilter%3A ChannelShake.md ├── LayerFilter%3A ColorMap.md ├── LayerFilter%3A Film.md ├── LayerFilter%3A FilmV2.md ├── LayerFilter%3A GaussianBlur.md ├── LayerFilter%3A HDREffects.md ├── LayerFilter%3A LightLeak.md ├── LayerFilter%3A MotionBlur.md ├── LayerFilter%3A Sharp %26 Soft.md ├── LayerFilter%3A Sharp & Soft.md ├── LayerFilter%3A SkinBeauty.md ├── LayerFilter%3A SoftLight.md ├── LayerFilter%3A WaterColor.md ├── LayerMask%3A BiRefNetUltra.md ├── LayerMask%3A BlendIf Mask.md ├── LayerMask%3A CreateGradientMask.md ├── LayerMask%3A MaskBoxDetect.md ├── LayerMask%3A MaskByColor.md ├── LayerMask%3A MaskByDifferent.md ├── LayerMask%3A MaskEdgeShrink.md ├── LayerMask%3A MaskEdgeUltraDetail V2.md ├── LayerMask%3A MaskEdgeUltraDetail.md ├── LayerMask%3A MaskGradient.md ├── LayerMask%3A MaskGrain.md ├── LayerMask%3A MaskGrow.md ├── LayerMask%3A MaskInvert.md ├── LayerMask%3A MaskMotionBlur.md ├── LayerMask%3A MaskPreview.md ├── LayerMask%3A MaskStroke.md ├── LayerMask%3A MediapipeFacialSegment.md ├── LayerMask%3A PersonMaskUltra V2.md ├── LayerMask%3A PersonMaskUltra.md ├── LayerMask%3A PixelSpread.md ├── LayerMask%3A RemBgUltra.md ├── LayerMask%3A RmBgUltra V2.md ├── LayerMask%3A SegformerB2ClothesUltra.md ├── LayerMask%3A SegmentAnythingUltra V2.md ├── LayerMask%3A SegmentAnythingUltra.md ├── LayerMask%3A Shadow %26 Highlight Mask.md ├── LayerMask%3A Shadow & Highlight Mask.md ├── LayerMask%3A YoloV8Detect.md ├── LayerStyle%3A ColorOverlay V2.md ├── LayerStyle%3A ColorOverlay.md ├── LayerStyle%3A ColorOverlayV2.md ├── LayerStyle%3A DropShadow V2.md ├── LayerStyle%3A DropShadow.md ├── LayerStyle%3A GradientOverlay V2.md ├── LayerStyle%3A GradientOverlay.md ├── LayerStyle%3A InnerGlow V2.md ├── LayerStyle%3A InnerGlow.md ├── LayerStyle%3A InnerShadow V2.md ├── LayerStyle%3A InnerShadow.md ├── LayerStyle%3A OuterGlow V2.md ├── LayerStyle%3A OuterGlow.md ├── LayerStyle%3A Stroke V2.md ├── LayerStyle%3A Stroke.md ├── LayerUtility%3A AddBlindWaterMark.md ├── LayerUtility%3A BatchSelector.md ├── LayerUtility%3A Boolean.md ├── LayerUtility%3A BooleanOperator.md ├── LayerUtility%3A ColorImage V2.md ├── LayerUtility%3A ColorImage.md ├── LayerUtility%3A ColorImageV2.md ├── LayerUtility%3A ColorPicker.md ├── LayerUtility%3A CreateQRCode.md ├── LayerUtility%3A CropBoxResolve.md ├── LayerUtility%3A CropByMask V2.md ├── LayerUtility%3A CropByMask.md ├── LayerUtility%3A DecodeQRCode.md ├── LayerUtility%3A ExtendCanvas.md ├── LayerUtility%3A ExtendCanvasV2.md ├── LayerUtility%3A Float.md ├── LayerUtility%3A GetColorTone.md ├── LayerUtility%3A GetColorToneV2.md ├── LayerUtility%3A GetImageSize.md ├── LayerUtility%3A GradientImage V2.md ├── LayerUtility%3A GradientImage.md ├── LayerUtility%3A HLFrequencyDetailRestore.md ├── LayerUtility%3A ImageAutoCrop V2.md ├── LayerUtility%3A ImageAutoCrop.md ├── LayerUtility%3A ImageBlend V2.md ├── LayerUtility%3A ImageBlend.md ├── LayerUtility%3A ImageBlendAdvance V2.md ├── LayerUtility%3A ImageBlendAdvance.md ├── LayerUtility%3A ImageChannelMerge.md ├── LayerUtility%3A ImageChannelSplit.md ├── LayerUtility%3A ImageCombineAlpha.md ├── LayerUtility%3A ImageHub.md ├── LayerUtility%3A ImageMaskScaleAs.md ├── LayerUtility%3A ImageOpacity.md ├── LayerUtility%3A ImageRemoveAlpha.md ├── LayerUtility%3A ImageRewardFilter.md ├── LayerUtility%3A ImageScaleByAspectRatio V2.md ├── LayerUtility%3A ImageScaleByAspectRatio.md ├── LayerUtility%3A ImageScaleRestore V2.md ├── LayerUtility%3A ImageScaleRestore.md ├── LayerUtility%3A ImageShift.md ├── LayerUtility%3A Integer.md ├── LayerUtility%3A LaMa.md ├── LayerUtility%3A LayerImageTransform.md ├── LayerUtility%3A LayerMaskTransform.md ├── LayerUtility%3A LoadPSD.md ├── LayerUtility%3A NumberCalculator.md ├── LayerUtility%3A PrintInfo.md ├── LayerUtility%3A PromptEmbellish.md ├── LayerUtility%3A PromptTagger.md ├── LayerUtility%3A PurgeVRAM.md ├── LayerUtility%3A QWenImage2Prompt.md ├── LayerUtility%3A RGB Value,md ├── LayerUtility%3A RGB Value.md ├── LayerUtility%3A RestoreCropBox.md ├── LayerUtility%3A SD3NegativeConditioning.md ├── LayerUtility%3A SaveImagePlus.md ├── LayerUtility%3A Seed.md ├── LayerUtility%3A ShowBlindWaterMark.md ├── LayerUtility%3A SimpleTextImage.md ├── LayerUtility%3A TextBox.md ├── LayerUtility%3A TextImage.md ├── LayerUtility%3A TextJoin.md ├── LayerUtility%3A XY to Percent.md ├── LayerUtility%3A%20BatchSelector.md ├── LayeredDiffusionApply.md ├── LayeredDiffusionCondApply.md ├── LayeredDiffusionCondJointApply.md ├── LayeredDiffusionDecode.md ├── LayeredDiffusionDecodeRGBA.md ├── LayeredDiffusionDecodeSplit.md ├── LayeredDiffusionDiffApply.md ├── LayeredDiffusionJointApply.md ├── LeReS-DepthMapPreprocessor.md ├── LeRes_DepthMap_Preprocessor_Provider_for_SEGS %2F%2FInspire.md ├── LeRes_DepthMap_Preprocessor_Provider_for_SEGS __Inspire.md ├── Lerp.md ├── LightingStyler.md ├── LightingStylerAdvanced.md ├── LimitNumber.md ├── LineArtPreprocessor.md ├── LineArt_Preprocessor_Provider_for_SEGS %2F%2FInspire.md ├── LineArt_Preprocessor_Provider_for_SEGS __Inspire.md ├── Linear Cross-Hatch Power Fractal (PPF Noise).md ├── Linear Curve [Dream].md ├── LineartStandardPreprocessor.md ├── List Length.md ├── List of any [Crystools].md ├── List of strings [Crystools].md ├── ListCounter %2F%2FInspire.md ├── ListCounter __Inspire.md ├── ListStringToFloatNode.md ├── LoRA Stack to String converter.md ├── LoRA Stacker.md ├── LoRAScheduler.md ├── Load 64 Encoded Image.md ├── Load Cache.md ├── Load CheckPoint DragNUWA.md ├── Load Face Analysis Model (mtb).md ├── Load Face Enhance Model (mtb).md ├── Load Face Swap Model (mtb).md ├── Load Film Model (mtb).md ├── Load Image Based on Number.md ├── Load Image Batch.md ├── Load Image From Url (mtb).md ├── Load Image Sequence (mtb).md ├── Load Lora.md ├── Load Motion Camera Preset.md ├── Load Motion Traj Preset.md ├── Load MotionBrush From Optical Flow Directory.md ├── Load MotionBrush From Optical Flow Without Model.md ├── Load MotionBrush From Optical Flow.md ├── Load MotionBrush From Tracking Points Without Model.md ├── Load MotionBrush From Tracking Points.md ├── Load Motionctrl Checkpoint.md ├── Load Motionctrl-SVD Camera Preset.md ├── Load Motionctrl-SVD Checkpoint.md ├── Load Pose KeyPoints.md ├── Load Text File.md ├── Load image with metadata [Crystools].md ├── LoadElla.md ├── LoadImage %2F%2FInspire.md ├── LoadImage __Inspire.md ├── LoadImage.md ├── LoadImageAsMaskFromUrl.md ├── LoadImageFromUrl.md ├── LoadImageListFromDir __Inspire.md ├── LoadImageMask.md ├── LoadImagesFromDir __Inspire.md ├── LoadImagesFromDirectory.md ├── LoadInstanceFusersNode.md ├── LoadInstancePositionNetModel.md ├── LoadInstanceScaleUNode.md ├── LoadJsonFromUrl.md ├── LoadLatent.md ├── LoadOOTDPipeline.md ├── LoadPromptsFromDir __Inspire.md ├── LoadPromptsFromFile %2F%2FInspire.md ├── LoadPromptsFromFile __Inspire.md ├── LoadResAdapterNormalization.md ├── LoadSinglePromptFromFile %2F%2FInspire.md ├── LoadSinglePromptFromFile __Inspire.md ├── LoadText%7Cpysssss.md ├── LoadTextFile.md ├── LoadVideo(ArtVentureX%2Fcomfyui-animatediff).md ├── LoadVideoFromUrl.md ├── Log Entry Joiner [Dream].md ├── Log File [Dream].md ├── Logic Boolean Primitive.md ├── Logic Boolean.md ├── Logic Comparison AND.md ├── Logic Comparison OR.md ├── Logic Comparison XOR.md ├── Logic NOT.md ├── Loop.md ├── LoopEnd_IMAGE.md ├── LoopStart_IMAGE.md ├── Lora Input Switch.md ├── Lora Loader (JPS).md ├── Lora Loader Stack (rgthree).md ├── Lora Loader.md ├── LoraBlockInfo %2F%2FInspire.md ├── LoraBlockInfo __Inspire.md ├── LoraInfo.md ├── LoraLoader (dirty).md ├── LoraLoader%7Cpysssss.md ├── LoraLoader.md ├── LoraLoaderBlockWeight %2F%2FInspire.md ├── LoraLoaderBlockWeight __Inspire.md ├── LoraLoaderModelOnly.md ├── LoraNames_.md ├── LoraSyntaxProcessor.md ├── LutsStyler.md ├── LutsStylerAdvanced.md ├── M-LSDPreprocessor.md ├── M2M VFI.md ├── MagicAnimate.md ├── MagicAnimateModelLoader.md ├── Make Image Batch.md ├── Make Interpolation State List.md ├── Make Resized Mask Batch (SuperBeasts.AI).md ├── MakeBasicPipe %2F%2FInspire.md ├── MakeBasicPipe __Inspire.md ├── MakeCircularVAE.md ├── Manga2Anime_LineArt_Preprocessor.md ├── Manga2Anime_LineArt_Preprocessor_Provider_for_SEGS %2F%2FInspire.md ├── Manga2Anime_LineArt_Preprocessor_Provider_for_SEGS __Inspire.md ├── Manual XY Entry Info.md ├── MarigoldDepthEstimation.md ├── MarigoldDepthEstimationVideo.md ├── Mask Arbitrary Region.md ├── Mask Batch Manager (SuperBeasts.AI).md ├── Mask Batch to Mask.md ├── Mask Batch.md ├── Mask By Text.md ├── Mask Ceiling Region.md ├── Mask Crop Dominant Region.md ├── Mask Crop Minority Region.md ├── Mask Crop Region.md ├── Mask Dilate Region.md ├── Mask Dominant Region.md ├── Mask Erode Region.md ├── Mask Fill Holes.md ├── Mask Floor Region.md ├── Mask Gaussian Region.md ├── Mask Invert.md ├── Mask Minority Region.md ├── Mask Morphology.md ├── Mask Paste Region.md ├── Mask Smooth Region.md ├── Mask Switch (JPS).md ├── Mask Threshold Region.md ├── Mask To Image (mtb).md ├── Mask To Region.md ├── MaskBatch+.md ├── MaskBatchMulti.md ├── MaskBlur+.md ├── MaskBoundingBox+.md ├── MaskClamp.md ├── MaskComposite(FaceParsing).md ├── MaskComposite.md ├── MaskDetailerPipe.md ├── MaskExpandBatch+.md ├── MaskFlip+.md ├── MaskFromBatch+.md ├── MaskFromColor+.md ├── MaskFromList+.md ├── MaskFromRGBCMYBW+.md ├── MaskFromSegmentation+.md ├── MaskGrid N KSamplers Advanced.md ├── MaskListComposite(FaceParsing).md ├── MaskListSelect(FaceParsing).md ├── MaskListToMaskBatch.md ├── MaskOptFlow.md ├── MaskOrImageToWeight.md ├── MaskOuterBlur.md ├── MaskPreview+.md ├── MaskSmooth+.md ├── MaskToBBox(FaceParsing).md ├── MaskToImage.md ├── MaskToSEGS.md ├── MaskToSEGS_for_AnimateDiff.md ├── Masks Add.md ├── Masks Combine Batch.md ├── Masks Combine Regions.md ├── Masks Subtract.md ├── MasksToMaskList.md ├── MasqueradeIncrementer.md ├── Match Dimensions (mtb).md ├── MaterialsStyler.md ├── MaterialsStylerAdvanced.md ├── Math Expression (mtb).md ├── MathExpression%7Cpysssss.md ├── MediaPipe-FaceMeshPreprocessor.md ├── MediaPipeFaceMeshDetectorProvider %2F%2FInspire.md ├── MediaPipeFaceMeshDetectorProvider __Inspire.md ├── MediaPipeFaceMeshToSEGS.md ├── MediaPipe_FaceMesh_Preprocessor_Provider_for_SEGS %2F%2FInspire.md ├── MediaPipe_FaceMesh_Preprocessor_Provider_for_SEGS __Inspire.md ├── Merge Latent Batch Gridwise.md ├── MergeLayers.md ├── MergeModels.md ├── MeshGraphormer-DepthMapPreprocessor.md ├── MeshGraphormerDepthMapPreprocessorProvider_for_SEGS %2F%2FInspire.md ├── MeshGraphormerDepthMapPreprocessorProvider_for_SEGS __Inspire.md ├── Metadata comparator [Crystools].md ├── Metadata extractor [Crystools].md ├── MiDaS Depth Approximation.md ├── MiDaS Mask Image.md ├── MiDaS Model Loader.md ├── MiDaS-DepthMapPreprocessor.md ├── MiDaS-NormalMapPreprocessor.md ├── MiDaS_DepthMap_Preprocessor_Provider_for_SEGS %2F%2FInspire.md ├── MiDaS_DepthMap_Preprocessor_Provider_for_SEGS __Inspire.md ├── MicrosoftSpeech_TTS.md ├── Mikey Sampler Base Only Advanced.md ├── Mikey Sampler Base Only.md ├── Mikey Sampler Tiled Base Only.md ├── Mikey Sampler Tiled.md ├── Mikey Sampler.md ├── MikeySamplerTiledAdvanced.md ├── MikeySamplerTiledAdvancedBaseOnly.md ├── MilehighStyler.md ├── MilehighStylerAdvanced.md ├── MirroredImage.md ├── Mix Color By Mask.md ├── Mix Images By Mask.md ├── MixingMaskGenerator.md ├── Model Input Switch.md ├── Model Patch Seamless (mtb).md ├── Model Switch (JPS).md ├── ModelClamp.md ├── ModelCompile+.md ├── ModelMergeAdd.md ├── ModelMergeBlockNumber.md ├── ModelMergeBlocks.md ├── ModelMergeSD1.md ├── ModelMergeSD2.md ├── ModelMergeSDXL.md ├── ModelMergeSDXLDetailedTransformers.md ├── ModelMergeSDXLTransformers.md ├── ModelMergeSimple.md ├── ModelMergeSubtract.md ├── ModelSamplerTonemapNoiseTest.md ├── ModelSamplingContinuousEDM.md ├── ModelSamplingDiscrete.md ├── ModelSamplingStableCascade.md ├── Modelscopet2v.md ├── Modelscopev2v.md ├── MonoMerge.md ├── MoodStyler.md ├── MoodStylerAdvanced.md ├── Moondream Interrogator.md ├── MorphologicOperation.md ├── MorphologicSkeletoning.md ├── Morphology.md ├── MosaicExpandImage.md ├── MotionCLIPTextEncode.md ├── MotionDataVisualizer.md ├── MotionDiffLoader.md ├── MotionDiffSimpleSampler.md ├── Motionctrl Cond.md ├── Motionctrl Sample Simple.md ├── Motionctrl Sample.md ├── Motionctrl-SVD Sample Simple.md ├── MultiplicationNode.md ├── Multiply Float Float (JPS).md ├── Multiply Int Float (JPS).md ├── Multiply Int Int (JPS).md ├── Multiply Integer (WLSH).md ├── NEW_PhotoMaker_Generation.md ├── NNLatentUpscale.md ├── NaiveAutoKMeansColor.md ├── NewLayer.md ├── Noise Control Script.md ├── Noise from Area Palettes [Dream].md ├── Noise from Palette [Dream].md ├── NoiseImage.md ├── NoiseInjectionDetailerHookProvider.md ├── NoiseInjectionHookProvider.md ├── NormalMapSimple.md ├── NormalizedAmplitudeToMask.md ├── NounsStyler.md ├── NounsStylerAdvanced.md ├── Number Counter.md ├── Number Input Condition.md ├── Number Input Switch.md ├── Number Multiple Of.md ├── Number Operation.md ├── Number PI.md ├── Number to Float.md ├── Number to Int.md ├── Number to Seed.md ├── Number to String.md ├── Number to Text.md ├── NumberScaler.md ├── ONNXDetectorProvider.md ├── ONNXDetectorSEGS.md ├── OOTDGenerate.md ├── OffsetImage.md ├── OffsetLatentImage.md ├── OffsetMask.md ├── OffsetMaskByNormalizedAmplitude.md ├── OneButtonArtify.md ├── OneButtonFlufferize.md ├── OneButtonPreset.md ├── OneButtonPrompt.md ├── OneButtonSuperPrompt.md ├── OneFormer-ADE20K-SemSegPreprocessor.md ├── OneFormer-COCO-SemSegPreprocessor.md ├── OobaPrompt.md ├── OpenPose_Preprocessor_Provider_for_SEGS %2F%2FInspire.md ├── OpenPose_Preprocessor_Provider_for_SEGS __Inspire.md ├── OpenposePreprocessor.md ├── OtsuThreshold.md ├── OutlineMask.md ├── Outpaint to Image (WLSH).md ├── OverlayInpaintedImage.md ├── OverlayInpaintedLatent.md ├── PCApplySettings.md ├── PCPromptFromSchedule.md ├── PCScheduleSettings.md ├── PCSplitSampling.md ├── PFG.md ├── Pack SDXL Tuple.md ├── PainterNode.md ├── Palette Color Align [Dream].md ├── Palette Color Shift [Dream].md ├── Parabolize.md ├── Paste By Mask.md ├── PatchModelAddDownscale.md ├── PencilSketch.md ├── PerfectionStyler.md ├── PerfectionStylerAdvanced.md ├── Perlin Power Fractal Latent (PPF Noise).md ├── Perlin Power Fractal Settings (PPF Noise).md ├── PerpNeg.md ├── PerpNegGuider.md ├── PerturbedAttentionGuidance.md ├── PhotoMakerAdapter_Loader_local.md ├── PhotoMakerEncode.md ├── PhotoMakerLoader.md ├── PiDiNetPreprocessor.md ├── Pick From Batch (mtb).md ├── Pipe from any [Crystools].md ├── Pipe to_edit any [Crystools].md ├── Pixel Deflicker (SuperBeasts.AI).md ├── PixelKSampleHookCombine.md ├── PixelKSampleUpscalerProvider.md ├── PixelKSampleUpscalerProviderPipe.md ├── PixelOEPixelize+.md ├── PixelPerfectResolution.md ├── PixelSort.md ├── PixelTiledKSampleUpscalerProvider.md ├── PixelTiledKSampleUpscalerProviderPipe.md ├── Pixelize.md ├── Play Sound (loop) .md ├── Play Sound.md ├── PlaySound%7Cpysssss.md ├── Plot Batch Float (mtb).md ├── PolyexponentialScheduler.md ├── PorterDuffImageComposite.md ├── PortraitMaster.md ├── PortraitMaster_中文版.md ├── PoseNode.md ├── Power KSampler Advanced (PPF Noise).md ├── Power Lora Loader (rgthree).md ├── Power Prompt (rgthree).md ├── Power Prompt - Simple (rgthree).md ├── Power-Law Noise (PPF Noise).md ├── PrepImageForClipVision.md ├── Prepare Image (JPS).md ├── Prepare Image Plus (JPS).md ├── Prepare Image Tiled IPA (JPS).md ├── PrepareImageAndMaskForInpaint.md ├── PrepositionStyler.md ├── PrepositionStylerAdvanced.md ├── PresentString.md ├── PresetRatioSelector.md ├── Preview Chooser Fabric.md ├── Preview Chooser.md ├── Preview from image [Crystools].md ├── Preview from metadata [Crystools].md ├── PreviewBridge.md ├── PreviewBridgeLatent.md ├── PreviewDetailerHookProvider.md ├── PreviewImage.md ├── PreviewLatent.md ├── PreviewLatentAdvanced.md ├── PreviewLatentXL.md ├── PreviewTextNode.md ├── Primitive boolean [Crystools].md ├── Primitive float [Crystools].md ├── Primitive integer [Crystools].md ├── Primitive string [Crystools].md ├── Primitive string multiline [Crystools].md ├── PrintFloats.md ├── PrintSigmas.md ├── Prompt Multiple Styles Selector.md ├── Prompt Styles Selector.md ├── Prompt Weight (WLSH).md ├── Prompt With SDXL.md ├── Prompt With Style V2.md ├── Prompt With Style V3.md ├── Prompt With Style.md ├── PromptBuilder %2F%2FInspire.md ├── PromptBuilder __Inspire.md ├── PromptComposerCustomLists.md ├── PromptComposerEffect.md ├── PromptComposerGrouping.md ├── PromptComposerMerge.md ├── PromptComposerStyler.md ├── PromptComposerTextSingle.md ├── PromptControlSimple.md ├── PromptExtractor %2F%2FInspire.md ├── PromptExtractor __Inspire.md ├── PromptImage.md ├── PromptSchedule.md ├── PromptScheduleEncodeSDXL.md ├── PromptScheduleNodeFlow.md ├── PromptScheduleNodeFlowEnd.md ├── PromptSimplification.md ├── PromptSlide.md ├── PromptToSchedule.md ├── Prompt_Styler.md ├── Prompts Everywhere.md ├── Prune By Mask.md ├── QRCodeGenerator.md ├── Qr Code (mtb).md ├── Quantize.md ├── Quick Resolution Multiply (WLSH).md ├── RAFTEstimate.md ├── RAFTFlowToImage.md ├── RAFTLoadFlowFromEXRChannels.md ├── RGB to HSV.md ├── RGB_Picker.md ├── RIFE VFI.md ├── Random Number.md ├── RandomFloat.md ├── RandomGeneratorForList %2F%2FInspire.md ├── RandomGeneratorForList __Inspire.md ├── RandomInt.md ├── RandomNoise.md ├── RandomPrompt.md ├── Range Float.md ├── Range Integer.md ├── Range(Num Steps) - Float.md ├── Range(Num Steps) - Int.md ├── Range(Step) - Float.md ├── Range(Step) - Int.md ├── Ratio Advanced.md ├── ReActorBuildFaceModel.md ├── ReActorFaceSwap.md ├── ReActorFaceSwapOpt.md ├── ReActorImageDublicator.md ├── ReActorLoadFaceModel.md ├── ReActorMakeFaceModelBatch.md ├── ReActorMaskHelper.md ├── ReActorOptions.md ├── ReActorRestoreFace.md ├── ReActorSaveFaceModel.md ├── Read Playlist (mtb).md ├── RebatchImages.md ├── RebatchLatents.md ├── Rect Grab Cut.md ├── ReencodeLatent.md ├── ReencodeLatentPipe.md ├── Ref_Image_Preprocessing.md ├── ReferenceOnlySimple.md ├── RegionalConditioningColorMask %2F%2FInspire.md ├── RegionalConditioningColorMask __Inspire.md ├── RegionalConditioningSimple %2F%2FInspire.md ├── RegionalConditioningSimple __Inspire.md ├── RegionalIPAdapterColorMask %2F%2FInspire.md ├── RegionalIPAdapterColorMask __Inspire.md ├── RegionalIPAdapterEncodedColorMask %2F%2FInspire.md ├── RegionalIPAdapterEncodedColorMask __Inspire.md ├── RegionalIPAdapterEncodedMask %2F%2FInspire.md ├── RegionalIPAdapterEncodedMask __Inspire.md ├── RegionalIPAdapterMask %2F%2FInspire.md ├── RegionalIPAdapterMask __Inspire.md ├── RegionalPrompt.md ├── RegionalPromptColorMask %2F%2FInspire.md ├── RegionalPromptColorMask __Inspire.md ├── RegionalPromptSimple %2F%2FInspire.md ├── RegionalPromptSimple __Inspire.md ├── RegionalSampler.md ├── RegionalSamplerAdvanced.md ├── RegionalSeedExplorerColorMask %2F%2FInspire.md ├── RegionalSeedExplorerColorMask __Inspire.md ├── RegionalSeedExplorerMask %2F%2FInspire.md ├── RegionalSeedExplorerMask __Inspire.md ├── RelightSimple.md ├── RemBGSession+.md ├── Remap.md ├── RemapBarrelDistortion.md ├── RemapDepth.md ├── RemapFromInsideParabolas.md ├── RemapFromQuadrilateral (homography).md ├── RemapImageRange.md ├── RemapInsideParabolas.md ├── RemapInsideParabolasAdvanced.md ├── RemapMaskRange.md ├── RemapPinch.md ├── RemapRange.md ├── RemapReverseBarrelDistortion.md ├── RemapStretch.md ├── RemapToInnerCylinder.md ├── RemapToOuterCylinder.md ├── RemapToQuadrilateral.md ├── RemapWarpPolar.md ├── RemoveBackendData %2F%2FInspire.md ├── RemoveBackendData __Inspire.md ├── RemoveBackendDataNumberKey %2F%2FInspire.md ├── RemoveBackendDataNumberKey __Inspire.md ├── RemoveControlNet %2F%2FInspire.md ├── RemoveControlNet __Inspire.md ├── RemoveControlNetFromRegionalPrompts %2F%2FInspire.md ├── RemoveControlNetFromRegionalPrompts __Inspire.md ├── RemoveImageFromSEGS.md ├── RemoveLatentMask+.md ├── RemoveNoiseMask.md ├── RenderMultipleSubjectsSMPLMesh.md ├── RenderSMPLMesh.md ├── Render_OpenPose_From_SMPL_Mesh_Multiple_Subjects.md ├── Repeat Into Grid (image).md ├── Repeat Into Grid (latent).md ├── RepeatImageBatch.md ├── RepeatLatentBatch.md ├── Repeater%7Cpysssss.md ├── ReplaceImagesInBatch.md ├── RequestInputs.md ├── ReroutePrimitive%7Cpysssss.md ├── RescaleCFG.md ├── RescaleClassifierFreeGuidanceTest.md ├── Resize Image for SDXL.md ├── ResizeImageMixlab.md ├── ResizeMask.md ├── Resolution Multiply (JPS).md ├── Resolutions by Ratio (WLSH).md ├── Restore Face (mtb).md ├── RetrieveBackendData %2F%2FInspire.md ├── RetrieveBackendData __Inspire.md ├── RetrieveBackendDataNumberKey %2F%2FInspire.md ├── RetrieveBackendDataNumberKey __Inspire.md ├── ReverseImageBatch.md ├── Revision Settings (JPS).md ├── Revision Settings Pipe (JPS).md ├── Robust Video Matting.md ├── RoundMask.md ├── SAG delayed activation.md ├── SAIColorTransfer.md ├── SAIOpenAIAPIWhisper.md ├── SAIPrimitiveConverter.md ├── SAIStringRegexSearchMatch.md ├── SAIStringRegexSearchReplace.md ├── SAIWhisperLoadModel.md ├── SAIWhisperTranscribe.md ├── SALVTON_Apply.md ├── SAM Image Mask.md ├── SAM Model Loader.md ├── SAM Parameters Combine.md ├── SAM Parameters.md ├── SAMDetectorCombined.md ├── SAMDetectorSegmented.md ├── SAMEmbeddingToImage.md ├── SAMLoader.md ├── SAMModelLoader (segment anything).md ├── SAMPreprocessor.md ├── SDTurboScheduler.md ├── SDXL Basic Settings (JPS).md ├── SDXL Basic Settings Pipe (JPS).md ├── SDXL Empty Latent Image (rgthree).md ├── SDXL Empty Latent Image.md ├── SDXL Fundamentals MultiPipe (JPS).md ├── SDXL Power Prompt - Positive (rgthree).md ├── SDXL Power Prompt - Simple _ Negative (rgthree).md ├── SDXL Prompt Handling (JPS).md ├── SDXL Prompt Handling Plus (JPS).md ├── SDXL Prompt Styler (JPS).md ├── SDXL Quick Empty Latent (WLSH).md ├── SDXL Quick Image Scale (WLSH).md ├── SDXL Recommended Resolution Calc (JPS).md ├── SDXL Resolutions (JPS).md ├── SDXL Resolutions (WLSH).md ├── SDXL Settings (JPS).md ├── SDXL Settings Pipe (JPS).md ├── SDXL Steps (WLSH).md ├── SDXLAspectRatioSelector.md ├── SDXLEmptyLatentSizePicker+.md ├── SDXLPromptStyler.md ├── SDXLPromptStylerAdvanced.md ├── SDXLPromptStylerAll.md ├── SDXLPromptStylerHorror.md ├── SDXLPromptStylerMisc.md ├── SDXLPromptStylerbyArtist.md ├── SDXLPromptStylerbyCamera.md ├── SDXLPromptStylerbyComposition.md ├── SDXLPromptStylerbyCyberpunkSurrealism.md ├── SDXLPromptStylerbyDepth.md ├── SDXLPromptStylerbyEnvironment.md ├── SDXLPromptStylerbyFantasySetting.md ├── SDXLPromptStylerbyFilter.md ├── SDXLPromptStylerbyFocus.md ├── SDXLPromptStylerbyImpressionism.md ├── SDXLPromptStylerbyLighting.md ├── SDXLPromptStylerbyMileHigh.md ├── SDXLPromptStylerbyMood.md ├── SDXLPromptStylerbyMythicalCreature.md ├── SDXLPromptStylerbyOriginal.md ├── SDXLPromptStylerbyQuantumRealism.md ├── SDXLPromptStylerbySteamPunkRealism.md ├── SDXLPromptStylerbySubject.md ├── SDXLPromptStylerbySurrealism.md ├── SDXLPromptStylerbyTheme.md ├── SDXLPromptStylerbyTimeofDay.md ├── SDXLPromptStylerbyWyvern.md ├── SDXLPromptbyCelticArt.md ├── SDXLPromptbyContemporaryNordicArt.md ├── SDXLPromptbyFashionArt.md ├── SDXLPromptbyGothicRevival.md ├── SDXLPromptbyIrishFolkArt.md ├── SDXLPromptbyRomanticNationalismArt.md ├── SDXLPromptbySportsArt.md ├── SDXLPromptbyStreetArt.md ├── SDXLPromptbyVikingArt.md ├── SDXLPromptbyWildlifeArt.md ├── SD_4XUpscale_Conditioning.md ├── SEGSDetailer.md ├── SEGSDetailerForAnimateDiff.md ├── SEGSLabelFilterDetailerHookProvider.md ├── SEGSOrderedFilterDetailerHookProvider.md ├── SEGSPaste.md ├── SEGSPreview.md ├── SEGSPreviewCNet.md ├── SEGSRangeFilterDetailerHookProvider.md ├── SEGSSwitch.md ├── SEGSToImageList.md ├── SEGSUpscaler.md ├── SEGSUpscalerPipe.md ├── SMPLLoader.md ├── SMPLShapeParameters.md ├── SRFloatPromptInput.md ├── SRIntPromptInput.md ├── SRStringPromptInput.md ├── STMFNet VFI.md ├── SUPIR_Upscale.md ├── SUPIR_conditioner.md ├── SUPIR_decode.md ├── SUPIR_encode.md ├── SUPIR_first_stage.md ├── SUPIR_model_loader.md ├── SUPIR_model_loader_v2.md ├── SUPIR_sample.md ├── SUPIR_tiles.md ├── SV3D_BatchSchedule.md ├── SV3D_Conditioning.md ├── SVD_img2vid_Conditioning.md ├── SV_random.md ├── SaltAIStableVideoDiffusion.md ├── SaltAdvancedAudioCompressor.md ├── SaltAudio2VHS.md ├── SaltAudioBandpassFilter.md ├── SaltAudioBassBoost.md ├── SaltAudioCompressor.md ├── SaltAudioDeesser.md ├── SaltAudioFade.md ├── SaltAudioFramesyncSchedule.md ├── SaltAudioFrequencyBoost.md ├── SaltAudioFrequencyCutoff.md ├── SaltAudioInversion.md ├── SaltAudioLDM2LoadModel.md ├── SaltAudioLDM2Sampler.md ├── SaltAudioMixer.md ├── SaltAudioNoiseReductionSpectralSubtraction.md ├── SaltAudioNormalize.md ├── SaltAudioPitchShift.md ├── SaltAudioPitchShiftScheduled.md ├── SaltAudioPlaybackRate.md ├── SaltAudioRepeat.md ├── SaltAudioSimpleEcho.md ├── SaltAudioSimpleReverb.md ├── SaltAudioStereoMerge.md ├── SaltAudioStereoSplitter.md ├── SaltAudioStitcher.md ├── SaltAudioTrebleBoost.md ├── SaltAudioTrim.md ├── SaltAudioVisualizer.md ├── SaltBatchCropDataExtractor.md ├── SaltCLIPSegLoader.md ├── SaltCLIPSegMasking.md ├── SaltCLIPTextEncodeSequence.md ├── SaltChangeAudioVolume.md ├── SaltConditioningSetMaskAndCombine.md ├── SaltCropImageLocation.md ├── SaltCyclicalSchedule.md ├── SaltDisplayAny.md ├── SaltFilmicTransitions.md ├── SaltFloatScheduler.md ├── SaltImageBlendingModes.md ├── SaltImageComposite.md ├── SaltImagePasteCrop.md ├── SaltInfo.md ├── SaltInput.md ├── SaltKSamplerSequence.md ├── SaltKeyframeMetrics.md ├── SaltKeyframeScheduler.md ├── SaltKeyframeSchedulerBFN.md ├── SaltKeyframeVisualizer.md ├── SaltLayerExtractor.md ├── SaltLayerScheduler.md ├── SaltListClamp.md ├── SaltListLinearInterpolation.md ├── SaltListOperation.md ├── SaltLoadAudio.md ├── SaltLoadImageZip.md ├── SaltMaskAdaptiveThresholdingRegion.md ├── SaltMaskAdd.md ├── SaltMaskArbitaryRegion.md ├── SaltMaskBilateralFilter.md ├── SaltMaskCeilingRegion.md ├── SaltMaskClipHardeningFilter.md ├── SaltMaskContourExtraction.md ├── SaltMaskCropRegion.md ├── SaltMaskDilateRegion.md ├── SaltMaskDominantRegion.md ├── SaltMaskEdgeDetection.md ├── SaltMaskErodeRegion.md ├── SaltMaskFillRegion.md ├── SaltMaskFloorRegion.md ├── SaltMaskGaussianRegion.md ├── SaltMaskGradientRegion.md ├── SaltMaskHistogramEqualizationRegion.md ├── SaltMaskInvert.md ├── SaltMaskMinorityRegion.md ├── SaltMaskNoiseAddition.md ├── SaltMaskRegionLabeling.md ├── SaltMaskRegionSplit.md ├── SaltMaskSharpeningFilter.md ├── SaltMaskSkeletonization.md ├── SaltMaskSmoothRegion.md ├── SaltMaskSubtract.md ├── SaltMaskThresholdRegion.md ├── SaltMasksToImages.md ├── SaltOPAC.md ├── SaltOPACPerlinSettings.md ├── SaltOutput.md ├── SaltParallaxMotion.md ├── SaltRGBAFromMask.md ├── SaltSaveAudio.md ├── SaltSchedule2ExecSchedule.md ├── SaltScheduleConverter.md ├── SaltScheduleListExponentialFade.md ├── SaltScheduleMerge.md ├── SaltScheduleRandomValues.md ├── SaltScheduleSmoothing.md ├── SaltScheduleSplit.md ├── SaltScheduleVariance.md ├── SaltScheduledBinaryComparison.md ├── SaltScheduledImageAdjust.md ├── SaltScheduledImageDisplacement.md ├── SaltScheduledPerlinPowerFractalNoise.md ├── SaltScheduledShapeTransformation.md ├── SaltScheduledVoronoiNoise.md ├── SaltThresholdSchedule.md ├── Sample Image Area as Palette [Dream].md ├── Sample Image as Palette [Dream].md ├── SampleColorHSV.md ├── Sampler Scheduler Settings (JPS).md ├── Sampler Selector.md ├── SamplerCustom.md ├── SamplerCustomAdvanced.md ├── SamplerDPMAdaptative.md ├── SamplerDPMPP_2M_SDE.md ├── SamplerDPMPP_3M_SDE.md ├── SamplerDPMPP_SDE.md ├── SamplerEulerAncestral.md ├── SamplerLCMAlternative.md ├── SamplerLCMCycle.md ├── SamplerLCMUpscale.md ├── SamplerLMS.md ├── SamplerNames_.md ├── Samples Passthrough (Stat System).md ├── Save Gif (mtb).md ├── Save Image (api).md ├── Save Image Grid (mtb).md ├── Save Image If True.md ├── Save Image Sequence (mtb).md ├── Save Image With Prompt Data.md ├── Save Image w_Metadata.md ├── Save Images Mikey.md ├── Save Images No Display.md ├── Save Images Plus (JPS).md ├── Save Positive Prompt(WLSH).md ├── Save Prompt (WLSH).md ├── Save Prompt%2FInfo (WLSH).md ├── Save Tensors (mtb).md ├── Save Text File.md ├── Save image with extra metadata [Crystools].md ├── SaveAnimatedPNG.md ├── SaveAnimatedWEBP.md ├── SaveImage.md ├── SaveImageExtended.md ├── SaveImageOpenEXR.md ├── SaveImageToLocal.md ├── SaveImageWithAlpha.md ├── SaveLatent.md ├── SaveMetaData.md ├── SavePoseKpsAsJsonFile.md ├── SavePromptToFile.md ├── SaveSMPL.md ├── SaveText%7Cpysssss.md ├── Saw Curve [Dream].md ├── SawtoothWave.md ├── ScaleBatchPromptSchedule.md ├── ScaledSoftControlNetWeights.md ├── ScaledSoftMaskedUniversalWeights.md ├── ScheduleToCond.md ├── ScheduleToModel.md ├── Scheduler Selector.md ├── ScribblePreprocessor.md ├── Scribble_PiDiNet_Preprocessor.md ├── Scribble_XDoG_Preprocessor.md ├── SeamlessClone (simple).md ├── SeamlessClone.md ├── SeamlessTile.md ├── SearchAndReplace.md ├── SeargeAdvancedParameters.md ├── SeargeCheckpointLoader.md ├── SeargeConditionMixing.md ├── SeargeConditioningMuxer2.md ├── SeargeConditioningMuxer5.md ├── SeargeConditioningParameters.md ├── SeargeControlnetAdapterV2.md ├── SeargeControlnetModels.md ├── SeargeCustomAfterUpscaling.md ├── SeargeCustomAfterVaeDecode.md ├── SeargeCustomPromptMode.md ├── SeargeDebugPrinter.md ├── SeargeEnablerInputs.md ├── SeargeFloatConstant.md ├── SeargeFloatMath.md ├── SeargeFloatPair.md ├── SeargeFreeU.md ├── SeargeGenerated1.md ├── SeargeGenerationParameters.md ├── SeargeHighResolution.md ├── SeargeImage2ImageAndInpainting.md ├── SeargeImageAdapterV2.md ├── SeargeImageSave.md ├── SeargeImageSaving.md ├── SeargeInput1.md ├── SeargeInput2.md ├── SeargeInput3.md ├── SeargeInput4.md ├── SeargeInput5.md ├── SeargeInput6.md ├── SeargeInput7.md ├── SeargeIntegerConstant.md ├── SeargeIntegerMath.md ├── SeargeIntegerPair.md ├── SeargeIntegerScaler.md ├── SeargeLatentMuxer3.md ├── SeargeLoraLoader.md ├── SeargeLoras.md ├── SeargeMagicBox.md ├── SeargeModelSelector.md ├── SeargeOperatingMode.md ├── SeargeOutput1.md ├── SeargeOutput2.md ├── SeargeOutput3.md ├── SeargeOutput4.md ├── SeargeOutput5.md ├── SeargeOutput6.md ├── SeargeOutput7.md ├── SeargeParameterProcessor.md ├── SeargePipelineStart.md ├── SeargePipelineTerminator.md ├── SeargePreviewImage.md ├── SeargePromptAdapterV2.md ├── SeargePromptCombiner.md ├── SeargePromptStyles.md ├── SeargePromptText.md ├── SeargeSDXLBasePromptEncoder.md ├── SeargeSDXLImage2ImageSampler.md ├── SeargeSDXLImage2ImageSampler2.md ├── SeargeSDXLPromptEncoder.md ├── SeargeSDXLRefinerPromptEncoder.md ├── SeargeSDXLSampler.md ├── SeargeSDXLSampler2.md ├── SeargeSDXLSamplerV3.md ├── SeargeSamplerInputs.md ├── SeargeSaveFolderInputs.md ├── SeargeSeparator.md ├── SeargeStylePreprocessor.md ├── SeargeTextInputV2.md ├── SeargeUpscaleModelLoader.md ├── SeargeUpscaleModels.md ├── SeargeVAELoader.md ├── Seed (rgthree).md ├── Seed Everywhere.md ├── Seed Generator.md ├── Seed String.md ├── Seed and Int (WLSH).md ├── Seed to Number (WLSH).md ├── Seed.md ├── SeedExplorer %2F%2FInspire.md ├── SeedExplorer __Inspire.md ├── SeedSelector.md ├── Seed_.md ├── SegmDetectorCombined_v2.md ├── SegmDetectorSEGS.md ├── SegsToCombinedMask.md ├── Select Image Indices.md ├── SelfAttentionGuidance.md ├── SemSegPreprocessor.md ├── SendMessage.md ├── Send_To_Editor.md ├── Separate Mask Components.md ├── Sepconv VFI.md ├── SetDefaultImageForSEGS.md ├── SetLatentNoiseMask.md ├── SetRequestStateToComplete.md ├── Sharpen (mtb).md ├── Sharpen.md ├── Show any [Crystools].md ├── Show any to JSON [Crystools].md ├── ShowCachedInfo %2F%2FInspire.md ├── ShowCachedInfo __Inspire.md ├── ShowLayer.md ├── ShowText%7Cpysssss.md ├── ShowTextForGPT.md ├── ShuffleChannels.md ├── ShufflePreprocessor.md ├── Simple Eval Examples.md ├── Simple Pattern Replace (WLSH).md ├── Simple String Combine (WLSH).md ├── Simple String.md ├── SimpleChat.md ├── SimpleMath+.md ├── SinWave.md ├── Sine Curve [Dream].md ├── SineWave.md ├── SingleString.md ├── SizeSelector.md ├── Sleep.md ├── Smart Step (mtb).md ├── Smooth Event Curve [Dream].md ├── SmoothMask.md ├── SmplifyMotionData.md ├── SoftControlNetWeights.md ├── SoftT2IAdapterWeights.md ├── Solarize.md ├── SolidMask.md ├── SomethingToString.md ├── SoundReactive.md ├── SpectreFaceReconLoader.md ├── SpectreImg2SMPL.md ├── SpeechRecognition.md ├── SpeechSynthesis.md ├── SplineEditor.md ├── Split Tracking Points.md ├── SplitBboxes.md ├── SplitImage(esheep).md ├── SplitImage.md ├── SplitImageWithAlpha.md ├── SplitLongMask.md ├── SplitSigmas.md ├── SplitSigmasDenoise.md ├── SquareWave.md ├── StabilityAPI_SD3.md ├── StableCascade_CheckpointLoader %2F%2FInspire.md ├── StableCascade_CheckpointLoader __Inspire.md ├── StableCascade_EmptyLatentImage.md ├── StableCascade_StageB_Conditioning.md ├── StableCascade_StageC_VAEEncode.md ├── StableCascade_SuperResolutionControlnet.md ├── StableSRColorFix.md ├── StableZero123_BatchSchedule.md ├── StableZero123_Conditioning.md ├── StableZero123_Conditioning_Batched.md ├── Stack Images (mtb).md ├── Stack Images.md ├── Stats system [Crystools].md ├── StepsScheduleHookProvider.md ├── String Input [Dream].md ├── String Literal.md ├── String Replace (mtb).md ├── String Tokenizer [Dream].md ├── String to Float.md ├── String to Integer.md ├── String to Log Entry [Dream].md ├── String to Text.md ├── String.md ├── StringConcatenate.md ├── StringConstant.md ├── StringConstantMultiline.md ├── StringFunction%7Cpysssss.md ├── StringSchedule.md ├── StringToInt.md ├── StringToNumber.md ├── Style Conditioner Base Only.md ├── Style Conditioner.md ├── StyleAlignedBatchAlign.md ├── StyleAlignedReferenceSampler.md ├── StyleAlignedSampleReferenceLatents.md ├── StyleModelApply.md ├── StyleModelClamp.md ├── StyleModelLoader.md ├── Styles Loader (mtb).md ├── SubjectStyler.md ├── SubjectStylerAdvanced.md ├── Substract Int Int (JPS).md ├── SubtractMask.md ├── SubtractMaskForEach.md ├── Superprompt.md ├── SvgImage.md ├── Switch any [Crystools].md ├── Switch conditioning [Crystools].md ├── Switch image [Crystools].md ├── Switch latent [Crystools].md ├── Switch mask [Crystools].md ├── Switch string [Crystools].md ├── SwitchByIndex.md ├── TEEDPreprocessor.md ├── TESTNODE_.md ├── TESTNODE_TOKEN.md ├── Tensor Batch to Image.md ├── Text Add Token by Input.md ├── Text Add Tokens.md ├── Text Compare.md ├── Text Concatenate (JPS).md ├── Text Concatenate.md ├── Text Contains.md ├── Text Dictionary Convert.md ├── Text Dictionary Get.md ├── Text Dictionary Keys.md ├── Text Dictionary New.md ├── Text Dictionary To Text.md ├── Text Dictionary Update.md ├── Text File History Loader.md ├── Text Find and Replace Input.md ├── Text Find and Replace by Dictionary.md ├── Text Find and Replace.md ├── Text Input Switch.md ├── Text Input [Dream].md ├── Text List Concatenate.md ├── Text List to Text.md ├── Text List.md ├── Text Load Line From File.md ├── Text Multiline.md ├── Text Parse A1111 Embeddings.md ├── Text Parse Noodle Soup Prompts.md ├── Text Parse Tokens.md ├── Text Prompt (JPS).md ├── Text Prompt Combo (JPS).md ├── Text Random Line.md ├── Text Random Prompt.md ├── Text Shuffle.md ├── Text String Truncate.md ├── Text String.md ├── Text To Image (mtb).md ├── Text to Conditioning.md ├── Text to Console.md ├── Text to Number.md ├── Text to String.md ├── Text2InputOr3rdOption.md ├── TextCombinations.md ├── TextCombinations3.md ├── TextConcat.md ├── TextImage.md ├── TextInput_.md ├── TextPreserve.md ├── TextSplitByDelimiter.md ├── TextToNumber.md ├── ThemeStyler.md ├── ThemeStylerAdvanced.md ├── ThresholdMask.md ├── TilePreprocessor.md ├── TilePreprocessor_Provider_for_SEGS %2F%2FInspire.md ├── TilePreprocessor_Provider_for_SEGS __Inspire.md ├── Tiled KSampler.md ├── Tiled Upscaler Script.md ├── TiledDiffusion.md ├── TiledKSamplerProvider.md ├── Time Seed (JPS).md ├── Time String (WLSH).md ├── TimeofdayStyler.md ├── TimeofdayStylerAdvanced.md ├── TimestepKeyframe.md ├── To Device (mtb).md ├── ToBasicPipe.md ├── ToBinaryMask.md ├── ToColorList.md ├── ToCondList.md ├── ToDetailerPipe.md ├── ToDetailerPipeSDXL.md ├── ToFloatList.md ├── ToIPAdapterPipe %2F%2FInspire.md ├── ToIPAdapterPipe __Inspire.md ├── ToImageList.md ├── ToIntList.md ├── ToLatentList.md ├── ToMaskList.md ├── ToModelList.md ├── ToStringList.md ├── TomePatchModel.md ├── Tonemap.md ├── TonemapNoiseWithRescaleCFG.md ├── Transform Image (mtb).md ├── TransitionBetween2Image.md ├── TransitionFromSize.md ├── TransitionMask+.md ├── TranslateCLIPTextEncode.md ├── TranslateNode.md ├── TransparentImage.md ├── Triangle Curve [Dream].md ├── Triangle Event Curve [Dream].md ├── TriangleWave.md ├── TripoSRModelLoader.md ├── TripoSRSampler.md ├── TripoSRViewer.md ├── True Random.org Number Generator.md ├── TwoAdvancedSamplersForMask.md ├── TwoSamplersForMask.md ├── TwoSamplersForMaskUpscalerProvider.md ├── TwoSamplersForMaskUpscalerProviderPipe.md ├── UNETLoader.md ├── UNetCrossAttentionMultiply.md ├── UNetSelfAttentionMultiply.md ├── UNetTemporalAttentionMultiply.md ├── UltimateSDUpscale.md ├── UltimateSDUpscaleNoUpscale.md ├── UltralyticsDetectorProvider.md ├── UnGridify (image).md ├── UnJitterImage.md ├── UnTonemap.md ├── Unary Image Op.md ├── Unary Mask Op.md ├── Uncrop (mtb).md ├── UniFormer-SemSegPreprocessor.md ├── Unimatch_OptFlowPreprocessor.md ├── Unpack SDXL Tuple.md ├── UnsamplerDetailerHookProvider.md ├── UnsamplerHookProvider.md ├── Unsplash Image (mtb).md ├── UnzipPrompt %2F%2FInspire.md ├── UnzipPrompt __Inspire.md ├── Upscale Model Loader.md ├── Upscale Model Switch.md ├── Upscale Tile Calculator.md ├── Upscale by Factor with Model (WLSH).md ├── UpscaleModelClamp.md ├── UpscaleModelLoader.md ├── VAE Encode for Inpaint w%2FPadding (WLSH).md ├── VAE Input Switch.md ├── VAE Switch (JPS).md ├── VAEDecode.md ├── VAEDecodeTiled.md ├── VAEDecodeTiled_TiledDiffusion.md ├── VAEEncode.md ├── VAEEncodeArgMax.md ├── VAEEncodeBatch.md ├── VAEEncodeForInpaint (WAS).md ├── VAEEncodeForInpaint.md ├── VAEEncodeTiled.md ├── VAEEncodeTiled_TiledDiffusion.md ├── VAELoader.md ├── VAESave.md ├── VHS_BatchManager.md ├── VHS_DuplicateImages.md ├── VHS_DuplicateLatents.md ├── VHS_DuplicateMasks.md ├── VHS_GetImageCount.md ├── VHS_GetLatentCount.md ├── VHS_GetMaskCount.md ├── VHS_LoadAudio.md ├── VHS_LoadAudioUpload.md ├── VHS_LoadImages.md ├── VHS_LoadImagesPath.md ├── VHS_LoadVideo.md ├── VHS_LoadVideoPath.md ├── VHS_MergeImages.md ├── VHS_MergeLatents.md ├── VHS_MergeMasks.md ├── VHS_PruneOutputs.md ├── VHS_SelectEveryNthImage.md ├── VHS_SelectEveryNthLatent.md ├── VHS_SelectEveryNthMask.md ├── VHS_SplitImages.md ├── VHS_SplitLatents.md ├── VHS_SplitMasks.md ├── VHS_VAEDecodeBatched.md ├── VHS_VAEEncodeBatched.md ├── VHS_VideoCombine.md ├── VHS_VideoInfo.md ├── VHS_VideoInfoLoaded.md ├── VHS_VideoInfoSource.md ├── VPScheduler.md ├── VRAM_Debug.md ├── Vae Decode (mtb).md ├── VaeClamp.md ├── ValueSchedule.md ├── VariationNoiseDetailerHookProvider.md ├── VerbingStyler.md ├── VerbingStylerAdvanced.md ├── VidDirIterator.md ├── Video Dump Frames.md ├── VideoLinearCFGGuidance.md ├── VideoTriangleCFGGuidance.md ├── Vignette.md ├── VividSharpen.md ├── WAV Curve [Dream].md ├── WD14Tagger%7Cpysssss.md ├── WeightScheduleConvert.md ├── WeightScheduleExtend.md ├── WidgetToString.md ├── Width_Height Literal.md ├── Wildcard Processor.md ├── WildcardAndLoraSyntaxProcessor.md ├── WildcardEncode %2F%2FInspire.md ├── WildcardEncode __Inspire.md ├── WildcardOobaPrompt.md ├── Write to GIF.md ├── Write to Video.md ├── XY Input%3A Add_Return Noise.md ├── XY Input%3A Aesthetic Score.md ├── XY Input%3A CFG Scale.md ├── XY Input%3A Checkpoint.md ├── XY Input%3A Clip Skip.md ├── XY Input%3A Control Net Plot.md ├── XY Input%3A Control Net.md ├── XY Input%3A Denoise.md ├── XY Input%3A LoRA Plot.md ├── XY Input%3A LoRA Stacks.md ├── XY Input%3A LoRA.md ├── XY Input%3A Lora Block Weight __Inspire.md ├── XY Input%3A Manual XY Entry.md ├── XY Input%3A Prompt S_R.md ├── XY Input%3A Refiner On_Off.md ├── XY Input%3A Sampler_Scheduler.md ├── XY Input%3A Seeds++ Batch.md ├── XY Input%3A Steps.md ├── XY Input%3A VAE.md ├── XY Plot.md ├── XYAny.md ├── XYImage.md ├── YoloSEGdetectionNode.md ├── YoloSegNode.md ├── Yoloworld_ESAM_DetectorProvider_Zho.md ├── Yoloworld_ESAM_Zho.md ├── Yoloworld_ModelLoader_Zho.md ├── ZipPrompt %2F%2FInspire.md ├── ZipPrompt __Inspire.md ├── Zoe-DepthMapPreprocessor.md ├── Zoe_DepthAnythingPreprocessor.md ├── color_drop.md ├── concat.md ├── convertKeyframeKeysToBatchKeys.md ├── easy LLLiteLoader.md ├── easy XYInputs%3A CFG Scale.md ├── easy XYInputs%3A Checkpoint.md ├── easy XYInputs%3A ControlNet.md ├── easy XYInputs%3A Denoise.md ├── easy XYInputs%3A Lora.md ├── easy XYInputs%3A ModelMergeBlocks.md ├── easy XYInputs%3A NegativeCond.md ├── easy XYInputs%3A NegativeCondList.md ├── easy XYInputs%3A PositiveCond.md ├── easy XYInputs%3A PositiveCondList.md ├── easy XYInputs%3A PromptSR.md ├── easy XYInputs%3A Sampler_Scheduler.md ├── easy XYInputs%3A Seeds++ Batch.md ├── easy XYInputs%3A Steps.md ├── easy XYPlot.md ├── easy XYPlotAdvanced.md ├── easy a1111Loader.md ├── easy boolean.md ├── easy cascadeKSampler.md ├── easy cascadeLoader.md ├── easy ckptNames.md ├── easy cleanGpuUsed.md ├── easy clearCacheAll.md ├── easy clearCacheKey.md ├── easy comfyLoader.md ├── easy compare.md ├── easy controlnetLoader.md ├── easy controlnetLoaderADV.md ├── easy controlnetNames.md ├── easy convertAnything.md ├── easy detailerFix.md ├── easy dynamiCrafterLoader.md ├── easy float.md ├── easy fooocusInpaintLoader.md ├── easy fullCascadeKSampler.md ├── easy fullLoader.md ├── easy fullkSampler.md ├── easy globalSeed.md ├── easy hiresFix.md ├── easy humanSegmentation.md ├── easy if.md ├── easy imageChooser.md ├── easy imageColorMatch.md ├── easy imageCount.md ├── easy imageInsetCrop.md ├── easy imageInterrogator.md ├── easy imagePixelPerfect.md ├── easy imageRatio.md ├── easy imageRemBg.md ├── easy imageSave.md ├── easy imageScaleDown.md ├── easy imageScaleDownBy.md ├── easy imageScaleDownToSize.md ├── easy imageSize.md ├── easy imageSizeByLongerSide.md ├── easy imageSizeBySide.md ├── easy imageSplitList.md ├── easy imageSwitch.md ├── easy imageToBase64.md ├── easy imageToMask.md ├── easy imagesSplitImage.md ├── easy injectNoiseToLatent.md ├── easy instantIDApply.md ├── easy instantIDApplyADV.md ├── easy int.md ├── easy ipadapterApply.md ├── easy ipadapterApplyADV.md ├── easy ipadapterApplyEmbeds.md ├── easy ipadapterApplyEncoder.md ├── easy ipadapterApplyFromParams.md ├── easy ipadapterApplyRegional.md ├── easy ipadapterStyleComposition.md ├── easy isSDXL.md ├── easy joinImageBatch.md ├── easy kSampler.md ├── easy kSamplerDownscaleUnet.md ├── easy kSamplerInpainting.md ├── easy kSamplerLayerDiffusion.md ├── easy kSamplerSDTurbo.md ├── easy kSamplerTiled.md ├── easy latentCompositeMaskedWithCond.md ├── easy latentNoisy.md ├── easy loadImageBase64.md ├── easy loraStack.md ├── easy negative.md ├── easy pipeBatchIndex.md ├── easy pipeEdit.md ├── easy pipeIn.md ├── easy pipeOut.md ├── easy pipeToBasicPipe.md ├── easy portraitMaster.md ├── easy poseEditor.md ├── easy positive.md ├── easy preDetailerFix.md ├── easy preMaskDetailerFix.md ├── easy preSampling.md ├── easy preSamplingAdvanced.md ├── easy preSamplingCascade.md ├── easy preSamplingCustom.md ├── easy preSamplingDynamicCFG.md ├── easy preSamplingLayerDiffusion.md ├── easy preSamplingLayerDiffusionADDTL.md ├── easy preSamplingNoiseIn.md ├── easy preSamplingSdTurbo.md ├── easy promptConcat.md ├── easy promptLine.md ├── easy promptList.md ├── easy promptReplace.md ├── easy rangeFloat.md ├── easy rangeInt.md ├── easy samLoaderPipe.md ├── easy seed.md ├── easy showAnything.md ├── easy showLoaderSettingsNames.md ├── easy showSpentTime.md ├── easy showTensorShape.md ├── easy stableDiffusion3API.md ├── easy string.md ├── easy styleAlignedBatchAlign.md ├── easy stylesSelector.md ├── easy sv3dLoader.md ├── easy svdLoader.md ├── easy textSwitch.md ├── easy ultralyticsDetectorPipe.md ├── easy unSampler.md ├── easy wildcards.md ├── easy xyAny.md ├── easy zero123Loader.md ├── mgpt_model_loader.md ├── mgpt_t2m.md ├── promptComposerTextMultiple.md ├── smZ CLIPTextEncode.md ├── smZ Settings.md ├── ttN KSampler_v2.md ├── ttN advanced xyPlot.md ├── ttN concat.md ├── ttN float.md ├── ttN hiresfixScale.md ├── ttN imageOutput.md ├── ttN imageREMBG.md ├── ttN int.md ├── ttN multiModelMerge.md ├── ttN pipe2BASIC.md ├── ttN pipe2DETAILER.md ├── ttN pipeEDIT.md ├── ttN pipeEncodeConcat.md ├── ttN pipeIN.md ├── ttN pipeKSampler.md ├── ttN pipeKSamplerAdvanced.md ├── ttN pipeKSamplerAdvanced_v2.md ├── ttN pipeKSamplerSDXL.md ├── ttN pipeKSamplerSDXL_v2.md ├── ttN pipeKSampler_v2.md ├── ttN pipeLoader.md ├── ttN pipeLoaderSDXL.md ├── ttN pipeLoaderSDXL_v2.md ├── ttN pipeLoader_v2.md ├── ttN pipeLoraStack.md ├── ttN pipeOUT.md ├── ttN seed.md ├── ttN text.md ├── ttN text3BOX_3WAYconcat.md ├── ttN text7BOX_concat.md ├── ttN textDebug.md ├── ttN xyPlot.md ├── unCLIP Checkpoint Loader.md ├── unCLIPCheckpointLoader.md ├── unCLIPConditioning.md └── xy_Tiling_KSampler.md ├── examples └── 2.png ├── logo.png ├── pyproject.toml ├── server ├── __init__.py └── request.py └── web └── comfyui ├── constants.js ├── creatDocsElement.js ├── index.css ├── index.js ├── marked.js ├── settings.js └── utils.js /.cache/.cache_directory: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/.cache/.cache_directory -------------------------------------------------------------------------------- /.github/workflows/publish.yml: -------------------------------------------------------------------------------- 1 | name: Publish to Comfy registry 2 | on: 3 | workflow_dispatch: 4 | push: 5 | branches: 6 | - main 7 | paths: 8 | - "pyproject.toml" 9 | 10 | permissions: 11 | issues: write 12 | 13 | jobs: 14 | publish-node: 15 | name: Publish Custom Node to registry 16 | runs-on: ubuntu-latest 17 | if: ${{ github.repository_owner == 'CavinHuang' }} 18 | steps: 19 | - name: Check out code 20 | uses: actions/checkout@v4 21 | - name: Publish Custom Node 22 | uses: Comfy-Org/publish-node-action@v1 23 | with: 24 | ## Add your own personal access token to your Github Repository secrets and reference it here. 25 | personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }} 26 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | __pycache__ 2 | *.ini 3 | .vscode/ 4 | .idea/ 5 | node_modules/ 6 | .cache/** 7 | !.cache/.cache_directory 8 | 9 | ## Update log 10 | 11 | ### 2024-05-25 12 | -Added a switch in the settings to select whether to display node documents 13 | -Add local document modification function. If you feel there is a problem with the document, you can modify it locally without affecting others 14 | -Added a switch in the settings for whether to participate in co construction. You can choose whether to participate in co construction or not. By default, it will be turned on, and the locally modified records will be recorded in the cloud DB. After review, they will be merged into the main branch 15 | -Add the functions of exporting and importing documents. Exporting documents will export and download locally modified records and documents provided by the warehouse. Importing documents will import the exported documents locally without affecting the documents in the main warehouse. 16 | -Fixed some bugs -------------------------------------------------------------------------------- /__init__.py: -------------------------------------------------------------------------------- 1 | from .server import * 2 | 3 | WEB_DIRECTORY = "./web/comfyui" 4 | NODE_CLASS_MAPPINGS = {} 5 | 6 | __all__ = ['WEB_DIRECTORY', 'NODE_CLASS_MAPPINGS'] 7 | 8 | 9 | MAGENTA = '\033[95m' 10 | RESET = '\033[0m' 11 | print(f"{MAGENTA}==============================================") 12 | print(f"{MAGENTA}[comfyui-nodes-docs]{RESET}Loaded comfyui-nodes-docs plugin") 13 | print(f"{MAGENTA}=============================================={RESET}") 14 | -------------------------------------------------------------------------------- /docs/AB SamplerCustom (experimental).md: -------------------------------------------------------------------------------- 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13 | - anything 14 | - 代表节点可以处理的任何可选输入。这种灵活性使得节点能够处理各种数据类型和结构，从而适应不同的使用场景。 15 | - Comfy dtype: * 16 | - Python dtype: object 17 | 18 | # Output types 19 | 该节点没有输出类型 20 | 21 | 22 | ## Usage tips 23 | - Infra type: `CPU` 24 | - Common nodes: unknown 25 | 26 | 27 | ## Source code 28 | ```python 29 | class AnythingEverywhere(Base): 30 | @classmethod 31 | def INPUT_TYPES(s): 32 | return {"required":{}, 33 | "optional": { "anything" : ("*", {}), }, 34 | "hidden": {"id":"UNIQUE_ID"} } 35 | 36 | def func(self, id, **kwargs): 37 | for key in kwargs: 38 | message(id, kwargs[key],) 39 | return () 40 | 41 | ``` 42 | -------------------------------------------------------------------------------- /docs/Apply Text Template (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Apply Text Template (mtb).md -------------------------------------------------------------------------------- /docs/AreaToMask.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: AreaToMask 3 | - Category: ♾️Mixlab/Mask 4 | - Output node: False 5 | - Repo Ref: https://github.com/shadowcz007/comfyui-mixlab-nodes.git 6 | 7 | 该节点将带有RGBA通道的图像转换为掩码，专注于通过移除透明度和应用切割技术来隔离感兴趣的特定区域。它强调在图像处理领域内对视觉数据进行转换以进行进一步的分析或操作。 8 | 9 | # Input types 10 | ## Required 11 | - RGBA 12 | - RGBA输入至关重要，因为它提供了节点执行转换为掩码所需的原始图像数据。它是节点操作的基础，决定了结果掩码的质量和范围。 13 | - Comfy dtype: image 14 | - Python dtype: PIL.Image 15 | 16 | # Output types 17 | - MASK 18 | - 输出掩码是节点操作的重要产物，代表了输入图像中感兴趣的隔离区域。它作为后续图像处理任务的关键组成部分，使得精确的操作和分析成为可能。 19 | - Comfy dtype: tensor 20 | - Python dtype: torch.Tensor 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class AreaToMask: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'RGBA': ('RGBA',)}} 32 | RETURN_TYPES = ('MASK',) 33 | FUNCTION = 'run' 34 | CATEGORY = '♾️Mixlab/Mask' 35 | INPUT_IS_LIST = False 36 | OUTPUT_IS_LIST = (False,) 37 | 38 | def run(self, RGBA): 39 | mask = AreaToMask_run(RGBA) 40 | return (mask,) 41 | ``` -------------------------------------------------------------------------------- /docs/ArgosTranslateTextNode.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ArgosTranslateTextNode 4 | - Category: AlekPet Nodes/text 5 | - Output node: False 6 | 7 | ArgosTranslateTextNode是一个专门用于文本翻译的节点，它利用Argos Translate库的功能进行语言转换。该节点旨在提供准确高效的语言翻译服务，支持广泛的语言类型。 8 | 9 | # Input types 10 | ## Required 11 | - from_translate 12 | - 指定翻译的源语言代码，决定了文本将从哪种语言进行翻译。 13 | - Comfy dtype: COMBO[STRING] 14 | - Python dtype: str 15 | - to_translate 16 | - 定义翻译的目标语言代码，表示文本将被翻译成哪种语言。 17 | - Comfy dtype: COMBO[STRING] 18 | - Python dtype: str 19 | - text 20 | - 需要翻译的文本，以字符串形式提供。这是将要进行翻译的主要内容。 21 | - Comfy dtype: STRING 22 | - Python dtype: str 23 | 24 | # Output types 25 | - text 26 | - 翻译后的文本，以字符串形式返回。这个输出反映了文本从源语言到目标语言翻译后的结果。 27 | - Comfy dtype: STRING 28 | - Python dtype: str 29 | 30 | 31 | ## Usage tips 32 | - Infra type: `CPU` 33 | - Common nodes: unknown 34 | 35 | 36 | ## Source code 37 | ```python 38 | # Built-in or C extension class, unable to automatically detect source code 39 | ``` 40 | -------------------------------------------------------------------------------- /docs/Auto Pan Equilateral (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Auto Pan Equilateral (mtb).md -------------------------------------------------------------------------------- /docs/BaseModel_Loader_local.md: -------------------------------------------------------------------------------- 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RETURN_TYPES = ("BOOLEAN",) 38 | 39 | RETURN_NAMES = ("BOOLEAN",) 40 | 41 | FUNCTION = "execute" 42 | 43 | CATEGORY = "Logic" 44 | 45 | def execute(self, value): 46 | return (value,) 47 | 48 | ``` 49 | -------------------------------------------------------------------------------- /docs/CLIP +%2F- w%2FText Unified (WLSH).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/CLIP +%2F- w%2FText Unified (WLSH).md -------------------------------------------------------------------------------- /docs/CLIPAttentionMultiply.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/CLIPAttentionMultiply.md -------------------------------------------------------------------------------- /docs/CLIPTextEncodeSDXL+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/CLIPTextEncodeSDXL+.md -------------------------------------------------------------------------------- /docs/CM_BoolToInt.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: BoolToInt 3 | - Category: math/conversion 4 | - Output node: False 5 | - Repo Ref: https://github.com/evanspearman/ComfyMath 6 | 7 | BoolToInt节点旨在将布尔值转换为其整数等价物。在需要布尔状态的数值表示的情况下，例如数学运算或数据处理工作流中，它发挥着关键作用。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 'a'参数是节点期待的布尔输入。它对于转换过程至关重要，因为节点的目的是将这个布尔值转换为整数。输入的布尔特性直接影响输出的整数值，'True'映射为1，'False'映射为0。 13 | - Comfy dtype: BOOL 14 | - Python dtype: bool 15 | 16 | # Output types 17 | - op 18 | - 'op'输出提供了输入布尔值的整数转换。它很重要，因为它代表了节点操作的直接结果，概括了从布尔到整数的转换过程的本质。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class BoolToInt: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls) -> Mapping[str, Any]: 31 | return {'required': {'a': ('BOOL', {'default': False})}} 32 | RETURN_TYPES = ('INT',) 33 | FUNCTION = 'op' 34 | CATEGORY = 'math/conversion' 35 | 36 | def op(self, a: bool) -> tuple[int]: 37 | return (int(a),) 38 | ``` -------------------------------------------------------------------------------- /docs/CM_BreakoutVec3.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: BreakoutVec3 3 | - Category: math/conversion 4 | - Output node: False 5 | - Repo Ref: https://github.com/evanspearman/ComfyMath 6 | 7 | BreakoutVec3节点旨在将三维向量分解为其各个分量。它在需要进一步处理或分析的数学运算中扮演着基础角色，其中向量元素的分离是必要的。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 'a'参数是一个三维向量，节点对其进行操作。它对节点的功能至关重要，因为它是将被分解为其组成部分的输入向量。 13 | - Comfy dtype: VEC3 14 | - Python dtype: Vec3 15 | 16 | # Output types 17 | - result 18 | - BreakoutVec3节点的输出是一个包含输入向量三个独立分量的元组。每个分量是一个浮点数，代表向量的一个维度。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: Tuple[float, float, float] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class BreakoutVec3: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls) -> Mapping[str, Any]: 31 | return {'required': {'a': ('VEC3', {'default': VEC3_ZERO})}} 32 | RETURN_TYPES = ('FLOAT', 'FLOAT', 'FLOAT') 33 | FUNCTION = 'op' 34 | CATEGORY = 'math/conversion' 35 | 36 | def op(self, a: Vec3) -> tuple[float, float, float]: 37 | return (a[0], a[1], a[2]) 38 | ``` -------------------------------------------------------------------------------- /docs/CM_FloatToInt.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: FloatToInt 3 | - Category: math/conversion 4 | - Output node: False 5 | - Repo Ref: https://github.com/evanspearman/ComfyMath 6 | 7 | FloatToInt节点旨在将浮点数转换为它们的整数等价物。在需要将精确的小数值转换为整数的情境中，它扮演着至关重要的角色，促进了需要整数输入的操作。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 'a'参数是要被节点转换为整数的浮点数。它对节点的操作至关重要，因为它直接影响输出，决定了转换过程的起始值。 13 | - Comfy dtype: FLOAT 14 | - Python dtype: float 15 | 16 | # Output types 17 | - result 18 | - 'result'输出是输入浮点数的整数表示。它标志着转换过程的结果，提供了一个可以在随后的基于整数的计算中使用的整数。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class FloatToInt: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls) -> Mapping[str, Any]: 31 | return {'required': {'a': ('FLOAT', {'default': 0.0})}} 32 | RETURN_TYPES = ('INT',) 33 | FUNCTION = 'op' 34 | CATEGORY = 'math/conversion' 35 | 36 | def op(self, a: float) -> tuple[int]: 37 | return (int(a),) 38 | ``` -------------------------------------------------------------------------------- /docs/CM_FloatToNumber.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: FloatToNumber 3 | - Category: math/conversion 4 | - Output node: False 5 | - Repo Ref: https://github.com/evanspearman/ComfyMath 6 | 7 | FloatToNumber节点旨在将浮点数值转换为更通用的数字表示形式。它在数据类型转换中扮演着关键角色，确保了数学或计算工作流程的不同部分之间的兼容性。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 'a'参数是一个浮点数，该节点旨在进行转换。它对节点的操作至关重要，因为它决定了需要转换的输入数据类型。 13 | - Comfy dtype: FLOAT 14 | - Python dtype: float 15 | 16 | # Output types 17 | - result 18 | - 'result'输出是由输入浮点值转换得到的数字。它标志着从特定数据类型成功转换为更通用的数字形式。 19 | - Comfy dtype: NUMBER 20 | - Python dtype: number 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class FloatToNumber: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls) -> Mapping[str, Any]: 31 | return {'required': {'a': ('FLOAT', {'default': 0.0})}} 32 | RETURN_TYPES = ('NUMBER',) 33 | FUNCTION = 'op' 34 | CATEGORY = 'math/conversion' 35 | 36 | def op(self, a: float) -> tuple[number]: 37 | return (a,) 38 | ``` -------------------------------------------------------------------------------- /docs/CM_IntToBool.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: IntToBool 3 | - Category: math/conversion 4 | - Output node: False 5 | - Repo Ref: https://github.com/evanspearman/ComfyMath 6 | 7 | IntToBool节点旨在将整数值转换为布尔表示。在数值的存在与否至关重要的情况下，它作为一个基本的实用工具，从数值数据中抽象出真值概念。此节点在数据类型转换中扮演着关键角色，确保数值输入在布尔上下文中得到适当的解释。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 参数'a'是节点将处理的输入整数。它对节点的操作至关重要，因为它根据值是否非零来确定布尔输出。此参数直接影响节点的执行和生成的布尔值。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - op 18 | - 'op'输出是一个布尔值，表示输入整数的真值。它之所以重要，是因为它在布尔上下文中提供了对数值输入的清晰和直接的解释，这通常在系统的进一步处理或决策中是必需的。 19 | - Comfy dtype: BOOL 20 | - Python dtype: bool 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class IntToBool: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls) -> Mapping[str, Any]: 31 | return {'required': {'a': ('INT', {'default': 0})}} 32 | RETURN_TYPES = ('BOOL',) 33 | FUNCTION = 'op' 34 | CATEGORY = 'math/conversion' 35 | 36 | def op(self, a: int) -> tuple[bool]: 37 | return (a != 0,) 38 | ``` -------------------------------------------------------------------------------- /docs/CM_IntToFloat.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: IntToFloat 3 | - Category: math/conversion 4 | - Output node: False 5 | - Repo Ref: https://github.com/evanspearman/ComfyMath 6 | 7 | IntToFloat节点旨在将整数值转换为其浮点数等价物。它在数值运算中扮演着关键角色，确保在需要准确结果的情况下进行计算时数据类型保持一致，从而保证了计算的精度。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 参数'a'表示要转换为浮点数的整数值。它对节点的操作至关重要，因为它决定了转换过程的起始点。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - result 18 | - 输出'result'是输入整数的浮点表示。它很重要，因为它提供了可以用于后续数值计算的转换后的值。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: float 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class IntToFloat: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls) -> Mapping[str, Any]: 31 | return {'required': {'a': ('INT', {'default': 0})}} 32 | RETURN_TYPES = ('FLOAT',) 33 | FUNCTION = 'op' 34 | CATEGORY = 'math/conversion' 35 | 36 | def op(self, a: int) -> tuple[float]: 37 | return (float(a),) 38 | ``` -------------------------------------------------------------------------------- /docs/CM_IntToNumber.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: IntToNumber 3 | - Category: math/conversion 4 | - Output node: False 5 | - Repo Ref: https://github.com/evanspearman/ComfyMath 6 | 7 | 该节点将整数输入转换为适合进一步处理的数字格式，强调在计算工作流中数据类型转换的重要性。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 参数'a'是一个关键的输入，它为节点提供整数值。正确输入对于节点准确执行转换和影响最终结果至关重要。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - result 18 | - 该节点的输出是输入整数的数字表示形式，对于需要数值数据的后续操作至关重要。 19 | - Comfy dtype: NUMBER 20 | - Python dtype: int 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class IntToNumber: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls) -> Mapping[str, Any]: 31 | return {'required': {'a': ('INT', {'default': 0})}} 32 | RETURN_TYPES = ('NUMBER',) 33 | FUNCTION = 'op' 34 | CATEGORY = 'math/conversion' 35 | 36 | def op(self, a: int) -> tuple[number]: 37 | return (a,) 38 | ``` -------------------------------------------------------------------------------- /docs/CM_NumberToFloat.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: NumberToFloat 3 | - Category: math/conversion 4 | - Output node: False 5 | - Repo Ref: https://github.com/evanspearman/ComfyMath 6 | 7 | NumberToFloat节点旨在将输入数字转换为浮点格式。它在确保不同数据类型之间的数值计算保持精度和一致性中发挥着关键作用。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 'a'参数是节点打算转换为浮点值的输入数字。它对节点的操作至关重要，因为它直接影响输出的数值表示。 13 | - Comfy dtype: NUMBER 14 | - Python dtype: Union[int, float, str] 15 | 16 | # Output types 17 | - result 18 | - 'result'输出是从输入派生的转换后的浮点数。它很重要，因为它代表了节点的主要输出和转换过程的最终结果。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: float 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class NumberToFloat: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls) -> Mapping[str, Any]: 31 | return {'required': {'a': ('NUMBER', {'default': 0.0})}} 32 | RETURN_TYPES = ('FLOAT',) 33 | FUNCTION = 'op' 34 | CATEGORY = 'math/conversion' 35 | 36 | def op(self, a: number) -> tuple[float]: 37 | return (float(a),) 38 | ``` -------------------------------------------------------------------------------- /docs/CM_NumberToInt.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: NumberToInt 3 | - Category: math/conversion 4 | - Output node: False 5 | - Repo Ref: https://github.com/evanspearman/ComfyMath 6 | 7 | NumberToInt节点旨在将数值输入转换为整数形式。在不需要浮点数的精度且更倾向于整数的简单性和效率的场景中，它发挥着关键作用。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 'a'参数是节点将转换为整数的数值输入。它对节点的操作至关重要，因为它决定了转换过程的起点。 13 | - Comfy dtype: NUMBER 14 | - Python dtype: Union[int, float] 15 | 16 | # Output types 17 | - op 18 | - 'op'输出提供了输入参数'a'的整数转换。它很重要，因为它代表了可以用于进一步处理的最终转换值。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class NumberToInt: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls) -> Mapping[str, Any]: 31 | return {'required': {'a': ('NUMBER', {'default': 0.0})}} 32 | RETURN_TYPES = ('INT',) 33 | FUNCTION = 'op' 34 | CATEGORY = 'math/conversion' 35 | 36 | def op(self, a: number) -> tuple[int]: 37 | return (int(a),) 38 | ``` -------------------------------------------------------------------------------- /docs/ClipClamp.md: -------------------------------------------------------------------------------- 1 | --- 2 | tags: 3 | - DataClamp 4 | 5 | # ClipClamp 6 | ## 文档说明 7 | ### 类名：`ClipClamp` 8 | ### 分类：`clamp` 9 | ### 输出节点：`False` 10 | 11 | `ClipClamp` 节点旨在处理 CLIP 数据而不进行修改，作为数据处理管道中的占位符或检查点。 12 | ## 输入类型 13 | ### 必需项 14 | - **`clip`** 15 | - `clip` 参数是此节点处理的 CLIP 数据。它充当直接通过器，确保 CLIP 数据在节点中保持不变。 16 | - Comfy 数据类型：`CLIP` 17 | - Python 数据类型：`tuple` 18 | 19 | ## 输出类型 20 | - **`clip`** 21 | - Comfy 数据类型：`CLIP` 22 | - 返回未修改的 CLIP 数据，维护其完整性以供进一步处理或分析。 23 | - Python 数据类型：`tuple` 24 | 25 | ## 使用提示 26 | - 硬件类型：`CPU` 27 | - 常用节点：未知 28 | 29 | ## 源代码 30 | ```python 31 | class ClipClamp: 32 | def __init__(self): 33 | pass 34 | 35 | @classmethod 36 | def INPUT_TYPES(cls): 37 | return { 38 | "required": { 39 | "clip": ("CLIP",), 40 | }, 41 | } 42 | 43 | RETURN_TYPES = ("CLIP",) 44 | FUNCTION = "node" 45 | CATEGORY = "clamp" 46 | 47 | def node(self, clip): 48 | return (clip,) 49 | ``` -------------------------------------------------------------------------------- /docs/Color Correct (mtb).md: 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表示要以不变形式通过的数据，强调了节点在保持控制网络信息原始状态方面的作用。 16 | - Comfy 数据类型：`CONTROL_NET` 17 | - Python 数据类型：`tuple` 18 | 19 | ## 输出类型 20 | - **`control_net`** 21 | - Comfy 数据类型：`CONTROL_NET` 22 | - 输出未修改的控制网络数据，维持原始输入的完整性。 23 | - Python 数据类型：`tuple` 24 | 25 | ## 使用提示 26 | - 硬件类型：`CPU` 27 | - 常用节点：未知 28 | 29 | ## 源代码 30 | ```python 31 | class ControlNetClamp: 32 | def __init__(self): 33 | pass 34 | 35 | @classmethod 36 | def INPUT_TYPES(cls): 37 | return { 38 | "required": { 39 | "control_net_clamp": ("CONTROL_NET",), 40 | }, 41 | } 42 | 43 | RETURN_TYPES = ("CONTROL_NET",) 44 | FUNCTION = "node" 45 | CATEGORY = "clamp" 46 | 47 | def node(self, control_net_clamp): 48 | return (control_net_clamp,) 49 | ``` -------------------------------------------------------------------------------- /docs/CreateRequestMetadata.md: -------------------------------------------------------------------------------- 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return { 37 | "required": { 38 | "Value": Field.float(), 39 | } 40 | } 41 | 42 | RETURN_TYPES = ("INT",) 43 | FUNCTION = "get_value" 44 | CATEGORY = TREE_CONVERTERS 45 | 46 | def get_value(self, Value): 47 | total = int(math.ceil(Value)) 48 | return (total,) 49 | 50 | ``` 51 | -------------------------------------------------------------------------------- /docs/DF_Floor.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: DF_Floor 4 | - Category: Derfuu_Nodes/Functions/Converters 5 | - Output node: False 6 | 7 | DF_Floor节点设计用于将输入的浮点数向下舍入到最接近的较小整数。这种操作通常被称为对数字进行"向下取整"。 8 | 9 | # Input types 10 | ## Required 11 | - Value 12 | - "Value"参数代表要向下舍入的浮点数。它对确定节点的输出至关重要，因为它直接影响向下取整操作。 13 | - Comfy dtype: FLOAT 14 | - Python dtype: float 15 | 16 | # Output types 17 | - int 18 | - 输出是输入浮点数经过向下取整操作后得到的最接近的较小整数值。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class FloorNode: 31 | def __init__(self) -> None: 32 | pass 33 | 34 | @classmethod 35 | def INPUT_TYPES(cls): 36 | return { 37 | "required": { 38 | "Value": Field.float(), 39 | } 40 | } 41 | 42 | RETURN_TYPES = ("INT",) 43 | FUNCTION = "get_value" 44 | CATEGORY = TREE_CONVERTERS 45 | 46 | def get_value(self, Value): 47 | total = int(math.floor(Value)) 48 | return (total,) 49 | 50 | ``` 51 | -------------------------------------------------------------------------------- /docs/DF_Int_to_Float.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: DF_Int_to_Float 4 | - Category: Derfuu_Nodes/Functions/Converters 5 | - Output node: False 6 | 7 | DF_Int_to_Float节点旨在将整数值转换为浮点数，以便进行需要小数精度的运算。这种转换对于在需要更高精度的计算中使用整数输入非常重要。 8 | 9 | # Input types 10 | ## Required 11 | - Value 12 | - Value参数代表将被转换为浮点数的整数输入。这种转换对于启用整数本身无法适应的精确计算至关重要。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - float 18 | - 输出是输入整数的浮点表示，允许在后续操作中使用小数精度。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: float 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class Int2Float: 31 | def __init__(self): 32 | pass 33 | 34 | @classmethod 35 | def INPUT_TYPES(cls): 36 | return { 37 | "required": { 38 | "Value": Field.int(), 39 | } 40 | } 41 | 42 | RETURN_TYPES = ("FLOAT",) 43 | FUNCTION = "get_value" 44 | CATEGORY = TREE_CONVERTERS 45 | 46 | def get_value(self, Value): 47 | return (float(Value),) 48 | 49 | ``` 50 | -------------------------------------------------------------------------------- /docs/DF_Square_root.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: DF_Square_root 4 | - Category: Derfuu_Nodes/Math 5 | - Output node: False 6 | 7 | SquareRootNode提供了一个数学运算功能，用于计算给定值的平方根，并返回正负两个平方根值。 8 | 9 | # Input types 10 | ## Required 11 | - Value 12 | - 需要计算平方根的输入值。这个值决定了输出的大小。 13 | - Comfy dtype: FLOAT 14 | - Python dtype: float 15 | 16 | # Output types 17 | - float 18 | - 输入值的正负平方根。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: tuple[float, float] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class SquareRootNode: 31 | def __init__(self) -> None: 32 | pass 33 | 34 | @classmethod 35 | def INPUT_TYPES(cls): 36 | return { 37 | "required": { 38 | "Value": Field.float(), 39 | }, 40 | } 41 | 42 | RETURN_TYPES = ("FLOAT", "FLOAT",) 43 | FUNCTION = "sqrt" 44 | CATEGORY = TREE_MATH 45 | 46 | def sqrt(self, Value): 47 | total = math.sqrt(Value) 48 | return (total, -total,) 49 | 50 | ``` 51 | -------------------------------------------------------------------------------- /docs/DF_Text.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: DF_Text 4 | - Category: Derfuu_Nodes/Variables 5 | - Output node: False 6 | 7 | DF_Text节点设计用于捕获和处理文本输入，允许在工作流程中操作和转换字符串。它强调处理文本数据，为以各种形式输入和输出文本提供了一个直观的接口。 8 | 9 | # Input types 10 | ## Required 11 | - Text 12 | - 此参数接受字符串输入，作为节点操作的主要数据。它在节点的文本处理和操作能力中扮演着至关重要的角色。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - string 18 | - 输出处理后的文本作为字符串，反映节点内应用的任何转换或操作。 19 | - Comfy dtype: STRING 20 | - Python dtype: str 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class StringNode: 31 | def __init__(self): 32 | pass 33 | 34 | @classmethod 35 | def INPUT_TYPES(cls): 36 | return { 37 | "required": { 38 | "Text": Field.string(), 39 | } 40 | } 41 | 42 | RETURN_TYPES = ("STRING",) 43 | FUNCTION = "get_value" 44 | CATEGORY = TREE_VARIABLE 45 | 46 | def get_value(self, Text: str) -> tuple[str]: 47 | return (Text,) 48 | 49 | ``` 50 | -------------------------------------------------------------------------------- /docs/DF_Text_Box.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: DF_Text_Box 4 | - Category: Derfuu_Nodes/Variables 5 | - Output node: False 6 | 7 | DF_Text_Box节点设计用于捕获和处理多行文本输入，允许在基于节点的编程环境中处理扩展的文本数据。 8 | 9 | # Input types 10 | ## Required 11 | - Text 12 | - 该参数接受多行文本输入，使节点能够处理和操作跨越多行的文本数据。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - string 18 | - 以字符串形式输出处理后的文本，保持其多行格式。 19 | - Comfy dtype: STRING 20 | - Python dtype: str 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class MultilineStringNode: 31 | def __init__(self): 32 | pass 33 | 34 | @classmethod 35 | def INPUT_TYPES(cls): 36 | return { 37 | "required": { 38 | "Text": Field.string(multiline=True), 39 | } 40 | } 41 | 42 | RETURN_TYPES = ("STRING",) 43 | FUNCTION = "get_value" 44 | CATEGORY = TREE_VARIABLE 45 | 46 | def get_value(self, Text: str) -> tuple[str]: 47 | return (Text,) 48 | 49 | ``` 50 | -------------------------------------------------------------------------------- /docs/DPJinja.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: DPJinja 3 | - Category: Prompt Generation 4 | - Output node: False 5 | - Repo Ref: https://github.com/adieyal/comfyui-dynamicprompts.git 6 | 7 | DPJinja节点旨在使用Jinja模板语法生成提示。它利用JinjaGenerator基于提供的文本和模板配置创建一组提示，提供了一种灵活的方法来生成根据特定需求量身定制的动态提示。 8 | 9 | # Input types 10 | ## Required 11 | - text 12 | - “text”参数是Jinja模板将生成提示的源材料。它至关重要，因为它直接影响生成提示的内容和多样性。 13 | - Comfy dtype: "str" 14 | - Python dtype: str 15 | 16 | # Output types 17 | - prompts 18 | - “prompts”输出是基于输入文本和Jinja模板生成的提示列表。它代表了节点功能的主要结果，包含了提示生成过程的动态特性。 19 | - Comfy dtype: COMBO["str"] 20 | - Python dtype: List[str] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class DPJinja(DPGeneratorNode): 28 | 29 | def generate_prompt(self, text): 30 | prompt_generator = JinjaGenerator() 31 | all_prompts = prompt_generator.generate(text, 1) or [''] 32 | return str(all_prompts[0]) 33 | ``` -------------------------------------------------------------------------------- /docs/DPOutput.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: OutputString 3 | - Category: utils 4 | - Output node: True 5 | - Repo Ref: https://github.com/adieyal/comfyui-dynamicprompts.git 6 | 7 | 该节点旨在处理和输出文本数据，在需要字符串操作或显示的各种工作流中充当重要的实用工具。 8 | 9 | # Input types 10 | ## Required 11 | - text 12 | - 文本输入至关重要，因为它是节点操作的主要数据。它影响节点的整个输出，决定了结果字符串的内容和结构。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - ui.string 18 | - 输出代表处理后的文本数据，是节点对输入字符串操作的结果。它很重要，因为它传达了节点功能的最终结果。 19 | - Comfy dtype: STRING 20 | - Python dtype: str 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class OutputString: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls): 31 | return {'required': {'text': ('STRING', {})}} 32 | RETURN_TYPES = () 33 | FUNCTION = 'output_string' 34 | OUTPUT_NODE = True 35 | CATEGORY = 'utils' 36 | 37 | def output_string(self, string): 38 | return ({'ui': {'string': string}},) 39 | ``` -------------------------------------------------------------------------------- /docs/Debug (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Debug (mtb).md -------------------------------------------------------------------------------- /docs/DebugPrint.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: DebugPrint 4 | - Category: Logic 5 | - Output node: True 6 | 7 | DebugPrint节点是为调试目的而设计的，它允许开发者将任何输入直接打印到控制台。这有助于跟踪和检查通过节点网络的数据流，从而帮助识别和解决问题。 8 | 9 | # Input types 10 | ## Required 11 | - ANY 12 | - 接受任何输入，作为灵活的数据记录通道。这种通用性确保了该节点可以无缝集成到节点网络的各个点，而不会出现兼容性问题。 13 | - Comfy dtype: {} 14 | - Python dtype: Any 15 | 16 | # Output types 17 | 该节点没有输出类型 18 | 19 | 20 | ## Usage tips 21 | - Infra type: `CPU` 22 | - Common nodes: unknown 23 | 24 | 25 | ## Source code 26 | ```python 27 | class DebugPrint: 28 | """ 29 | This node prints the input to the console. 30 | """ 31 | 32 | @classmethod 33 | def INPUT_TYPES(s): 34 | """ 35 | Takes in any input. 36 | 37 | """ 38 | return {"required": {"ANY": (AlwaysEqualProxy({}),)}} 39 | 40 | RETURN_TYPES = () 41 | 42 | OUTPUT_NODE = True 43 | 44 | FUNCTION = "log_input" 45 | 46 | CATEGORY = "Logic" 47 | 48 | def log_input(self, ANY): 49 | print(ANY) 50 | return {} 51 | 52 | ``` 53 | -------------------------------------------------------------------------------- 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DisableNoise节点旨在采样过程中抑制噪声，确保输出不包含任何随机元素。在需要确定性结果的场景中，它作为一个关键组件，提供了生成潜在表示的无噪声路径。 8 | 9 | # Input types 10 | ## Optional 11 | - seed 12 | - seed参数用于初始化噪声生成过程。尽管它不是必需的，但在确保结果的可重复性方面起着关键作用，允许在不同运行中获得一致的结果。 13 | - Comfy dtype: int 14 | - Python dtype: int 15 | 16 | # Output types 17 | - NOISE 18 | - DisableNoise节点的输出是Noise_EmptyNoise类的一个实例，它代表了一个无噪声状态。它标志着生成的潜在图像中没有任何噪声，符合节点提供确定性输出的目的。 19 | - Comfy dtype: Noise_EmptyNoise 20 | - Python dtype: comfy.k_diffusion.sampling.DisableNoise.Noise_EmptyNoise 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class DisableNoise: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {}} 32 | RETURN_TYPES = ('NOISE',) 33 | FUNCTION = 'get_noise' 34 | CATEGORY = 'sampling/custom_sampling/noise' 35 | 36 | def get_noise(self): 37 | return (Noise_EmptyNoise(),) 38 | ``` -------------------------------------------------------------------------------- /docs/DrawText+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/DrawText+.md -------------------------------------------------------------------------------- /docs/Export With Ffmpeg (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Export With Ffmpeg (mtb).md -------------------------------------------------------------------------------- /docs/ExtendColorList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ExtendColorList 4 | - Category: Bmad/Lists/Extend 5 | - Output node: False 6 | 7 | ExtendColorList 节点旨在通过添加更多颜色值来扩展现有的颜色列表。这一功能在需要动态扩展颜色选择的场景中至关重要，例如在图像处理、设计应用或数据可视化任务中，更广泛的调色板可能会增强输出的美观性或信息价值。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 指定要添加到现有颜色列表中的颜色值数量。此参数决定了调色板扩展的规模。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - color 18 | - 扩展后的颜色列表，将原有的颜色列表与新添加的颜色值相结合。这个输出对于后续需要更广泛或修改后的调色板的应用来说意义重大。 19 | - Comfy dtype: COLOR 20 | - Python dtype: List[str] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ExtendColorList(metaclass=ExtendListMeta): TYPE = "COLOR" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ExtendCondList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ExtendCondList 4 | - Category: Bmad/Lists/Extend 5 | - Output node: False 6 | 7 | ExtendCondList节点的作用是扩展一个条件列表。它允许向现有的列表中添加新的条件元素，从而实现动态扩展用于各种计算模型或过程中的条件数据。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 'inputs_len'参数表示要添加到现有列表中的条件元素的数量。它在扩展列表容量和纳入新的条件数据方面起着至关重要的作用，可以显著影响节点的执行和结果。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - conditioning 18 | - 该节点输出一个扩展后的条件元素列表，将新添加的样本整合到现有列表中。 19 | - Comfy dtype: CONDITIONING 20 | - Python dtype: List[Conditioning] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ExtendCondList(metaclass=ExtendListMeta): TYPE = "CONDITIONING" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ExtendFloatList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ExtendFloatList 4 | - Category: Bmad/Lists/Extend 5 | - Output node: False 6 | - Repo Ref: https://github.com/bmad4ever/ComfyUI-Bmad-Custom-Nodes 7 | 8 | ExtendFloatList节点旨在将多个浮点数列表连接成一个单一的扩展列表。这一功能在需要聚合来自不同来源的数据的场景中特别有用，能够实现对数值数据集合的高效、流畅处理。 9 | 10 | # Input types 11 | ## Required 12 | - inputs_len 13 | - 指定要连接的浮点数列表的数量。这个参数决定了有多少个列表将被合并到扩展列表中，从而影响节点的执行过程和最终生成的列表大小。 14 | - Comfy dtype: INT 15 | - Python dtype: Tuple[int] 16 | 17 | # Output types 18 | - float 19 | - 由所有输入列表聚合而成的连接浮点数列表。 20 | - Comfy dtype: FLOAT 21 | - Python dtype: List[float] 22 | 23 | 24 | ## Usage tips 25 | - Infra type: `CPU` 26 | - Common nodes: unknown 27 | 28 | 29 | ## Source code 30 | ```python 31 | class ExtendFloatList(metaclass=ExtendListMeta): TYPE = "FLOAT" 32 | 33 | ``` 34 | -------------------------------------------------------------------------------- /docs/ExtendImageList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ExtendImageList 4 | - Category: Bmad/Lists/Extend 5 | - Output node: False 6 | 7 | ExtendImageList节点旨在向现有图像列表中添加新的图像。它专注于将多个图像资源聚合到一个综合集合中，便于进行需要批量图像数据管理的操作。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 'inputs_len'参数对于定义扩展前集合的起始点至关重要。它代表了要扩展的初始图像数量，为扩展过程奠定了基础。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - image 18 | - 'image'参数代表扩展过程后的最终图像集合。它包含了原始图像和新添加的图像，为进一步处理提供了一个统一的集合。 19 | - Comfy dtype: IMAGE 20 | - Python dtype: List[torch.Tensor] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ExtendImageList(metaclass=ExtendListMeta): TYPE = "IMAGE" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ExtendIntList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ExtendIntList 4 | - Category: Bmad/Lists/Extend 5 | - Output node: False 6 | 7 | ExtendIntList节点旨在将多个整数列表串联成单个扩展列表。这一功能在需要汇总来自不同来源的整数数据的场景中特别有用，可以实现无缝的数据操作和分析。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 指定要连接的整数列表的数量。该参数决定了将有多少个列表被合并到扩展列表中。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - int 18 | - 由所有输入列表汇总而成的连接整数列表。 19 | - Comfy dtype: INT 20 | - Python dtype: List[int] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ExtendIntList(metaclass=ExtendListMeta): TYPE = "INT" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ExtendLatentList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ExtendLatentList 4 | - Category: Bmad/Lists/Extend 5 | - Output node: False 6 | 7 | ExtendLatentList节点旨在扩展潜在表示的列表。它能够将额外的潜在向量聚合到现有集合中，从而实现潜在数据集的扩展，以便进行进一步的处理或分析。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 'inputs_len'参数代表要扩展的初始潜在向量集。它在确定新潜在向量将被添加到的基础集合方面起着至关重要的作用，影响着节点的执行过程和最终的扩展列表结果。 13 | - Comfy dtype: INT 14 | - Python dtype: List[torch.Tensor] 15 | 16 | # Output types 17 | - latent 18 | - 'latent'输出参数代表扩展后的潜在向量列表。它表示在添加新向量后得到的增强潜在表示集合。 19 | - Comfy dtype: LATENT 20 | - Python dtype: List[torch.Tensor] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ExtendLatentList(metaclass=ExtendListMeta): TYPE = "LATENT" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ExtendMaskList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ExtendMaskList 4 | - Category: Bmad/Lists/Extend 5 | - Output node: False 6 | 7 | ExtendMaskList节点旨在扩展掩码列表，允许将多个掩码元素聚合到一个综合列表中。这一功能对于需要同时操作或分析多个掩码的操作至关重要，为批量处理掩码数据提供了一种简化的方法。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 'inputs_len'参数代表要扩展的掩码元素集合。它在节点操作中起着关键作用，作为主要的数据输入，节点随后会处理这些输入以生成扩展后的掩码列表。 13 | - Comfy dtype: INT 14 | - Python dtype: List[torch.Tensor] 15 | 16 | # Output types 17 | - mask 18 | - 输出是一个扩展后的掩码元素列表，整合成单一实体以便于进一步处理或分析。 19 | - Comfy dtype: MASK 20 | - Python dtype: List[torch.Tensor] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ExtendMaskList(metaclass=ExtendListMeta): TYPE = "MASK" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ExtendModelList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ExtendModelList 4 | - Category: Bmad/Lists/Extend 5 | - Output node: False 6 | 7 | ExtendModelList节点旨在将多个模型列表聚合成一个单一的扩展列表。这一功能对于需要合并模型列表以形成全面的模型集合以供进一步处理或分析的场景至关重要。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 指定要合并的模型列表数量。它决定了有多少个列表将被聚合到扩展列表中。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - model 18 | - 合并后的模型列表，将所有输入的模型列表聚合成一个单一的扩展集合。 19 | - Comfy dtype: MODEL 20 | - Python dtype: List[torch.nn.Module] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ExtendModelList(metaclass=ExtendListMeta): TYPE = "MODEL" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ExtendStringList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ExtendStringList 4 | - Category: Bmad/Lists/Extend 5 | - Output node: False 6 | - Repo Ref: https://github.com/bmad4ever/Bmad-Comfy-Nodes 7 | 8 | ExtendStringList节点的设计目的是将多个字符串列表连接成一个单一的、扩展的列表。这个节点在需要聚合来自不同来源的字符串数据的场景中特别有用，它可以促进涉及集体字符串数据集操作或分析的任务。 9 | 10 | # Input types 11 | ## Required 12 | - inputs_len 13 | - 指定要连接的字符串列表的数量。这个参数决定了将有多少个字符串列表被合并到扩展列表中。 14 | - Comfy dtype: INT 15 | - Python dtype: int 16 | 17 | # Output types 18 | - string 19 | - 连接所有提供的字符串列表后的结果列表。这个列表按照各自的顺序包含了所有输入列表中的字符串。 20 | - Comfy dtype: STRING 21 | - Python dtype: List[str] 22 | 23 | 24 | ## Usage tips 25 | - Infra type: `CPU` 26 | - Common nodes: unknown 27 | 28 | 29 | ## Source code 30 | ```python 31 | class ExtendStringList(metaclass=ExtendListMeta): TYPE = "STRING" 32 | 33 | ``` 34 | -------------------------------------------------------------------------------- /docs/ExtractKeyframes+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/ExtractKeyframes+.md -------------------------------------------------------------------------------- /docs/Face Swap (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Face Swap (mtb).md -------------------------------------------------------------------------------- /docs/FakeScribblePreprocessor_Provider_for_SEGS %2F%2FInspire.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: FakeScribblePreprocessor_Provider_for_SEGS 3 | - Category: Image Processing 4 | - Output node: False 5 | - Repo Ref: https://github.com/ltdrdata/ComfyUI-Inspire-Pack.git 6 | 7 | FakeScribblePreprocessor_Provider_for_SEGS 节点旨在通过应用模拟涂鸦的预处理步骤来增强图像分割任务。该节点利用 HED（全卷积边缘检测）算法的能力来创建提示图像，这有助于分割过程。它特别适用于通过为分割模型提供额外的上下文信息来生成详细和清晰的分割图。 8 | 9 | # Input types 10 | ## Required 11 | - safe 12 | - 'safty' 参数决定是否应该在应用预处理时采取安全措施，以防止潜在的数据损坏或丢失。这对于确保预处理阶段输入数据的完整性至关重要。 13 | - Comfy dtype: bool 14 | - Python dtype: bool 15 | 16 | # Output types 17 | - result 18 | - FakeScribblePreprocessor_Provider_for_SEGS 节点的输出是经过预处理步骤的图像。这个图像可以直接用作分割模型的输入，增强模型产生准确分割的能力。 19 | - Comfy dtype: image 20 | - Python dtype: PIL.Image or numpy.ndarray 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class FakeScribblePreprocessor_Provider_for_SEGS(HEDPreprocessor_Provider_for_SEGS): 28 | 29 | def doit(self, safe): 30 | obj = HED_Preprocessor_wrapper(safe, 'FakeScribblePreprocessor') 31 | return (obj,) 32 | ``` -------------------------------------------------------------------------------- /docs/FakeScribblePreprocessor_Provider_for_SEGS __Inspire.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FakeScribblePreprocessor_Provider_for_SEGS __Inspire 4 | - Category: InspirePack/SEGS/ControlNet 5 | - Output node: False 6 | 7 | 该节点为SEGS (语义分割模型)提供了一个预处理步骤,通过应用伪涂鸦效果。它旨在为进一步处理准备图像,通过增强或修改图像特征以更好地满足SEGS模型的要求。 8 | 9 | # Input types 10 | ## Required 11 | - safe 12 | - 该参数决定是否以"安全"模式执行预处理。它会影响执行过程和结果,可能会改变处理的强度或使用的方法。 13 | - Comfy dtype: BOOLEAN 14 | - Python dtype: bool 15 | 16 | # Output types 17 | - segs_preprocessor 18 | - 输出一个经过预处理的对象,专门用于SEGS模型,具有伪涂鸦效果。 19 | - Comfy dtype: SEGS_PREPROCESSOR 20 | - Python dtype: HED_Preprocessor_wrapper 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class FakeScribblePreprocessor_Provider_for_SEGS(HEDPreprocessor_Provider_for_SEGS): 31 | def doit(self, safe): 32 | obj = HED_Preprocessor_wrapper(safe, "FakeScribblePreprocessor") 33 | return (obj, ) 34 | 35 | ``` 36 | -------------------------------------------------------------------------------- /docs/Filter Z (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Filter Z (mtb).md -------------------------------------------------------------------------------- /docs/Fit Number (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Fit Number (mtb).md -------------------------------------------------------------------------------- /docs/Float To Floats (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Float To Floats (mtb).md -------------------------------------------------------------------------------- /docs/Float To Number (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Float To Number (mtb).md -------------------------------------------------------------------------------- /docs/Floats To Float (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Floats To Float (mtb).md -------------------------------------------------------------------------------- /docs/Floats To Ints (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Floats To Ints (mtb).md -------------------------------------------------------------------------------- /docs/Font.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: FontInput 3 | - Category: ♾️Mixlab/Utils 4 | - Output node: False 5 | - Repo Ref: https://github.com/shadowcz007/comfyui-mixlab-nodes.git 6 | 7 | 该节点根据指定的字体名称检索字体文件，为在各种图形或文本处理任务中访问和使用字体提供了一种简化的方法。 8 | 9 | # Input types 10 | ## Required 11 | - font 12 | - ‘font’参数至关重要，因为它标识了系统中要使用的具体字体。它直接影响节点的操作和结果输出，确保将正确的字体应用到当前任务中。 13 | - Comfy dtype: list 14 | - Python dtype: list 15 | 16 | # Output types 17 | - font_file 18 | - 输出‘font_file’代表与输入字体参数相关的检索到的字体文件，这对于应用程序中进一步的图形或文本处理至关重要。 19 | - Comfy dtype: list 20 | - Python dtype: list 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class FontInput: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'font': (list(font_files.keys()),)}} 32 | RETURN_TYPES = ('STRING',) 33 | FUNCTION = 'run' 34 | CATEGORY = '♾️Mixlab/Utils' 35 | INPUT_IS_LIST = False 36 | OUTPUT_IS_LIST = (False,) 37 | 38 | def run(self, font): 39 | return (font_files[font],) 40 | ``` -------------------------------------------------------------------------------- /docs/FromListGet1Color.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGet1Color 4 | - Category: Bmad/Lists/Get1 5 | - Output node: False 6 | 7 | FromListGet1Color 节点设计用于从颜色列表中根据指定索引检索单个颜色值。它简化了访问列表元素的过程，允许以用户友好的方式直接检索颜色信息。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 此参数表示将从中检索单个颜色的颜色列表。该列表必须包含颜色值，节点将根据提供的索引访问其中之一。 13 | - Comfy dtype: COLOR 14 | - Python dtype: List[str] 15 | - index 16 | - 索引参数指定从颜色列表中检索颜色的位置。它支持正向和负向索引，使得可以从列表的开头或末尾访问元素。 17 | - Comfy dtype: INT 18 | - Python dtype: int 19 | 20 | # Output types 21 | - color 22 | - 输出是从输入颜色列表中指定位置检索到的单个颜色值。 23 | - Comfy dtype: COLOR 24 | - Python dtype: str 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | class FromListGet1Color(metaclass=GetSingleFromListMeta): TYPE = "COLOR" 35 | 36 | ``` 37 | -------------------------------------------------------------------------------- /docs/FromListGet1Cond.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGet1Cond 4 | - Category: Bmad/Lists/Get1 5 | - Output node: False 6 | 7 | FromListGet1Cond节点旨在从给定列表中根据指定索引提取单个条件元素。它实现了对列表中条件数据的选择性访问，便于需要单独操作或检查条件元素的操作。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 需要提取条件元素的源列表。这个参数对于指定源列表至关重要。 13 | - Comfy dtype: CONDITIONING 14 | - Python dtype: List[CONDITIONING] 15 | - index 16 | - 指定从列表中提取条件元素的索引。支持负索引以实现反向访问。 17 | - Comfy dtype: INT 18 | - Python dtype: int 19 | 20 | # Output types 21 | - conditioning 22 | - 从列表指定索引处提取的条件元素。 23 | - Comfy dtype: CONDITIONING 24 | - Python dtype: CONDITIONING 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | class FromListGet1Cond(metaclass=GetSingleFromListMeta): TYPE = "CONDITIONING" 35 | 36 | ``` 37 | -------------------------------------------------------------------------------- /docs/FromListGet1Float.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGet1Float 4 | - Category: Bmad/Lists/Get1 5 | - Output node: False 6 | 7 | FromListGet1Float节点旨在从给定列表中根据指定索引提取单个浮点值。它支持列表的随机访问，包括使用负索引来逆序访问元素，从而增强了数据操作的灵活性。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 用于提取浮点值的源列表。这个参数对于指定数据来源至关重要。 13 | - Comfy dtype: FLOAT 14 | - Python dtype: List[float] 15 | - index 16 | - 指定从列表中提取浮点值的索引位置。支持负索引以实现逆序访问。 17 | - Comfy dtype: INT 18 | - Python dtype: int 19 | 20 | # Output types 21 | - float 22 | - 从列表指定索引位置提取的浮点值。 23 | - Comfy dtype: FLOAT 24 | - Python dtype: float 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | class FromListGet1Float(metaclass=GetSingleFromListMeta): TYPE = "FLOAT" 35 | 36 | ``` 37 | -------------------------------------------------------------------------------- /docs/FromListGet1Image.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGet1Image 4 | - Category: Bmad/Lists/Get1 5 | - Output node: False 6 | 7 | FromListGet1Image 节点的设计目的是从一个图像列表中根据指定的索引检索单个图像。该节点支持随机访问，包括使用负索引从列表末尾访问元素，使其在各种图像处理任务中具有多功能性。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 要从中检索单个图像的图像列表。该参数对于指定图像的来源至关重要。 13 | - Comfy dtype: IMAGE 14 | - Python dtype: List[torch.Tensor] 15 | - index 16 | - 从列表中检索图像的索引。支持使用负索引进行反向访问。 17 | - Comfy dtype: INT 18 | - Python dtype: int 19 | 20 | # Output types 21 | - image 22 | - 从列表中指定索引检索到的单个图像。 23 | - Comfy dtype: IMAGE 24 | - Python dtype: torch.Tensor 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | class FromListGet1Image(metaclass=GetSingleFromListMeta): TYPE = "IMAGE" 35 | 36 | ``` 37 | -------------------------------------------------------------------------------- /docs/FromListGet1Int.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGet1Int 4 | - Category: Bmad/Lists/Get1 5 | - Output node: False 6 | 7 | FromListGet1Int 节点用于从一个整数列表中检索单个整数值。它根据指定的索引获取列表元素，支持负数索引以便从列表末尾访问元素，提供了灵活的列表元素访问方式。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 用于检索整数值的列表。这是操作的核心输入，提供了数据源。 13 | - Comfy dtype: INT 14 | - Python dtype: List[int] 15 | - index 16 | - 指定从列表中检索整数值的索引。支持负值以实现反向访问，直接影响输出整数的选择。 17 | - Comfy dtype: INT 18 | - Python dtype: int 19 | 20 | # Output types 21 | - int 22 | - 从列表指定索引处检索到的单个整数值。 23 | - Comfy dtype: INT 24 | - Python dtype: int 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | class FromListGet1Int(metaclass=GetSingleFromListMeta): TYPE = "INT" 35 | 36 | ``` 37 | -------------------------------------------------------------------------------- /docs/FromListGet1Latent.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGet1Latent 4 | - Category: Bmad/Lists/Get1 5 | - Output node: False 6 | 7 | FromListGet1Latent节点用于从潜在表示列表中提取单个潜在表示。它简化了从潜在表示集合中选择特定潜在项的过程，使得对潜在表示集合的操作和分析更加便捷。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 用于提取单个潜在表示的潜在表示列表。该参数对于指定要选择的潜在表示的来源至关重要。 13 | - Comfy dtype: LATENT 14 | - Python dtype: List[torch.Tensor] 15 | - index 16 | - 要从列表中提取的潜在表示的索引。该参数决定了从列表中选择哪一项。 17 | - Comfy dtype: INT 18 | - Python dtype: int 19 | 20 | # Output types 21 | - latent 22 | - 从提供的列表中提取的单个潜在表示。这个输出对于需要特定潜在项的下游任务至关重要。 23 | - Comfy dtype: LATENT 24 | - Python dtype: torch.Tensor 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | class FromListGet1Latent(metaclass=GetSingleFromListMeta): TYPE = "LATENT" 35 | 36 | ``` 37 | -------------------------------------------------------------------------------- /docs/FromListGet1Mask.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGet1Mask 4 | - Category: Bmad/Lists/Get1 5 | - Output node: False 6 | 7 | FromListGet1Mask节点旨在根据给定索引从掩码列表中检索特定项。它支持随机访问，包括使用负索引从列表末尾访问项目。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 将从中检索项目的掩码列表。它对于指定应在哪个列表上执行操作至关重要。 13 | - Comfy dtype: MASK 14 | - Python dtype: List[torch.Tensor] 15 | - index 16 | - 要从列表中检索的项目的索引。支持负值以进行反向访问。 17 | - Comfy dtype: INT 18 | - Python dtype: int 19 | 20 | # Output types 21 | - mask 22 | - 从列表中指定索引检索到的掩码。 23 | - Comfy dtype: MASK 24 | - Python dtype: torch.Tensor 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | class FromListGet1Mask(metaclass=GetSingleFromListMeta): TYPE = "MASK" 35 | 36 | ``` 37 | -------------------------------------------------------------------------------- /docs/FromListGet1Model.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGet1Model 4 | - Category: Bmad/Lists/Get1 5 | - Output node: False 6 | - Repo Ref: https://github.com/comfyanonymous/ComfyUI 7 | 8 | FromListGet1Model节点旨在从模型列表中提取单个模型。它通过指定索引来选择性地检索模型，从而实现对特定兴趣模型的聚焦操作。这种功能对于在大型模型集合中进行精准操作和分析特别有用。 9 | 10 | # Input types 11 | ## Required 12 | - list 13 | - list参数代表了一个模型集合，是节点操作的数据源。它对于确定节点的工作范围至关重要，直接影响了可供选择的模型范围。 14 | - Comfy dtype: MODEL 15 | - Python dtype: List[torch.nn.Module] 16 | - index 17 | - index参数决定了要从列表中检索的模型位置。它支持正向和反向索引，为用户提供了灵活的访问方式，无论是想要获取列表开头、结尾还是中间的模型。 18 | - Comfy dtype: INT 19 | - Python dtype: int 20 | 21 | # Output types 22 | - model 23 | - 输出的model是从指定列表中检索出的单个模型。它是节点操作的核心结果，为后续的个性化处理或分析奠定了基础。 24 | - Comfy dtype: MODEL 25 | - Python dtype: torch.nn.Module 26 | 27 | 28 | ## Usage tips 29 | - Infra type: `CPU` 30 | - Common nodes: unknown 31 | 32 | 33 | ## Source code 34 | ```python 35 | class FromListGet1Model(metaclass=GetSingleFromListMeta): TYPE = "MODEL" 36 | 37 | ``` 38 | -------------------------------------------------------------------------------- /docs/FromListGet1String.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGet1String 4 | - Category: Bmad/Lists/Get1 5 | - Output node: False 6 | 7 | FromListGet1String 节点旨在从给定列表中根据指定索引检索单个字符串元素。它支持灵活的列表元素访问方式，包括使用负索引从列表末尾访问元素。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 待检索字符串元素的源列表。这是指定源列表的关键输入。 13 | - Comfy dtype: STRING 14 | - Python dtype: List[str] 15 | - index 16 | - 用于从列表中检索字符串元素的索引。支持使用负索引进行反向访问。 17 | - Comfy dtype: INT 18 | - Python dtype: int 19 | 20 | # Output types 21 | - string 22 | - 从列表指定索引位置检索到的字符串元素。 23 | - Comfy dtype: STRING 24 | - Python dtype: str 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | class FromListGet1String(metaclass=GetSingleFromListMeta): TYPE = "STRING" 35 | 36 | ``` 37 | -------------------------------------------------------------------------------- /docs/FromListGetColors.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGetColors 4 | - Category: Bmad/Lists/GetAll 5 | - Output node: False 6 | 7 | 该节点旨在从列表中提取颜色信息，便于进一步处理或分析颜色数据。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 需要提取颜色信息的列表。这个参数对于指定节点将处理的颜色数据源至关重要。 13 | - Comfy dtype: COLOR 14 | - Python dtype: List[str] 15 | 16 | # Output types 17 | - color 18 | - 从输入列表中提取的颜色数据列表。这个输出对于需要颜色信息的下游任务非常重要。 19 | - Comfy dtype: COLOR 20 | - Python dtype: List[Tuple[int, int, int]] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class FromListGetColors(metaclass=UnMakeListMeta): TYPE = "COLOR" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/FromListGetConds.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGetConds 4 | - Category: Bmad/Lists/GetAll 5 | - Output node: False 6 | 7 | FromListGetConds 节点用于从指定列表中获取单个条件元素。它可以根据给定的索引随机访问列表元素，支持使用负索引进行反向访问，从而增强了处理条件数据的灵活性。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 用于检索条件元素的列表。它是指定数据源的关键输入。 13 | - Comfy dtype: CONDITIONING 14 | - Python dtype: List[CONDITIONING] 15 | 16 | # Output types 17 | - conditioning 18 | - 在指定索引处检索到的条件元素。 19 | - Comfy dtype: CONDITIONING 20 | - Python dtype: CONDITIONING 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class FromListGetConds(metaclass=UnMakeListMeta): TYPE = "CONDITIONING" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/FromListGetFloats.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGetFloats 4 | - Category: Bmad/Lists/GetAll 5 | - Output node: False 6 | 7 | FromListGetFloats节点用于从浮点数列表中检索特定索引位置的浮点值。它支持随机访问列表元素，包括使用负索引进行反向访问，从而增强了数据操作的灵活性。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 这是一个浮点数列表，用于检索特定的值。它是指定要访问的数据集的关键输入。 13 | - Comfy dtype: FLOAT 14 | - Python dtype: List[float] 15 | 16 | # Output types 17 | - float 18 | - 从列表中指定索引位置检索到的浮点值。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: float 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class FromListGetFloats(metaclass=UnMakeListMeta): TYPE = "FLOAT" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/FromListGetImages.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGetImages 4 | - Category: Bmad/Lists/GetAll 5 | - Output node: False 6 | 7 | FromListGetImages节点旨在根据给定索引从图像列表中检索特定图像。它支持随机访问列表中的图像，包括使用负索引实现反向访问图像的功能。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - list参数代表要从中检索特定图像的图像列表。它对于指定图像来源至关重要。 13 | - Comfy dtype: IMAGE 14 | - Python dtype: List[torch.Tensor] 15 | 16 | # Output types 17 | - image 18 | - 此输出是从列表中指定位置检索到的图像。 19 | - Comfy dtype: IMAGE 20 | - Python dtype: torch.Tensor 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class FromListGetImages(metaclass=UnMakeListMeta): TYPE = "IMAGE" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/FromListGetInts.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGetInts 4 | - Category: Bmad/Lists/GetAll 5 | - Output node: False 6 | 7 | FromListGetInts 节点旨在从整数列表中提取特定索引位置的单个整数值。它支持列表的随机访问，允许使用直接索引和负索引进行反向访问，从而实现从整数列表中灵活地检索数据。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 这是用于提取单个整数值的整数列表。该参数对于指定提取源列表至关重要。 13 | - Comfy dtype: INT 14 | - Python dtype: List[int] 15 | 16 | # Output types 17 | - int 18 | - 从列表中指定索引位置提取的整数值。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class FromListGetInts(metaclass=UnMakeListMeta): TYPE = "INT" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/FromListGetLatents.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGetLatents 4 | - Category: Bmad/Lists/GetAll 5 | - Output node: False 6 | 7 | FromListGetLatents节点旨在从提供的列表中提取多个潜在表示。它支持选择和操作潜在数据结构，便于进行潜在向量的检索、分析和转换等操作。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 指定要从中提取元素的潜在表示列表。此参数对于定义要操作的潜在数据源至关重要。 13 | - Comfy dtype: LATENT 14 | - Python dtype: List[torch.Tensor] 15 | 16 | # Output types 17 | - latent 18 | - 从指定列表中提取的潜在表示。这个输出对于潜在向量的进一步处理或分析非常重要。 19 | - Comfy dtype: LATENT 20 | - Python dtype: torch.Tensor 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class FromListGetLatents(metaclass=UnMakeListMeta): TYPE = "LATENT" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/FromListGetMasks.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGetMasks 4 | - Category: Bmad/Lists/GetAll 5 | - Output node: False 6 | - Repo Ref: https://github.com/bmad4ever/ComfyUI-Bmad-Custom-Nodes 7 | 8 | FromListGetMasks 节点旨在从给定的遮罩列表中检索特定遮罩。它支持列表元素的随机访问，允许正向和反向索引，从而实现对列表中遮罩的灵活操作和选择。 9 | 10 | # Input types 11 | ## Required 12 | - list 13 | - 这是要从中检索特定遮罩的遮罩列表。该参数对于指定源列表至关重要。 14 | - Comfy dtype: MASK 15 | - Python dtype: List[torch.Tensor] 16 | 17 | # Output types 18 | - mask 19 | - 从列表中指定索引处检索到的遮罩。这个输出对于进一步处理或操作所选遮罩至关重要。 20 | - Comfy dtype: MASK 21 | - Python dtype: torch.Tensor 22 | 23 | 24 | ## Usage tips 25 | - Infra type: `CPU` 26 | - Common nodes: unknown 27 | 28 | 29 | ## Source code 30 | ```python 31 | class FromListGetMasks(metaclass=UnMakeListMeta): TYPE = "MASK" 32 | 33 | ``` 34 | -------------------------------------------------------------------------------- /docs/FromListGetModels.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGetModels 4 | - Category: Bmad/Lists/GetAll 5 | - Output node: False 6 | 7 | FromListGetModels节点旨在从模型列表中提取单个模型，基于指定的索引。它实现了从集合中选择性地检索模型的功能，有助于需要对单个模型进行处理的操作。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 这是需要从中检索单个模型的模型列表。该参数对于指定模型的源集合至关重要。 13 | - Comfy dtype: MODEL 14 | - Python dtype: List[torch.nn.Module] 15 | 16 | # Output types 17 | - model 18 | - 从输入列表的指定索引处提取的模型。这个输出对于后续需要特定模型的操作非常重要。 19 | - Comfy dtype: MODEL 20 | - Python dtype: torch.nn.Module 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class FromListGetModels(metaclass=UnMakeListMeta): TYPE = "MODEL" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/FromListGetStrings.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: FromListGetStrings 4 | - Category: Bmad/Lists/GetAll 5 | - Output node: False 6 | 7 | FromListGetStrings节点设计用于从字符串列表中检索特定索引的字符串。它抽象了访问列表元素的过程，支持正向和反向索引，从而提高了在工作流中操作字符串列表的灵活性和便捷性。 8 | 9 | # Input types 10 | ## Required 11 | - list 12 | - 用于检索特定字符串的字符串列表。作为数据源，它对节点的操作至关重要。 13 | - Comfy dtype: STRING 14 | - Python dtype: List[str] 15 | 16 | # Output types 17 | - string 18 | - 从列表中指定索引位置检索出的字符串。这个输出对于工作流中的进一步处理或使用至关重要。 19 | - Comfy dtype: STRING 20 | - Python dtype: str 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class FromListGetStrings(metaclass=UnMakeListMeta): TYPE = "STRING" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/Get Batch From History (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Get Batch From History (mtb).md -------------------------------------------------------------------------------- /docs/GetImageSize+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/GetImageSize+.md -------------------------------------------------------------------------------- /docs/GligenClamp.md: -------------------------------------------------------------------------------- 1 | --- 2 | tags: 3 | - DataClamp 4 | 5 | # GligenClamp 6 | ## 文档说明 7 | ### 类名：`GligenClamp` 8 | ### 分类：`clamp` 9 | ### 输出节点：`False` 10 | 11 | `GligenClamp` 节点旨在原样传递 GLIGEN 数据，作为数据处理管道中的一个占位符或检查点。它确保 GLIGEN 数据在经过不同阶段的处理时保持完整，充当控制机制。 12 | ## 输入类型 13 | ### 必需项 14 | - **`gligen`** 15 | - `gligen` 参数表示要被钳制的 GLIGEN 数据。此节点作为中转站，确保在整个过程中 GLIGEN 数据保持不变。 16 | - Comfy 数据类型：`GLIGEN` 17 | - Python 数据类型：`tuple` 18 | 19 | ## 输出类型 20 | - **`gligen`** 21 | - Comfy 数据类型：`GLIGEN` 22 | - 返回未修改的 GLIGEN 数据，确保其在处理管道中保持完整性。 23 | - Python 数据类型：`tuple` 24 | 25 | ## 使用提示 26 | - 硬件类型：`CPU` 27 | - 常用节点：未知 28 | 29 | ## 源代码 30 | ```python 31 | class GligenClamp: 32 | def __init__(self): 33 | pass 34 | 35 | @classmethod 36 | def INPUT_TYPES(cls): 37 | return { 38 | "required": { 39 | "gligen": ("GLIGEN",), 40 | }, 41 | } 42 | 43 | RETURN_TYPES = ("GLIGEN",) 44 | FUNCTION = "node" 45 | CATEGORY = "clamp" 46 | 47 | def node(self, gligen): 48 | return (gligen,) 49 | ``` -------------------------------------------------------------------------------- /docs/GoogleTranslateTextNode.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: GoogleTranslateTextNode 4 | - Category: AlekPet Nodes/text 5 | - Output node: False 6 | 7 | 该节点提供了将文本从一种语言翻译成另一种语言的功能，并提供了手动跳过翻译的选项。它可以根据配置使用Google Translate API或内置翻译器来执行翻译。 8 | 9 | # Input types 10 | ## Required 11 | - from_translate 12 | - 指定翻译的源语言代码。如果设置为'auto'，将自动检测源语言。 13 | - Comfy dtype: COMBO[STRING] 14 | - Python dtype: str 15 | - to_translate 16 | - 指定翻译的目标语言代码。 17 | - Comfy dtype: COMBO[STRING] 18 | - Python dtype: str 19 | - manual_translate 20 | - 一个布尔标志，当设为true时，将跳过翻译过程并返回原始文本。对于手动控制翻译过程很有用。 21 | - Comfy dtype: COMBO[BOOLEAN] 22 | - Python dtype: bool 23 | - text 24 | - 需要翻译的文本。支持多行输入。 25 | - Comfy dtype: STRING 26 | - Python dtype: str 27 | 28 | # Output types 29 | - text 30 | - 翻译后的文本。 31 | - Comfy dtype: STRING 32 | - Python dtype: str 33 | 34 | 35 | ## Usage tips 36 | - Infra type: `CPU` 37 | - Common nodes: unknown 38 | 39 | 40 | ## Source code 41 | ```python 42 | # Built-in or C extension class, unable to automatically detect source code 43 | ``` 44 | -------------------------------------------------------------------------------- /docs/HaldCLUT .md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/HaldCLUT .md -------------------------------------------------------------------------------- /docs/ICLightAppply.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/ICLightAppply.md -------------------------------------------------------------------------------- /docs/IG Int.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: IG Int 4 | - Category: 🐓 IG Nodes/Primitives 5 | - Output node: False 6 | 7 | IG Int节点旨在封装和处理节点式编程环境中的整数值。它允许指定一个整数值，为在可视化编程环境中处理整数提供了一种直接的方式。 8 | 9 | # Input types 10 | ## Required 11 | - value 12 | - 指定要由节点使用或操作的整数值。这个参数是节点操作的核心，作为决定节点输出的主要输入。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - int 18 | - 输出由输入参数指定的整数值，有效地将该值传递通过节点。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class IG_Int: 31 | def __init__(self) -> None: 32 | pass 33 | 34 | @classmethod 35 | def INPUT_TYPES(cls): 36 | return { 37 | "required": { 38 | "value": ("INT", {"default": 0, "min": -sys.maxsize, "max": sys.maxsize, "step": 1}), 39 | }, 40 | } 41 | 42 | RETURN_TYPES = ("INT",) 43 | FUNCTION = "main" 44 | CATEGORY = TREE_PRIMITIVES 45 | 46 | def main(self, value): 47 | return (value,) 48 | 49 | ``` 50 | -------------------------------------------------------------------------------- /docs/IG String.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: `IG String` 4 | - Category: `🐓 IG Nodes/Primitives` 5 | - Output node: `False` 6 | 7 | IG String节点旨在处理字符串输入，允许用户在基于节点的处理环境中输入和传递字符串值。它作为需要文本数据操作的基本构建块。 8 | 9 | # Input types 10 | ## Required 11 | - value 12 | - 此参数接受一个字符串值，作为节点的主要输入。它使节点能够处理并原样传递输入的字符串，不做任何修改。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - string 18 | - 输出未经改变的输入字符串值，便于在后续节点或操作中使用。 19 | - Comfy dtype: STRING 20 | - Python dtype: str 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class IG_String: 31 | def __init__(self) -> None: 32 | pass 33 | 34 | @classmethod 35 | def INPUT_TYPES(cls): 36 | return { 37 | "required": { 38 | "value": ("STRING",{}), 39 | }, 40 | } 41 | 42 | RETURN_TYPES = ("STRING",) 43 | FUNCTION = "main" 44 | CATEGORY = TREE_PRIMITIVES 45 | 46 | def main(self, value): 47 | return (value,) 48 | 49 | ``` 50 | -------------------------------------------------------------------------------- /docs/IPAAdapterFaceIDBatch.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: IPAAdapterFaceIDBatch 3 | - Category: Adapter 4 | - Output node: False 5 | - Repo Ref: https://github.com/cubiq/ComfyUI_IPAdapter_plus.git 6 | 7 | IPAAdapterFaceIDBatch节点作为输入数据和FaceID模型之间的中介，确保高效处理批量数据。它旨在简化将FaceID模型应用于数据批量的过程，提高系统的整体性能和吞吐量。 8 | 9 | # Input types 10 | ## Required 11 | - input_data 12 | - input_data参数至关重要，因为它代表了节点将处理的图像批次。它的组织和质量直接影响节点正确应用FaceID模型并产生准确结果的能力。 13 | - Comfy dtype: torch.Tensor 14 | - Python dtype: torch.Tensor 15 | 16 | # Output types 17 | - output_data 18 | - output_data代表将FaceID模型应用于输入批次后的处理结果。它包含了模型的预测或识别，这对于进一步分析或下游任务非常重要。 19 | - Comfy dtype: torch.Tensor 20 | - Python dtype: torch.Tensor 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class IPAAdapterFaceIDBatch(IPAdapterFaceID): 28 | 29 | def __init__(self): 30 | self.unfold_batch = True 31 | ``` -------------------------------------------------------------------------------- /docs/Image Compare (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Image Compare (mtb).md -------------------------------------------------------------------------------- /docs/Image Premultiply (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Image Premultiply (mtb).md -------------------------------------------------------------------------------- /docs/Image Remove Background Rembg 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'image'输入类型代表将未经修改地通过节点的图像数据。它用作确保管道中数据符合预期格式或标准的机制。 12 | - Comfy dtype: IMAGE 13 | - Python dtype: torch.Tensor 14 | 15 | ## Output types 16 | - **image** 17 | - Comfy dtype: IMAGE 18 | - 输出是未修改的图像数据，确保其在数据处理管道中符合预期的格式或标准。 19 | - Python dtype: torch.Tensor 20 | 21 | ## Usage tips 22 | - Infra type: CPU 23 | - Common nodes: unknown 24 | 25 | 26 | ## Source code 27 | ```python 28 | class ImageClamp: 29 | def __init__(self): 30 | pass 31 | 32 | @classmethod 33 | def INPUT_TYPES(cls): 34 | return { 35 | "required": { 36 | "image": ("IMAGE",), 37 | }, 38 | } 39 | 40 | RETURN_TYPES = ("IMAGE",) 41 | FUNCTION = "node" 42 | CATEGORY = "clamp" 43 | 44 | def node(self, image): 45 | return (image,) 46 | ``` -------------------------------------------------------------------------------- /docs/ImageCompositeFromMaskBatch+.md: -------------------------------------------------------------------------------- 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Output types 17 | - image 18 | - 返回经过增强平滑处理的图像,呈现出更加柔和的视觉效果。 19 | - Comfy dtype: IMAGE 20 | - Python dtype: torch.Tensor 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ImageFilterSmoothMore: 31 | def __init__(self): 32 | pass 33 | 34 | @classmethod 35 | def INPUT_TYPES(cls): 36 | return { 37 | "required": { 38 | "images": ("IMAGE",), 39 | }, 40 | } 41 | 42 | RETURN_TYPES = ("IMAGE",) 43 | FUNCTION = "node" 44 | CATEGORY = "image/filter" 45 | 46 | def node(self, images): 47 | return applyImageFilter(images, ImageFilter.SMOOTH_MORE) 48 | 49 | ``` 50 | -------------------------------------------------------------------------------- /docs/ImageFlip+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/ImageFlip+.md -------------------------------------------------------------------------------- /docs/ImageFromBatch+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/ImageFromBatch+.md -------------------------------------------------------------------------------- /docs/ImageInvert.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: ImageInvert 3 | - Category: image 4 | - Output node: False 5 | - Repo Ref: https://github.com/comfyanonymous/ComfyUI 6 | 7 | ImageInvert 节点旨在执行一种基础的图像处理操作，即图像反色。它接收一张图像作为输入，并输出其反色的对应图像，其中像素强度被反转，从而颠倒了图像的明暗区域。该节点在各种图像分析和增强任务中扮演着关键角色，提供了一种简单而有效的视觉对比度改变方法。 8 | 9 | # Input types 10 | ## Required 11 | - image 12 | - 图像参数对于 ImageInvert 节点至关重要，因为它是决定操作对象的主要输入。节点处理这张图像以产生一个反色的版本，使图像参数成为节点功能和结果的核心。 13 | - Comfy dtype: IMAGE 14 | - Python dtype: torch.Tensor 15 | 16 | # Output types 17 | - inverted_image 18 | - 反色图像输出参数代表了图像反色处理的结果。它很重要，因为它是节点主要功能的直接输出，展示了具有反转像素强度的转换后的图像。 19 | - Comfy dtype: IMAGE 20 | - Python dtype: torch.Tensor 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class ImageInvert: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'image': ('IMAGE',)}} 32 | RETURN_TYPES = ('IMAGE',) 33 | FUNCTION = 'invert' 34 | CATEGORY = 'image' 35 | 36 | def invert(self, image): 37 | s = 1.0 - image 38 | return (s,) 39 | ``` -------------------------------------------------------------------------------- /docs/ImageListToBatch+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/ImageListToBatch+.md -------------------------------------------------------------------------------- /docs/ImagePosterize+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/ImagePosterize+.md -------------------------------------------------------------------------------- /docs/ImageRGBA2RGB.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ImageRGBA2RGB 4 | - Category: 🌌 ReActor 5 | - Output node: False 6 | 7 | ImageRGBA2RGB节点旨在将RGBA（红、绿、蓝、透明度）格式的图像转换为RGB格式。此转换过程涉及移除图像的alpha通道，实际上将具有透明度信息的图像转换为不含透明度的标准RGB图像。 8 | 9 | # Input types 10 | ## Required 11 | - image 12 | - 'image'参数表示需要转换为RGB的RGBA格式输入图像。此参数对节点的操作至关重要，因为它直接影响转换过程和最终的RGB图像结果。 13 | - Comfy dtype: IMAGE 14 | - Python dtype: torch.Tensor 15 | 16 | # Output types 17 | - image 18 | - 'image'输出参数表示转换后的RGB格式图像，即原始RGBA图像的alpha通道被移除后的结果。 19 | - Comfy dtype: IMAGE 20 | - Python dtype: torch.Tensor 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `GPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | # Built-in or C extension class, unable to automatically detect source code 31 | ``` 32 | -------------------------------------------------------------------------------- /docs/ImageRemoveBackground+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/ImageRemoveBackground+.md -------------------------------------------------------------------------------- /docs/ImageResize+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/ImageResize+.md -------------------------------------------------------------------------------- /docs/ImageSeamCarving+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/ImageSeamCarving+.md -------------------------------------------------------------------------------- /docs/ImpactDummyInput.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: ImpactDummyInput 3 | - Category: ImpactPack/Debug 4 | - Output node: False 5 | - Repo Ref: https://github.com/ltdrdata/ComfyUI-Impact-Pack.git 6 | 7 | ImpactDummyInput节点的'doit'方法在ImpactPack/Debug类别中充当占位符函数。它旨在执行一个简单的操作，通常用于测试或调试目的，而不会影响主工作流程。 8 | 9 | # Input types 10 | ## Required 11 | - required 12 | - ‘required’参数是一个字典，它指定了ImpactDummyInput节点的必需输入。这对于节点的操作至关重要，因为它决定了必须提供的数据，以便'doit'方法能够正确执行。 13 | - Comfy dtype: Dict[str, any_typ] 14 | - Python dtype: Dict[str, any_typ] 15 | 16 | # Output types 17 | - output 18 | - 'output'参数代表'doit'方法的结果，在这种情况下，是一个简单的字符串，指示虚拟操作的结果。它很重要，因为它在调试过程中提供了节点执行的直接反馈。 19 | - Comfy dtype: str 20 | - Python dtype: Tuple[str, ...] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class ImpactDummyInput: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {}} 32 | CATEGORY = 'ImpactPack/Debug' 33 | RETURN_TYPES = (any_typ,) 34 | FUNCTION = 'doit' 35 | 36 | def doit(self): 37 | return ('DUMMY',) 38 | ``` -------------------------------------------------------------------------------- /docs/ImpactIsNotEmptySEGS.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: ImpactNotEmptySEGS 3 | - Category: ImpactPack/Logic 4 | - Output node: False 5 | - Repo Ref: https://github.com/ltdrdata/ComfyUI-Impact-Pack.git 6 | 7 | ImpactNotEmptySEGS节点的'doit'方法用于检查给定的段落列表是否为空，特别关注列表中的第二个元素。在需要进一步处理或在逻辑流程中做出决策时，数据在特定段落中的存在至关重要。 8 | 9 | # Input types 10 | ## Required 11 | - segs 12 | - 'segs'参数是一个包含数据段落的列表。检查其内容对于'doit'方法的操作至关重要，因为它决定了第二个段落是否非空，这对于节点的决策过程至关重要。 13 | - Comfy dtype: SEGS 14 | - Python dtype: List[Any] 15 | 16 | # Output types 17 | - result 18 | - 'result'输出表示'segs'列表中的第二个元素是否非空。它是一个布尔值，根据'doit'方法执行的条件检查，直接影响后续的逻辑或操作。 19 | - Comfy dtype: BOOLEAN 20 | - Python dtype: bool 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class ImpactNotEmptySEGS: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls): 31 | return {'required': {'segs': ('SEGS',)}} 32 | FUNCTION = 'doit' 33 | CATEGORY = 'ImpactPack/Logic' 34 | RETURN_TYPES = ('BOOLEAN',) 35 | 36 | def doit(self, segs): 37 | return (segs[1] != [],) 38 | ``` -------------------------------------------------------------------------------- /docs/InpaintPreprocessor_Provider_for_SEGS __Inspire.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: InpaintPreprocessor_Provider_for_SEGS __Inspire 4 | - Category: InspirePack/SEGS/ControlNet 5 | - Output node: False 6 | - Repo Ref: https://github.com/ltdrdata/ComfyUI-Inspire-Pack 7 | 8 | 该节点为SEGS（分割）提供了修复（inpainting）预处理功能。它使用了一个专门的封装器，可以对图像应用修复技术（可能还包括蒙版），为进一步的处理或增强做准备。 9 | 10 | # Input types 11 | ## Required 12 | 无需输入参数。 13 | 14 | # Output types 15 | - segs_preprocessor 16 | - 该输出是经过修复预处理后的图像，已准备好进行进一步处理。 17 | - Comfy dtype: SEGS_PREPROCESSOR 18 | - Python dtype: torch.Tensor 19 | 20 | 21 | ## Usage tips 22 | - Infra type: `CPU` 23 | - Common nodes: unknown 24 | 25 | 26 | ## Source code 27 | ```python 28 | class InpaintPreprocessor_Provider_for_SEGS: 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {"required": {}} 32 | RETURN_TYPES = ("SEGS_PREPROCESSOR",) 33 | FUNCTION = "doit" 34 | 35 | CATEGORY = "InspirePack/SEGS/ControlNet" 36 | 37 | def doit(self): 38 | obj = InpaintPreprocessor_wrapper() 39 | return (obj, ) 40 | 41 | ``` 42 | -------------------------------------------------------------------------------- /docs/Int To Bool (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Int To Bool (mtb).md -------------------------------------------------------------------------------- /docs/Int To Number (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Int To Number (mtb).md -------------------------------------------------------------------------------- /docs/Int.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: Int 4 | - Category: Logic 5 | - Output node: False 6 | 7 | Int节点旨在处理整数值，允许在逻辑或计算环境中对这些值进行操作或评估。 8 | 9 | # Input types 10 | ## Required 11 | - value 12 | - 定义要由节点处理或操作的整数值。它作为节点执行操作或评估的主要输入。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - INT 18 | - 输出经过处理或评估的整数值，反映节点执行的任何操作或操作结果。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class Int: 31 | @classmethod 32 | def INPUT_TYPES(s): 33 | return { 34 | "required": {"value": ("INT", {"default": 0})}, 35 | } 36 | 37 | RETURN_TYPES = ("INT",) 38 | 39 | RETURN_NAMES = ("INT",) 40 | 41 | FUNCTION = "execute" 42 | 43 | CATEGORY = "Logic" 44 | 45 | def execute(self, value): 46 | return (value,) 47 | 48 | ``` 49 | -------------------------------------------------------------------------------- /docs/InvertMask (segment anything).md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: InvertMask 3 | - Category: segment_anything 4 | - Output node: False 5 | - Repo Ref: https://github.com/storyicon/comfyui_segment_anything 6 | 7 | InvertMask节点旨在反转二值掩码的值。它在各种图像分割任务中扮演着关键角色，其中反转掩码以突出不同的兴趣区域是必要的。该节点通过从输入掩码中减去1来操作，有效地翻转掩码的极性。 8 | 9 | # Input types 10 | ## Required 11 | - mask 12 | - ‘mask’参数是一个二值掩码，节点将对其进行反转。它对节点的操作至关重要，因为它直接决定了输出。反转后的掩码用于识别或隔离图像中的某些区域，这对于分割目的至关重要。 13 | - Comfy dtype: np.ndarray 14 | - Python dtype: numpy.ndarray 15 | 16 | # Output types 17 | - MASK 18 | - ‘MASK’输出是输入掩码的反转版本。它很重要，因为它代表了节点操作的结果，提供了一个具有反转值的二进制掩码，可以用于分割工作流中的进一步处理或分析。 19 | - Comfy dtype: np.ndarray 20 | - Python dtype: numpy.ndarray 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class InvertMask: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls): 31 | return {'required': {'mask': ('MASK',)}} 32 | CATEGORY = 'segment_anything' 33 | FUNCTION = 'main' 34 | RETURN_TYPES = ('MASK',) 35 | 36 | def main(self, mask): 37 | out = 1.0 - mask 38 | return (out,) 39 | ``` -------------------------------------------------------------------------------- /docs/InvertMask.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: InvertMask 3 | - Category: mask 4 | - Output node: False 5 | - Repo Ref: https://github.com/comfyanonymous/ComfyUI 6 | 7 | InvertMask 节点的 `invert` 方法旨在执行图像处理中一个简单但至关重要的操作。它反转输入的掩码，有效地将像素值从 0 反转到 1，反之亦然，这通常对于某些类型的图像操作或增强任务是必要的。这个节点在改变掩码的视觉表示中发挥关键作用，从而为后续的分析或转换提供了不同的视角或方法。 8 | 9 | # Input types 10 | ## Required 11 | - mask 12 | - 参数 'mask' 是 `invert` 方法的输入，对于节点的操作至关重要。它表示需要被反转的原始掩码。反转过程是基础性的，因为它可以显著改变掩码在下游任务中的上下文和应用。 13 | - Comfy dtype: MASK 14 | - Python dtype: torch.Tensor 15 | 16 | # Output types 17 | - out 18 | - invert 方法的输出是一个新的掩码，它是输入掩码的反转。这个输出很重要，因为它代表了原始掩码的转换状态，准备用于后续的图像处理步骤。 19 | - Comfy dtype: MASK 20 | - Python dtype: torch.Tensor 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class InvertMask: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls): 31 | return {'required': {'mask': ('MASK',)}} 32 | CATEGORY = 'mask' 33 | RETURN_TYPES = ('MASK',) 34 | FUNCTION = 'invert' 35 | 36 | def invert(self, mask): 37 | out = 1.0 - mask 38 | return (out,) 39 | ``` -------------------------------------------------------------------------------- /docs/JDC_EqualizeGrey.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: Equalize 3 | - Category: image/postprocessing 4 | - Output node: False 5 | - Repo Ref: https://github.com/Jordach/comfy-plasma.git 6 | 7 | 该节点类旨在通过调整图像的直方图来增强对比度，这通过分散像素强度值来改善图像的视觉清晰度和细节，使其更适合进一步分析或可视化，确保结果更加清晰和视觉上吸引人。 8 | 9 | # Input types 10 | ## Required 11 | - IMAGE 12 | - IMAGE参数是必不可少的，因为它提供了将由节点处理的输入图像。它直接影响输出，决定了增强图像的质量和外观。没有这个输入，节点无法执行其预期功能。 13 | - Comfy dtype: IMAGE 14 | - Python dtype: PIL.Image 15 | 16 | # Output types 17 | - IMAGE 18 | - 输出的IMAGE代表输入的加工版本，具有更好的对比度和视觉清晰度。它是节点功能直接的结果，对后续的图像分析或显示至关重要。 19 | - Comfy dtype: IMAGE 20 | - Python dtype: PIL.Image 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class Equalize: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'IMAGE': ('IMAGE',)}} 32 | RETURN_TYPES = ('IMAGE',) 33 | FUNCTION = 'process_image' 34 | CATEGORY = 'image/postprocessing' 35 | 36 | def process_image(self, IMAGE): 37 | cimg = conv_tensor_pil(IMAGE) 38 | return conv_pil_tensor(ImageOps.equalize(cimg)) 39 | ``` -------------------------------------------------------------------------------- /docs/JWFloatAbsolute.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: JWFloatAbsolute 4 | - Category: jamesWalker55 5 | - Output node: False 6 | 7 | JWFloatAbsolute节点用于计算给定浮点数的绝对值，有效地去除任何负号以确保结果为非负数。 8 | 9 | # Input types 10 | ## Required 11 | - value 12 | - 需要计算绝对值的输入浮点数。该参数允许节点处理正数和负数，将它们转换为对应的非负数。 13 | - Comfy dtype: FLOAT 14 | - Python dtype: float 15 | 16 | # Output types 17 | - float 18 | - 输入浮点数的非负绝对值。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: float 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | @register_node(identifier, display_name) 31 | class _: 32 | CATEGORY = category 33 | INPUT_TYPES = lambda: {"required": required_inputs} 34 | RETURN_TYPES = tuple(return_types) 35 | OUTPUT_NODE = output_node 36 | FUNCTION = "execute" 37 | 38 | def execute(self, *args, **kwargs): 39 | return func(*args, **kwargs) 40 | 41 | ``` 42 | -------------------------------------------------------------------------------- /docs/JWFloatAdd.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: JWFloatAdd 4 | - Category: jamesWalker55 5 | - Output node: False 6 | 7 | JWFloatAdd节点用于执行两个浮点数的加法运算，为数值计算提供了一个简单而基本的算术操作功能。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 表示要相加的第一个浮点数。它在决定加法运算的结果中起着关键作用。 13 | - Comfy dtype: FLOAT 14 | - Python dtype: float 15 | - b 16 | - 表示要相加的第二个浮点数。它与第一个数一起影响加法运算的结果。 17 | - Comfy dtype: FLOAT 18 | - Python dtype: float 19 | 20 | # Output types 21 | - float 22 | - 两个输入浮点数相加的结果。它封装了这个算术运算的最终输出。 23 | - Comfy dtype: FLOAT 24 | - Python dtype: float 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | @register_node(identifier, display_name) 35 | class _: 36 | CATEGORY = category 37 | INPUT_TYPES = lambda: {"required": required_inputs} 38 | RETURN_TYPES = tuple(return_types) 39 | OUTPUT_NODE = output_node 40 | FUNCTION = "execute" 41 | 42 | def execute(self, *args, **kwargs): 43 | return func(*args, **kwargs) 44 | 45 | ``` 46 | -------------------------------------------------------------------------------- /docs/JWFloatMin.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: JWFloatMin 4 | - Category: jamesWalker55 5 | - Output node: False 6 | 7 | JWFloatMin 节点计算两个浮点数的最小值，为数值数据处理提供了一个简单而基本的数学运算。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 要比较的第一个浮点数。它在与第二个数字比较以确定最小值时起着关键作用。 13 | - Comfy dtype: FLOAT 14 | - Python dtype: float 15 | - b 16 | - 要比较的第二个浮点数。它与第一个数字一起对确定最小值至关重要。 17 | - Comfy dtype: FLOAT 18 | - Python dtype: float 19 | 20 | # Output types 21 | - float 22 | - 两个输入浮点数之间的最小值。 23 | - Comfy dtype: FLOAT 24 | - Python dtype: float 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | @register_node(identifier, display_name) 35 | class _: 36 | CATEGORY = category 37 | INPUT_TYPES = lambda: {"required": required_inputs} 38 | RETURN_TYPES = tuple(return_types) 39 | OUTPUT_NODE = output_node 40 | FUNCTION = "execute" 41 | 42 | def execute(self, *args, **kwargs): 43 | return func(*args, **kwargs) 44 | 45 | ``` 46 | -------------------------------------------------------------------------------- /docs/JWFloatSub.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: JWFloatSub 4 | - Category: jamesWalker55 5 | - Output node: False 6 | 7 | 该节点旨在执行两个浮点数之间的减法运算，为在计算图中计算数值差提供了一种简单直接的方法。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 表示减法运算中的被减数，即将要从中减去另一个数（减数）的数。 13 | - Comfy dtype: FLOAT 14 | - Python dtype: float 15 | - b 16 | - 表示减法运算中的减数，即将要从另一个数（被减数）中减去的数。 17 | - Comfy dtype: FLOAT 18 | - Python dtype: float 19 | 20 | # Output types 21 | - float 22 | - 两个浮点数之间进行减法运算的结果。 23 | - Comfy dtype: FLOAT 24 | - Python dtype: tuple[float] 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | @register_node(identifier, display_name) 35 | class _: 36 | CATEGORY = category 37 | INPUT_TYPES = lambda: {"required": required_inputs} 38 | RETURN_TYPES = tuple(return_types) 39 | OUTPUT_NODE = output_node 40 | FUNCTION = "execute" 41 | 42 | def execute(self, *args, **kwargs): 43 | return func(*args, **kwargs) 44 | 45 | ``` 46 | -------------------------------------------------------------------------------- /docs/JWImageBatchCount.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: JWImageBatchCount 4 | - Category: jamesWalker55 5 | - Output node: False 6 | 7 | JWImageBatchCount节点用于计算给定图像批次中的总图像数量，提供了一种简单的方法来确定图像批次的大小。 8 | 9 | # Input types 10 | ## Required 11 | - images 12 | - 包含一批图像的张量。这是确定批次中图像总数的关键输入。 13 | - Comfy dtype: IMAGE 14 | - Python dtype: torch.Tensor 15 | 16 | # Output types 17 | - int 18 | - 输入批次中存在的图像总数。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `GPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | @register_node("JWImageLoadRGB", "Image Load RGB") 31 | class _: 32 | CATEGORY = "jamesWalker55" 33 | INPUT_TYPES = lambda: { 34 | "required": { 35 | "path": ("STRING", {"default": "./image.png"}), 36 | } 37 | } 38 | RETURN_TYPES = ("IMAGE",) 39 | FUNCTION = "execute" 40 | 41 | def execute(self, path: str): 42 | assert isinstance(path, str) 43 | 44 | img = load_image(path) 45 | return (img,) 46 | 47 | ``` 48 | -------------------------------------------------------------------------------- /docs/JWIntegerAbsolute.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: JWIntegerAbsolute 4 | - Category: jamesWalker55 5 | - Output node: False 6 | 7 | JWIntegerAbsolute节点用于计算整数的绝对值。它将负数转换为其正数对应值，而正数保持不变。这个操作可以确保输出始终是非负的。 8 | 9 | # Input types 10 | ## Required 11 | - value 12 | - 指定需要计算绝对值的整数。这个输入决定了输出的大小，同时确保输出是非负的。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - int 18 | - 输入整数的非负绝对值。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | @register_node(identifier, display_name) 31 | class _: 32 | CATEGORY = category 33 | INPUT_TYPES = lambda: {"required": required_inputs} 34 | RETURN_TYPES = tuple(return_types) 35 | OUTPUT_NODE = output_node 36 | FUNCTION = "execute" 37 | 38 | def execute(self, *args, **kwargs): 39 | return func(*args, **kwargs) 40 | 41 | ``` 42 | -------------------------------------------------------------------------------- /docs/JWIntegerAdd.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: JWIntegerAdd 4 | - Category: jamesWalker55 5 | - Output node: False 6 | 7 | JWIntegerAdd节点执行两个整数值的加法运算，在节点网络中提供了一个简单的算术操作功能。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 要相加的第一个整数值。它在确定加法运算结果中起着关键作用。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | - b 16 | - 要相加的第二个整数值。它与第一个整数一起对加法运算的结果做出同等贡献。 17 | - Comfy dtype: INT 18 | - Python dtype: int 19 | 20 | # Output types 21 | - int 22 | - 两个输入整数相加的结果。这个输出代表了输入值的总和。 23 | - Comfy dtype: INT 24 | - Python dtype: int 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | @register_node(identifier, display_name) 35 | class _: 36 | CATEGORY = category 37 | INPUT_TYPES = lambda: {"required": required_inputs} 38 | RETURN_TYPES = tuple(return_types) 39 | OUTPUT_NODE = output_node 40 | FUNCTION = "execute" 41 | 42 | def execute(self, *args, **kwargs): 43 | return func(*args, **kwargs) 44 | 45 | ``` 46 | -------------------------------------------------------------------------------- /docs/JWIntegerDiv.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: JWIntegerDiv 4 | - Category: jamesWalker55 5 | - Output node: False 6 | 7 | JWIntegerDiv节点执行两个整数输入之间的除法运算，产生一个浮点数结果。这个节点抽象了数学除法运算，允许在数据处理流程中集成除法功能。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 除法运算中的被除数。它代表要被除的整数值。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | - b 16 | - 除法运算中的除数。它代表用来除被除数的整数值。 17 | - Comfy dtype: INT 18 | - Python dtype: int 19 | 20 | # Output types 21 | - float 22 | - 输出是除法运算的结果，以浮点数表示。 23 | - Comfy dtype: FLOAT 24 | - Python dtype: float 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | @register_node(identifier, display_name) 35 | class _: 36 | CATEGORY = category 37 | INPUT_TYPES = lambda: {"required": required_inputs} 38 | RETURN_TYPES = tuple(return_types) 39 | OUTPUT_NODE = output_node 40 | FUNCTION = "execute" 41 | 42 | def execute(self, *args, **kwargs): 43 | return func(*args, **kwargs) 44 | 45 | ``` 46 | -------------------------------------------------------------------------------- /docs/JWIntegerSub.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: `JWIntegerSub` 4 | - Category: `jamesWalker55` 5 | - Output node: `False` 6 | 7 | 这个节点执行两个整数值之间的减法运算，提供了一个简单的算术操作，可以在各种计算工作流程中使用。 8 | 9 | # Input types 10 | ## Required 11 | - a 12 | - 被减数，即要被减去的第一个整数值。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | - b 16 | - 减数，即要从第一个整数中减去的第二个整数值。 17 | - Comfy dtype: INT 18 | - Python dtype: int 19 | 20 | # Output types 21 | - int 22 | - 从第一个整数中减去第二个整数的结果。 23 | - Comfy dtype: INT 24 | - Python dtype: int 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | @register_node(identifier, display_name) 35 | class _: 36 | CATEGORY = category 37 | INPUT_TYPES = lambda: {"required": required_inputs} 38 | RETURN_TYPES = tuple(return_types) 39 | OUTPUT_NODE = output_node 40 | FUNCTION = "execute" 41 | 42 | def execute(self, *args, **kwargs): 43 | return func(*args, **kwargs) 44 | 45 | ``` 46 | -------------------------------------------------------------------------------- /docs/JWIntegerToFloat.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: JWIntegerToFloat 4 | - Category: jamesWalker55 5 | - Output node: False 6 | 7 | JWIntegerToFloat节点旨在将整数输入转换为其浮点数表示。这种转换允许以可容纳小数的格式保存数值数据，从而便于需要分数值的操作。 8 | 9 | # Input types 10 | ## Required 11 | - value 12 | - 要转换为浮点数的整数值。这个输入对于操作至关重要，因为它决定了将要进行转换过程的确切数值数据。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - float 18 | - 输入整数的浮点数表示。这个输出很重要，因为它使得转换后的值可以在需要浮点精度的场景中使用。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: float 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | @register_node(identifier, display_name) 31 | class _: 32 | CATEGORY = category 33 | INPUT_TYPES = lambda: {"required": required_inputs} 34 | RETURN_TYPES = tuple(return_types) 35 | OUTPUT_NODE = output_node 36 | FUNCTION = "execute" 37 | 38 | def execute(self, *args, **kwargs): 39 | return func(*args, **kwargs) 40 | 41 | ``` 42 | -------------------------------------------------------------------------------- /docs/JWStringMultiline.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: JWStringMultiline 4 | - Category: jamesWalker55 5 | - Output node: False 6 | 7 | 该节点旨在处理和返回多行字符串，保留文本中的换行符和格式。它简化了管理多行字符串的复杂性，使处理跨多行的文本变得更加容易。 8 | 9 | # Input types 10 | ## Required 11 | - text 12 | - text输入参数允许用户输入多行字符串。这个参数对于保留输入文本的格式和换行符至关重要，确保输出能准确反映原始文本的结构。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - string 18 | - 输出是一个保留了输入文本格式和换行符的多行字符串，适用于需要保持原始文本结构的应用场景。 19 | - Comfy dtype: STRING 20 | - Python dtype: str 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | @register_node(identifier, display_name) 31 | class _: 32 | CATEGORY = category 33 | INPUT_TYPES = lambda: {"required": required_inputs} 34 | RETURN_TYPES = tuple(return_types) 35 | OUTPUT_NODE = output_node 36 | FUNCTION = "execute" 37 | 38 | def execute(self, *args, **kwargs): 39 | return func(*args, **kwargs) 40 | 41 | ``` 42 | -------------------------------------------------------------------------------- /docs/JWStringToInteger.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: JWStringToInteger 4 | - Category: jamesWalker55 5 | - Output node: False 6 | 7 | 该节点将整数的字符串表示转换为其数值形式。它旨在解析包含整数值的字符串，并将其转换为实际的整数数据类型，从而便于对原本为文本格式的值进行数值运算。 8 | 9 | # Input types 10 | ## Required 11 | - text 12 | - 'text'参数接受一个表示整数的字符串输入。这个参数对节点的操作至关重要，因为它决定了节点执行后将产生的整数值。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - int 18 | - 输出是输入字符串的整数表示。这允许对之前的文本整数值进行进一步的数值运算。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | @register_node(identifier, display_name) 31 | class _: 32 | CATEGORY = category 33 | INPUT_TYPES = lambda: {"required": required_inputs} 34 | RETURN_TYPES = tuple(return_types) 35 | OUTPUT_NODE = output_node 36 | FUNCTION = "execute" 37 | 38 | def execute(self, *args, **kwargs): 39 | return func(*args, **kwargs) 40 | 41 | ``` 42 | -------------------------------------------------------------------------------- /docs/JWStringUnescape.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: JWStringUnescape 4 | - Category: jamesWalker55 5 | - Output node: False 6 | 7 | JWStringUnescape节点旨在处理包含转义字符的字符串输入。它能将诸如'\n'这样的转义序列转换为实际的字符表示（如换行符）。这一功能对于准确处理和显示包含转义序列的字符串至关重要。 8 | 9 | # Input types 10 | ## Required 11 | - text 12 | - text参数是可能包含转义序列的输入字符串。该节点通过将这些序列转换为相应的字符来处理输入，从而提高字符串的可读性和可用性。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - string 18 | - 输出是一个所有转义序列都已转换为实际字符表示的字符串，使其更易读且更易于使用。 19 | - Comfy dtype: STRING 20 | - Python dtype: str 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | @register_node(identifier, display_name) 31 | class _: 32 | CATEGORY = category 33 | INPUT_TYPES = lambda: {"required": required_inputs} 34 | RETURN_TYPES = tuple(return_types) 35 | OUTPUT_NODE = output_node 36 | FUNCTION = "execute" 37 | 38 | def execute(self, *args, **kwargs): 39 | return func(*args, **kwargs) 40 | 41 | ``` 42 | -------------------------------------------------------------------------------- /docs/KSamplerVariationsStochastic+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/KSamplerVariationsStochastic+.md -------------------------------------------------------------------------------- /docs/KSamplerVariationsWithNoise+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/KSamplerVariationsWithNoise+.md -------------------------------------------------------------------------------- /docs/KfDebug_Clip.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfDebug_Clip 3 | - Category: Debugging 4 | - Output node: True 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点便于检查和验证处理流程中的数据，特别关注CLIP数据的完整性和结构。它的设计目的是提供对数据流的洞察，并确保正在处理的信息满足所需的标准和规格。 8 | 9 | # Input types 10 | ## Required 11 | - input 12 | - 输入参数对于节点至关重要，因为它携带了需要调试和检查的数据。它直接影响节点的运行和调试输出的质量。 13 | - Comfy dtype: CLIP 14 | - Python dtype: Any 15 | 16 | # Output types 17 | - output 18 | - 该节点的输出代表了调试过程的结果。它很重要，因为它提供了经过调试节点处理后数据状态的全面概述。 19 | - Comfy dtype: CLIP 20 | - Python dtype: Any 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfDebug_Clip(KfDebug_Passthrough): 28 | RETURN_TYPES = ('CLIP',) 29 | ``` -------------------------------------------------------------------------------- /docs/KfDebug_Cond.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfDebug_Cond 3 | - Category: debugging 4 | - Output node: True 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | KfDebug_Cond 节点旨在提供一种可视化和理解关键帧模型中调节方面的方法。它对于调试非常有用，确保调节数据被正确处理，从而更明智地进行模型优化。 8 | 9 | # Input types 10 | ## Required 11 | - conditioning_data 12 | - 调节数据（conditioning_data）对于 KfDebug_Cond 节点至关重要，因为它代表了用于调节模型输出的输入数据。正确处理该参数对于节点正常工作和调试过程的有效性至关重要。 13 | - Comfy dtype: torch.Tensor 14 | - Python dtype: torch.Tensor 15 | 16 | # Output types 17 | - debug_info 18 | - KfDebug_Cond 节点的 debug_info 输出包含了有关调节过程的宝贵信息。这些信息可以用来识别模型调节中的任何问题，从而促进调试和优化过程。 19 | - Comfy dtype: dict 20 | - Python dtype: Dict[str, Any] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfDebug_Cond(KfDebug_Passthrough): 28 | RETURN_TYPES = ('CONDITIONING',) 29 | ``` -------------------------------------------------------------------------------- /docs/KfDebug_Curve.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfDebug_Curve 3 | - Category: debug 4 | - Output node: True 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点旨在可视化和分析关键帧路径的曲率，清晰地表示动画中的平滑度和连续性。它有助于理解轨迹并确保运动符合预期，这对于保持最终输出中期望的审美和流畅性至关重要。 8 | 9 | # Input types 10 | ## Required 11 | - curve_data 12 | - 该参数保存表示待调试曲线的数值数据。它至关重要，因为它构成了可视化和分析的基础，使节点能够有效处理和显示曲线的特征。 13 | - Comfy dtype: numpy.ndarray 14 | - Python dtype: numpy.ndarray 15 | 16 | # Output types 17 | - visualized_curve 18 | - 输出是输入曲线的视觉表示，对于快速识别任何不规则或改进区域至关重要。它提供了一种有形的方式来评估曲线的性能并进行必要的调整。 19 | - Comfy dtype: PIL.Image 20 | - Python dtype: PIL.Image 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfDebug_Curve(KfDebug_Passthrough): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) 29 | ``` -------------------------------------------------------------------------------- /docs/KfDebug_Float.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfDebug_Float 3 | - Category: Debugging 4 | - Output node: True 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | KfDebug_Float 节点旨在通过提供一种检查和分析数据处理流水线中浮点数的方法来促进调试过程。它是开发人员验证计算各个阶段数值数据的完整性和行为的关键工具。 8 | 9 | # Input types 10 | ## Required 11 | - input_float 12 | - input_float 参数对于节点的操作至关重要，因为它表示需要调试的浮点数。它在节点的执行中起着核心作用，是主要的待检查和分析的数据。 13 | - Comfy dtype: FLOAT 14 | - Python dtype: float 15 | 16 | # Output types 17 | - output_float 18 | - output_float 参数非常重要，因为它代表了由节点处理过的已调试的浮点数。它对于下游流程至关重要，因为它确保了数据流的连续性和可靠性。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: float 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfDebug_Float(KfDebug_Passthrough): 28 | RETURN_TYPES = ('FLOAT',) 29 | ``` -------------------------------------------------------------------------------- /docs/KfDebug_Image.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfDebug_Image 3 | - Category: Debugging 4 | - Output node: True 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | KfDebug_Image节点旨在工作流中便于图像数据的可视化，提供在处理的不同阶段检查和验证图像输入或输出的手段。它通过提供清晰的图像视觉表示，增强了调试过程，确保图像数据被正确处理并满足预期标准。 8 | 9 | # Input types 10 | ## Required 11 | - image 12 | - 图像参数对于KfDebug_Image节点至关重要，因为它是节点可视化的主要输入。它通过允许节点显示图像以供检查，确保图像数据符合预期，并帮助识别任何潜在的问题或差异，影响整个调试过程。 13 | - Comfy dtype: COMBO[numpy.ndarray,PIL.Image,torch.Tensor] 14 | - Python dtype: Union[numpy.ndarray, PIL.Image, torch.Tensor] 15 | 16 | # Output types 17 | - image 18 | - KfDebug_Image节点的输出图像作为输入图像状态的视觉确认。它非常重要，因为它提供了一种在工作流中传递图像数据后验证图像数据的完整性和准确性的手段，确保没有发生更改或损坏。 19 | - Comfy dtype: IMAGE 20 | - Python dtype: Union[numpy.ndarray, PIL.Image] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfDebug_Image(KfDebug_Passthrough): 28 | RETURN_TYPES = ('IMAGE',) 29 | ``` -------------------------------------------------------------------------------- /docs/KfDebug_Int.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfDebug_Int 3 | - Category: Debug 4 | - Output node: True 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | KfDebug_Int节点旨在方便用户在计算图中检查和分析整数值。它使用户能够监控和理解整数数据的流动，确保模型中涉及整数的操作的正确性。该节点通过提供对整数处理和转换的清晰、专注的视图来帮助调试，避免了其他数据类型的复杂性。 8 | 9 | # Input types 10 | ## Required 11 | - input 12 | - 输入参数是将整数值输入到KfDebug_Int节点的关键元素。它对节点的功能至关重要，因为它允许节点监控和分析整数值。输入在决定节点的输出及其在调试过程中提供的洞察中起着关键作用。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - output 18 | - KfDebug_Int节点的输出是经过检查和分析的加工整数值。它作为节点操作的确认以及计算图中整数值的完整性的证明。输出非常重要，因为它为进一步的调试或验证模型的性能提供了基础。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfDebug_Int(KfDebug_Passthrough): 28 | RETURN_TYPES = ('INT',) 29 | ``` -------------------------------------------------------------------------------- /docs/KfDebug_Latent.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfDebug_Latent 3 | - Category: debugging 4 | - Output node: True 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | KfDebug_Latent 节点旨在提供对基于关键帧模型生成的潜在空间表示的洞察。它作为诊断工具，允许检查和分析潜在特征，这对于理解模型数据处理能力的潜在结构和质量至关重要。 8 | 9 | # Input types 10 | ## Required 11 | - input_data 12 | - input_data 参数是输入到节点的原始数据，预期是以 PyTorch 张量的形式。它至关重要，因为它构成了节点进行潜在空间分析的基础。input_data 的质量和结构直接影响节点生成有意义的潜在表示的能力。 13 | - Comfy dtype: torch.Tensor 14 | - Python dtype: torch.Tensor 15 | 16 | # Output types 17 | - latent_representation 18 | - latent_representation 输出提供了节点分析得出的处理后的潜在空间数据。它很重要，因为它包含了从 input_data 中提取的信息，提供了潜在特征的浓缩视图。这个输出对于进一步研究或可视化模型的潜在空间非常有用。 19 | - Comfy dtype: torch.Tensor 20 | - Python dtype: torch.Tensor 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfDebug_Latent(KfDebug_Passthrough): 28 | RETURN_TYPES = ('LATENT',) 29 | ``` -------------------------------------------------------------------------------- /docs/KfDebug_Model.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfDebug_Model 3 | - Category: Debugging 4 | - Output node: True 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点便于检查和分析模型的内部状态和输出，提供了一种理解和调试模型在推理过程中行为的手段。 8 | 9 | # Input types 10 | ## Required 11 | - input_data 12 | - 输入数据非常关键，它代表了模型处理的样本或样本批次。它直接影响模型的输出和从调试中获得的洞察。 13 | - Comfy dtype: COMBO[numpy.ndarray, torch.Tensor] 14 | - Python dtype: Union[numpy.ndarray, torch.Tensor] 15 | - model 16 | - 模型参数至关重要，它定义了正在被调试行为的神经网络结构。模型的配置和参数决定了调试过程。 17 | - Comfy dtype: torch.nn.Module 18 | - Python dtype: torch.nn.Module 19 | 20 | # Output types 21 | - debug_info 22 | - 调试信息很重要，因为它提供了模型内部工作的详细概览，有助于识别潜在问题和改进领域。 23 | - Comfy dtype: Dict[str, Any] 24 | - Python dtype: Dict[str, Any] 25 | 26 | # Usage tips 27 | - Infra type: GPU 28 | 29 | # Source code 30 | ``` 31 | class KfDebug_Model(KfDebug_Passthrough): 32 | RETURN_TYPES = ('MODEL',) 33 | ``` -------------------------------------------------------------------------------- /docs/KfDebug_Segs.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfDebug_Segs 3 | - Category: Debugging 4 | - Output node: True 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点在深学习框架内便于可视化和分析分割结果，使用户能够检查和理解模型在区分图像不同部分方面的性能。 8 | 9 | # Input types 10 | ## Required 11 | - image 12 | - 输入的图像或数组对节点的运行至关重要，因为它是分割的基础。输入的质量和分辨率直接影响分割结果的准确性和细节。 13 | - Comfy dtype: COMBO["Image", "ndarray"] 14 | - Python dtype: Image or torch.Tensor 15 | ## Optional 16 | - mask 17 | - 提供掩码参数有助于通过指定图像中的兴趣区域来细化分割过程。它增强了节点专注于特定段的能力，从而改善了整体的分割结果。 18 | - Comfy dtype: ndarray 19 | - Python dtype: numpy.ndarray 20 | 21 | # Output types 22 | - segmented_image 23 | - 输出代表分割过程的结果，输入图像的不同部分被识别和区分。这对于进一步分析和理解模型的性能至关重要。 24 | - Comfy dtype: Image 25 | - Python dtype: PIL.Image 26 | - segmentation_map 27 | - 该输出提供了分割的详细地图，指示了图像中每个段的边界和分类。这对于评估分割算法的精度和有效性至关重要。 28 | - Comfy dtype: ndarray 29 | - Python dtype: numpy.ndarray 30 | 31 | # Usage tips 32 | - Infra type: CPU 33 | 34 | # Source code 35 | ``` 36 | class KfDebug_Segs(KfDebug_Passthrough): 37 | RETURN_TYPES = ('SEGS',) 38 | ``` -------------------------------------------------------------------------------- /docs/KfDebug_String.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfDebug_String 3 | - Category: Debugging 4 | - Output node: True 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点旨在工作流中促进对字符串数据的检查和分析。它使用户能够在不同阶段查看和验证字符串的内容和结构，确保正在处理的文本信息的准确性和完整性。 8 | 9 | # Input types 10 | ## Required 11 | - input_string 12 | - input_string参数对于这个节点至关重要，因为它携带了需要检查的文本数据。它是一个关键组件，因为节点的主要功能围绕分析和显示这个字符串的内容。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - output_string 18 | - output_string代表节点操作的结果，通常与input_string相同，但根据调试过程可能会被修改或注释。它很重要，因为它提供了最终检查的文本数据。 19 | - Comfy dtype: STRING 20 | - Python dtype: str 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfDebug_String(KfDebug_Passthrough): 28 | RETURN_TYPES = ('STRING',) 29 | ``` -------------------------------------------------------------------------------- /docs/KfDebug_Vae.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfDebug_Vae 3 | - Category: Debugging 4 | - Output node: True 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点便于分析和可视化变分自编码器（VAE）模型的性能和行为，提供对生成过程和潜在空间结构的洞察。 8 | 9 | # Input types 10 | ## Required 11 | - image 12 | - 输入图像对于节点处理和分析数据至关重要，使得能够可视化VAE的重构和生成能力。 13 | - Comfy dtype: Image 14 | - Python dtype: PIL.Image.Image 15 | ## Optional 16 | - latent_codes 17 | - 此参数允许用户输入特定的潜在代码来探索和操作VAE生成的图像，提供对模型潜在空间更深入的理解。 18 | - Comfy dtype: Tensor 19 | - Python dtype: torch.Tensor 20 | 21 | # Output types 22 | - reconstructed_images 23 | - 输出显示VAE重构的图像，提供与原始输入的直接比较和对模型性能的评估。 24 | - Comfy dtype: Image 25 | - Python dtype: PIL.Image.Image 26 | - generated_images 27 | - 这些图像代表了节点从学习到的潜在空间生成新数据点的能力，展示了VAE的生成能力。 28 | - Comfy dtype: Image 29 | - Python dtype: PIL.Image.Image 30 | 31 | # Usage tips 32 | - Infra type: GPU 33 | 34 | # Source code 35 | ``` 36 | class KfDebug_Vae(KfDebug_Passthrough): 37 | RETURN_TYPES = ('VAE',) 38 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromFrequencyx2.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromFrequencyx2 3 | - Category: CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点基于提供的频率生成一对纠缠的正弦曲线，这些曲线从零过渡到一再回到零。它强调创建表现出特定周期行为的平滑、周期性函数，对于需要振荡模式的各种应用非常有用。 8 | 9 | # Input types 10 | ## Required 11 | - frequency 12 | - 频率参数决定了正弦曲线的周期性，影响了曲线振荡的速度以及峰值之间的距离。它对于定义生成曲线的整体节奏和速度非常关键。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - output 18 | - 输出包含两个纠缠的关键帧正弦曲线，它们展示了从零到一的振荡模式。这些曲线是节点功能的核心，代表了处理的主要结果。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromFrequencyx2(KfSinusoidalEntangledZeroOneFromFrequency): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 2 29 | 30 | def main(self, frequency): 31 | return super().main(n=2, frequency=frequency) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromFrequencyx3.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromFrequencyx3 3 | - Category: CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点基于给定的频率生成一组三个正弦曲线，这些曲线以零一模式交织在一起。它强调创建在零和一之间平滑过渡的周期性波形，重点是使用频率参数来控制曲线的周期性和整体形状。 8 | 9 | # Input types 10 | ## Required 11 | - frequency 12 | - 频率参数决定了正弦曲线的周期性，影响波形峰谷的间距和重复。这对于定义生成曲线的节奏和韵律至关重要。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - output 18 | - 输出是三个正弦曲线，每个曲线代表零一交织中的一个独特相位移动。这些曲线是节点功能的核心，作为处理的主要结果。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromFrequencyx3(KfSinusoidalEntangledZeroOneFromFrequency): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 3 29 | 30 | def main(self, frequency): 31 | return super().main(n=3, frequency=frequency) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromFrequencyx4.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromFrequencyx4 3 | - Category: core 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | KfSinusoidalEntangledZeroOneFromFrequencyx4节点旨在根据给定频率生成多个纠缠的正弦曲线。它通过创建四个不同的正弦曲线来操作，每个曲线都有从输入频率派生的独特相位偏移和振幅。该节点特别适用于需要生成复杂、相互关联波形的应用。 8 | 9 | # Input types 10 | ## Required 11 | - frequency 12 | - 频率参数对于确定正弦曲线振荡的基本速率至关重要。它直接影响节点的输出，影响生成曲线的形状和周期性。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - KEYFRAMED_CURVE 18 | - 节点的输出是一组四个关键帧正弦曲线。每条曲线代表一个独特的振荡模式，与其他曲线相互纠缠，形成一个复杂的波形结构。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromFrequencyx4(KfSinusoidalEntangledZeroOneFromFrequency): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 4 29 | 30 | def main(self, frequency): 31 | return super().main(n=4, frequency=frequency) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromFrequencyx5.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromFrequencyx5 3 | - Category: CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点基于给定频率生成五组纠缠的正弦曲线，代表从零到一的复杂值模式。它强调为需要周期性、非线性变换的应用创建复杂的波形。 8 | 9 | # Input types 10 | ## Required 11 | - frequency 12 | - 频率参数决定了正弦曲线的振荡速度，影响生成波形的整体节奏和周期性。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - output 18 | - 输出包含五个正弦曲线，每个曲线代表将输入频率转换到零到一值范围的独特变换。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromFrequencyx5(KfSinusoidalEntangledZeroOneFromFrequency): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 5 29 | 30 | def main(self, frequency): 31 | return super().main(n=5, frequency=frequency) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromFrequencyx6.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromFrequencyx6 3 | - Category: CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点基于提供的频率生成一组六个相互纠缠的正弦曲线，每个曲线在零和一之间振荡。它强调创建保持一致相位关系的相互关联波形，以促进复杂模式的生成和分析。 8 | 9 | # Input types 10 | ## Required 11 | - frequency 12 | - 频率参数决定了正弦曲线的振荡速度，影响生成波形的整体节奏和周期性。它对于定义输出的时间特征至关重要。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - output 18 | - 输出包含六个正弦曲线，每个曲线代表输入频率的一种独特的相位移位解释。这些曲线是节点功能的核心，为进一步分析或可视化提供了丰富的数据集。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromFrequencyx6(KfSinusoidalEntangledZeroOneFromFrequency): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 6 29 | 30 | def main(self, frequency): 31 | return super().main(n=6, frequency=frequency) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromFrequencyx7.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromFrequencyx7 3 | - Category: CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点根据输入的基本频率生成一组七个纠缠的正弦曲线，每个曲线在零和一之间振荡。它强调为信号处理或可视化中的各种应用创建复杂、同步的波形。 8 | 9 | # Input types 10 | ## Required 11 | - frequency 12 | - 频率参数决定了正弦曲线的振荡速率，影响生成波形的整体模式和周期性。它对于定义输出的时间特性至关重要。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - output 18 | - 输出包括七个正弦曲线，每个曲线根据输入频率表示一个独特的相位移动和振幅。这些曲线对节点的功能至关重要，为进一步分析或操作提供了丰富的数据点集。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromFrequencyx7(KfSinusoidalEntangledZeroOneFromFrequency): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 7 29 | 30 | def main(self, frequency): 31 | return super().main(n=7, frequency=frequency) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromWavelengthx2.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromWavelengthx2 3 | - Category: CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点根据给定的波长生成一对纠缠的正弦曲线，旨在创建复杂且同步的模式。它强调波长与生成波形之间的相互作用，专注于生成曲线的和谐与节奏。 8 | 9 | # Input types 10 | ## Required 11 | - wavelength 12 | - 波长参数决定了正弦曲线的周期，影响生成波形的整体模式和频率。它在确定输出的美学和功能质量方面至关重要。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - KEYFRAMED_CURVE 18 | - 输出包含两个纠缠且同步的正弦曲线，丰富地展示了输入波长的属性。这些曲线可用于需要节奏性和周期性模式的各种应用中。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromWavelengthx2(KfSinusoidalEntangledZeroOneFromWavelength): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 2 29 | 30 | def main(self, wavelength): 31 | return super().main(n=2, wavelength=wavelength) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromWavelengthx3.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromWavelengthx3 3 | - Category: CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点基于输入的波长生成一组三个相互纠缠的正弦曲线，创建一个在零和一之间振荡的复杂模式。它旨在引入适合需要复杂波形的应用的高度周期性变化。 8 | 9 | # Input types 10 | ## Required 11 | - wavelength 12 | - 波长参数决定了正弦曲线的周期，影响生成模式的整体复杂性和频率。这是一个关键输入，因为它直接影响曲线的空间特性。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - curves 18 | - 输出包含三条正弦曲线，每条曲线都有其独特的相位和振幅，这些是从输入波长派生出来的。这些曲线是节点功能的核心，代表了处理的主要结果。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromWavelengthx3(KfSinusoidalEntangledZeroOneFromWavelength): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 3 29 | 30 | def main(self, wavelength): 31 | return super().main(n=3, wavelength=wavelength) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromWavelengthx4.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromWavelengthx4 3 | - Category: CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点基于输入的波长生成一组四个正弦曲线，这些曲线相互纠缠，创造出在零和一之间振荡的模式。它旨在为需要周期性但复杂波形的各种应用生成复杂的波形。 8 | 9 | # Input types 10 | ## Required 11 | - wavelength 12 | - 波长参数决定了正弦曲线的周期，影响生成波形的频率和整体形状。这是一个关键输入，因为它直接影响振荡的模式和规律性。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - output 18 | - 输出包括四个纠缠的正弦曲线，每个曲线代表输入波长振荡模式的独特部分。这个输出非常重要，因为它为各种应用中的进一步分析或操作提供了基础。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromWavelengthx4(KfSinusoidalEntangledZeroOneFromWavelength): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 4 29 | 30 | def main(self, wavelength): 31 | return super().main(n=4, wavelength=wavelength) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromWavelengthx5.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromWavelengthx5 3 | - Category: CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点基于提供的波长生成五组正弦波形的关键帧曲线，将零和一的值以有节奏的模式纠缠在一起。它强调创建周期性、振荡的数据结构，这些数据结构在指定的高低值之间平滑过渡。 8 | 9 | # Input types 10 | ## Required 11 | - wavelength 12 | - 波长参数决定了正弦曲线的周期，影响了整体振荡模式和连续峰值之间的距离。它对于定义生成曲线的频率和重复性至关重要。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - curves 18 | - 输出包括五条关键帧正弦曲线，每条曲线代表基于输入波长生成的正弦模式的独特部分。这些曲线对于节点的功能至关重要，提供了振荡的视觉和数值表示。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromWavelengthx5(KfSinusoidalEntangledZeroOneFromWavelength): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 5 29 | 30 | def main(self, wavelength): 31 | return super().main(n=5, wavelength=wavelength) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromWavelengthx6.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromWavelengthx6 3 | - Category: CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点根据给定的波长生成一组六个具有不同相位差的纠缠正弦曲线。它强调创建在系统中过渡于零和一的复杂、和谐模式，便于分析振荡行为。 8 | 9 | # Input types 10 | ## Required 11 | - wavelength 12 | - 波长参数决定了正弦曲线的周期，影响了生成模式的频率和整体结构。它在定义振荡特性和峰值之间的间隔方面至关重要。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - curves 18 | - 输出包括六个正弦曲线，每个曲线代表振荡模式中的唯一相位。这些曲线对于理解节点对系统动态行为的贡献至关重要。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromWavelengthx6(KfSinusoidalEntangledZeroOneFromWavelength): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 6 29 | 30 | def main(self, wavelength): 31 | return super().main(n=6, wavelength=wavelength) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromWavelengthx7.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromWavelengthx7 3 | - Category: CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点根据输入的波长生成一组七个独特的正弦曲线，每个曲线的相位偏移用于表示从波长派生的二进制序列。它强调创建一个结构化模式，该模式基于波长参数调整频率，在零和一之间振荡。 8 | 9 | # Input types 10 | ## Required 11 | - wavelength 12 | - 波长参数决定了正弦曲线的频率，影响生成序列的整体模式。它对节点的运行至关重要，因为它决定了二进制表示的粒度和周期性。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - KEYFRAMED_CURVE 18 | - 输出是七个正弦曲线的集合，每个曲线代表二进制序列中的唯一相位。这些曲线的组合提供了基于输入波长的纠缠零一模式的视觉和数值表示。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromWavelengthx7(KfSinusoidalEntangledZeroOneFromWavelength): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 7 29 | 30 | def main(self, wavelength): 31 | return super().main(n=7, wavelength=wavelength) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromWavelengthx8.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromWavelengthx8 3 | - Category: CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点根据给定的波长生成一组八个正弦曲线，每个曲线都有不同的相位偏移。主要目的是创建一个在指定波长内振荡的零和一值的纠缠模式，为生成各种应用的复杂波形提供便利。 8 | 9 | # Input types 10 | ## Required 11 | - wavelength 12 | - 波长参数决定了正弦曲线一个完整周期的长度。它非常重要，因为它直接影响生成波形的频率和周期，从而影响曲线的整体模式和行为。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - output 18 | - 输出包括八个正弦曲线，每个曲线在指定波长内代表一个独特的相位偏移。这些曲线对节点的功能至关重要，因为它们为下游过程中的进一步分析或操作提供了基础。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: List[kf.SinusoidalCurve] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromWavelengthx8(KfSinusoidalEntangledZeroOneFromWavelength): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 8 29 | 30 | def main(self, wavelength): 31 | return super().main(n=8, wavelength=wavelength) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalEntangledZeroOneFromWavelengthx9.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalEntangledZeroOneFromWavelengthx9 3 | - Category: core 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | KfSinusoidalEntangledZeroOneFromWavelengthx9节点基于给定的波长生成一组九个正弦曲线，这些曲线相互纠缠，在零和一之间振荡。此节点特别适用于创建需要多个交织频率的复杂模式。 8 | 9 | # Input types 10 | ## Required 11 | - wavelength 12 | - 波长参数决定了正弦波振荡的周期，对于设置生成曲线的频率至关重要。它直接影响输出模式的总体形状和周期性。 13 | - Comfy dtype: float 14 | - Python dtype: float 15 | 16 | # Output types 17 | - KEYFRAMED_CURVE 18 | - 此节点的输出是九个关键帧正弦曲线的元组。每条曲线都被设计为对复合波形提供独特的贡献，提供丰富的振荡组合。 19 | - Comfy dtype: COMBO[kf.SinusoidalCurve] 20 | - Python dtype: Tuple[kf.SinusoidalCurve, ...] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalEntangledZeroOneFromWavelengthx9(KfSinusoidalEntangledZeroOneFromWavelength): 28 | RETURN_TYPES = ('KEYFRAMED_CURVE',) * 9 29 | 30 | def main(self, wavelength): 31 | return super().main(n=9, wavelength=wavelength) 32 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalGetAmplitude.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalGetAmplitude 3 | - Category: ROOT_CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点从弦曲线中提取振幅，提供了曲线偏离平均值的峰值偏差的度量。这对于理解曲线中振荡的强度至关重要。 8 | 9 | # Input types 10 | ## Required 11 | - curve 12 | - 输入的曲线参数代表从中提取振幅的正弦数据结构。它对节点的运行至关重要，因为它直接影响输出结果。 13 | - Comfy dtype: SINUSOIDAL_CURVE 14 | - Python dtype: keyframed.SinusoidalCurve 15 | 16 | # Output types 17 | - amplitude 18 | - 输出提供输入正弦曲线的振幅，表明其振荡的范围。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: float 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalGetAmplitude: 28 | CATEGORY = CATEGORY 29 | FUNCTION = 'main' 30 | RETURN_TYPES = ('FLOAT',) 31 | 32 | @classmethod 33 | def INPUT_TYPES(s): 34 | return {'required': {'curve': ('SINUSOIDAL_CURVE', {'forceInput': True})}} 35 | 36 | def main(self, curve): 37 | return (curve.amplitude,) 38 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalGetFrequency.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalGetFrequency 3 | - Category: ROOT_CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点从正弦曲线中提取基本频率，提供了其振荡速率的度量。 8 | 9 | # Input types 10 | ## Required 11 | - curve 12 | - 输入曲线参数是必需的，因为它是提取频率的数据源。 13 | - Comfy dtype: SINUSOIDAL_CURVE 14 | - Python dtype: kf.Keyframed 15 | 16 | # Output types 17 | - frequency 18 | - 输出代表输入正弦曲线的基本频率。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: float 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalGetFrequency: 28 | CATEGORY = CATEGORY 29 | FUNCTION = 'main' 30 | RETURN_TYPES = ('FLOAT',) 31 | 32 | @classmethod 33 | def INPUT_TYPES(s): 34 | return {'required': {'curve': ('SINUSOIDAL_CURVE', {'forceInput': True})}} 35 | 36 | def main(self, curve): 37 | return (1 / curve.wavelength,) 38 | ``` -------------------------------------------------------------------------------- /docs/KfSinusoidalGetPhase.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: KfSinusoidalGetPhase 3 | - Category: ROOT_CATEGORY 4 | - Output node: False 5 | - Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed 6 | 7 | 该节点旨在从正弦曲线中提取相位信息，这对于理解振荡模式中的时间定位和位置至关重要。 8 | 9 | # Input types 10 | ## Required 11 | - curve 12 | - 曲线参数至关重要，因为它定义了将从中提取相位的正弦波形，直接影响节点的输出。 13 | - Comfy dtype: SINUSOIDAL_CURVE 14 | - Python dtype: keyframed.SinusoidalCurve 15 | 16 | # Output types 17 | - phase 18 | - 输出的相位代表了正弦波的时间偏移量，这对于对齐或比较振荡模式具有重要意义。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: float 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class KfSinusoidalGetPhase: 28 | CATEGORY = CATEGORY 29 | FUNCTION = 'main' 30 | RETURN_TYPES = ('FLOAT',) 31 | 32 | @classmethod 33 | def INPUT_TYPES(s): 34 | return {'required': {'curve': ('SINUSOIDAL_CURVE', {'forceInput': True})}} 35 | 36 | def main(self, curve): 37 | return (curve.phase,) 38 | ``` -------------------------------------------------------------------------------- /docs/Latent Lerp (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Latent Lerp (mtb).md -------------------------------------------------------------------------------- /docs/LatentClamp.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: LatentClamp 4 | - Category: clamp 5 | - Output node: False 6 | 7 | LatentClamp节点旨在不做任何修改地传递潜在表示。它在管道中充当占位符或检查点的角色，确保潜在数据结构得以保留，以供后续处理步骤使用。 8 | 9 | # Input types 10 | ## Required 11 | - latent 12 | - latent参数代表需要传递的潜在数据结构。在操作或分析潜在表示的过程中，保持其完整性对于维护数据流的一致性至关重要。 13 | - Comfy dtype: LATENT 14 | - Python dtype: Dict[str, torch.Tensor] 15 | 16 | # Output types 17 | - latent 18 | - 返回未经改动的潜在数据结构，确保在潜在表示至关重要的处理管道中保持连续性。 19 | - Comfy dtype: LATENT 20 | - Python dtype: Dict[str, torch.Tensor] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class LatentClamp: 31 | def __init__(self): 32 | pass 33 | 34 | @classmethod 35 | def INPUT_TYPES(cls): 36 | return { 37 | "required": { 38 | "latent": ("LATENT",), 39 | }, 40 | } 41 | 42 | RETURN_TYPES = ("LATENT",) 43 | FUNCTION = "node" 44 | CATEGORY = "clamp" 45 | 46 | def node(self, latent): 47 | return (latent,) 48 | 49 | ``` 50 | -------------------------------------------------------------------------------- /docs/LayerColor%3A Brightness & Contrast.md: -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- /docs/LayerUtility%3A Boolean.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: BooleanNode 3 | - Category: 😺dzNodes/LayerUtility/Data 4 | - Output node: False 5 | - Repo Ref: https://github.com/chflame163/ComfyUI_LayerStyle 6 | 7 | 输出一个布尔值。 8 | 9 | # Input types 10 | ## Required 11 | 12 | - bool_value 13 | - 类型: BOOLEAN 14 | - 布尔值。 15 | - Comfy dtype: BOOLEAN 16 | - Python dtype: bool 17 | 18 | # Output types 19 | 20 | - boolean 21 | - 类型: BOOLEAN 22 | - 布尔值。 23 | - Comfy dtype: BOOLEAN 24 | - Python dtype: bool 25 | 26 | # Usage tips 27 | - Infra type: CPU 28 | 29 | # Source code 30 | ``` 31 | class BooleanNode: 32 | def __init__(self): 33 | pass 34 | @classmethod 35 | def INPUT_TYPES(self): 36 | return {"required": { 37 | "bool_value": ("BOOLEAN", {"default": False}), 38 | },} 39 | 40 | RETURN_TYPES = ("BOOLEAN",) 41 | RETURN_NAMES = ("boolean",) 42 | FUNCTION = 'boolean_node' 43 | CATEGORY = '😺dzNodes/LayerUtility/Data' 44 | 45 | def boolean_node(self, bool_value): 46 | return (bool_value,) 47 | ``` -------------------------------------------------------------------------------- /docs/LayerUtility%3A ColorImage V2.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/LayerUtility%3A ColorImage V2.md -------------------------------------------------------------------------------- /docs/LayerUtility%3A Integer.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: IntegerNode 3 | - Category: 😺dzNodes/LayerUtility/Data 4 | - Output node: False 5 | - Repo Ref: https://github.com/chflame163/ComfyUI_LayerStyle 6 | 7 | 输出一个整数。 8 | 9 | # Input types 10 | ## Required 11 | 12 | - int_value 13 | - 类型: INT 14 | - 整数值。 15 | - Comfy dtype: INT 16 | - Python dtype: int 17 | 18 | # Output types 19 | 20 | - int 21 | - 类型: INT 22 | - 整数值。 23 | - Comfy dtype: INT 24 | - Python dtype: int 25 | 26 | # Usage tips 27 | - Infra type: CPU 28 | 29 | # Source code 30 | ``` 31 | class IntegerNode: 32 | def __init__(self): 33 | pass 34 | @classmethod 35 | def INPUT_TYPES(self): 36 | return {"required": { 37 | "int_value":("INT", {"default": 0, "min": -99999999999999999999, "max": 99999999999999999999, "step": 1}), 38 | },} 39 | 40 | RETURN_TYPES = ("INT",) 41 | RETURN_NAMES = ("int",) 42 | FUNCTION = 'integer_node' 43 | CATEGORY = '😺dzNodes/LayerUtility/Data' 44 | 45 | def integer_node(self, int_value): 46 | return (int_value,) 47 | ``` -------------------------------------------------------------------------------- /docs/LayerUtility%3A RGB Value.md: -------------------------------------------------------------------------------- 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"seed":("INT", {"default": 0, "min": 0, "max": 99999999999999999999, "step": 1}), 38 | },} 39 | 40 | RETURN_TYPES = ("INT",) 41 | RETURN_NAMES = ("seed",) 42 | FUNCTION = 'seed_node' 43 | CATEGORY = '😺dzNodes/LayerUtility/Data' 44 | 45 | def seed_node(self, seed): 46 | return (seed,) 47 | ``` -------------------------------------------------------------------------------- /docs/LayerUtility%3A TextBox.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: TextBoxNode 3 | - Category: 😺dzNodes/LayerUtility/Data 4 | - Output node: False 5 | - Repo Ref: https://github.com/chflame163/ComfyUI_LayerStyle 6 | 7 | 输出一段字符串。 8 | 9 | # Input types 10 | ## Required 11 | 12 | - text 13 | - 类型: STRING 14 | - 文本内容。 15 | - Comfy dtype: STRING 16 | - Python dtype: str 17 | 18 | # Output types 19 | 20 | - text 21 | - 类型: STRING 22 | - 文本内容。 23 | - Comfy dtype: STRING 24 | - Python dtype: str 25 | 26 | # Usage tips 27 | - Infra type: CPU 28 | 29 | # Source code 30 | ``` 31 | class TextBoxNode: 32 | def __init__(self): 33 | pass 34 | @classmethod 35 | def INPUT_TYPES(self): 36 | return {"required": { 37 | "text": ("STRING", {"multiline": True}), 38 | },} 39 | 40 | RETURN_TYPES = ("STRING",) 41 | RETURN_NAMES = ("text",) 42 | FUNCTION = 'text_box_node' 43 | CATEGORY = '😺dzNodes/LayerUtility/Data' 44 | 45 | def text_box_node(self, text): 46 | return (text,) 47 | ``` -------------------------------------------------------------------------------- /docs/Load 64 Encoded Image.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Load 64 Encoded Image.md -------------------------------------------------------------------------------- /docs/Load Face Analysis Model (mtb).md: -------------------------------------------------------------------------------- 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该节点有助于解释光流数据以生成运动刷效果，这对于视觉模拟和效果生成至关重要，且不依赖于预训练模型。 8 | 9 | # Input types 10 | ## Required 11 | - optical_flow 12 | - 光流数据至关重要，因为它提供了推断运动模式并创建运动刷效果所需的基础信息。 13 | - Comfy dtype: OPTICAL_FLOW 14 | - Python dtype: numpy.ndarray 15 | 16 | # Output types 17 | - MotionBrush 18 | - 输出代表合成的运动刷，包含了从光流数据中推断出的运动模式。 19 | - Comfy dtype: MOTION_BRUSH 20 | - Python dtype: tuple 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class LoadMotionBrushFromOpticalFlowWithoutModel: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls): 31 | return {'required': {'optical_flow': ('OPTICAL_FLOW',)}} 32 | RETURN_TYPES = ('MotionBrush',) 33 | FUNCTION = 'run_inference' 34 | CATEGORY = 'DragNUWA' 35 | 36 | def run_inference(self, optical_flow): 37 | return (optical_flow,) 38 | ``` -------------------------------------------------------------------------------- /docs/Logic Boolean Primitive.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: WAS_Boolean_Primitive 3 | - Category: WAS Suite/Logic 4 | - Output node: False 5 | - Repo Ref: https://github.com/WASasquatch/was-node-suite-comfyui 6 | 7 | WAS_Boolean_Primitive 节点的 `do` 方法旨在处理并返回一个布尔值。它作为逻辑操作中的基本构建块，确保了工作流程中布尔计算的完整性。 8 | 9 | # Input types 10 | ## Required 11 | - boolean 12 | - “boolean”参数对节点的操作至关重要，因为它直接影响“do”方法的逻辑结果。它是决定节点行为和结果布尔值的主要输入。 13 | - Comfy dtype: BOOLEAN 14 | - Python dtype: bool 15 | 16 | # Output types 17 | - result 18 | - “result”输出参数代表了由“do”方法执行的布尔运算的结果。它很重要，因为它在处理输入后提供了最终的布尔值。 19 | - Comfy dtype: BOOLEAN 20 | - Python dtype: bool 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class WAS_Boolean_Primitive: 28 | 29 | def __init__(self): 30 | pass 31 | 32 | @classmethod 33 | def INPUT_TYPES(cls): 34 | return {'required': {'boolean': ('BOOLEAN', {'default': False})}} 35 | RETURN_TYPES = ('BOOLEAN',) 36 | FUNCTION = 'do' 37 | CATEGORY = 'WAS Suite/Logic' 38 | 39 | def do(self, boolean): 40 | return (boolean,) 41 | ``` -------------------------------------------------------------------------------- /docs/Logic Comparison AND.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: WAS_Logical_AND 3 | - Category: Logical Operations 4 | - Output node: False 5 | - Repo Ref: https://github.com/WASasquatch/was-node-suite-comfyui 6 | 7 | WAS_Logical_AND节点旨在执行逻辑与操作。它评估两个布尔输入，以确定两个条件是否都为真，返回一个布尔结果，表示输入的逻辑与。 8 | 9 | # Input types 10 | ## Required 11 | - boolean_a 12 | - 第一个布尔输入，用于逻辑与操作。它至关重要，因为它代表了必须为真的条件之一，以使最终结果为真。 13 | - Comfy dtype: bool 14 | - Python dtype: bool 15 | - boolean_b 16 | - 第二个布尔输入，也用于逻辑与操作。它的值同样重要，因为只有当它与第一个输入同时为真时，节点才会返回真结果。 17 | - Comfy dtype: bool 18 | - Python dtype: bool 19 | 20 | # Output types 21 | - result 22 | - 两个输入布尔值之间逻辑与操作的结果。它很重要，因为它提供了逻辑与运算的最终结果。 23 | - Comfy dtype: bool 24 | - Python dtype: bool 25 | 26 | # Usage tips 27 | - Infra type: CPU 28 | 29 | # Source code 30 | ``` 31 | class WAS_Logical_AND(WAS_Logical_Comparisons): 32 | 33 | def do(self, boolean_a, boolean_b): 34 | return (boolean_a and boolean_b,) 35 | ``` -------------------------------------------------------------------------------- /docs/Logic Comparison OR.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: WAS_Logical_OR 3 | - Category: Logical Operations 4 | - Output node: False 5 | - Repo Ref: https://github.com/WASasquatch/was-node-suite-comfyui 6 | 7 | WAS_Logical_OR节点旨在对两个布尔输入执行逻辑或操作。在决策过程中，它在存在任一条件就足以触发某个动作或结果时是基础性的。 8 | 9 | # Input types 10 | ## Required 11 | - boolean_a 12 | - 逻辑或操作的第一个布尔输入。它在确定函数结果中起着关键作用，因为它是当为真时将导致整体输出为真的条件之一。 13 | - Comfy dtype: bool 14 | - Python dtype: bool 15 | - boolean_b 16 | - 逻辑或操作的第二个布尔输入。它与第一个输入同等重要，因为它代表了满足条件时可以导致输出为真的另一个条件。 17 | - Comfy dtype: bool 18 | - Python dtype: bool 19 | 20 | # Output types 21 | - result 22 | - 两个输入之间逻辑或操作的结果。它表示是否至少满足了一个条件，概括了或逻辑的精髓。 23 | - Comfy dtype: bool 24 | - Python dtype: bool 25 | 26 | # Usage tips 27 | - Infra type: CPU 28 | 29 | # Source code 30 | ``` 31 | class WAS_Logical_OR(WAS_Logical_Comparisons): 32 | 33 | def do(self, boolean_a, boolean_b): 34 | return (boolean_a or boolean_b,) 35 | ``` -------------------------------------------------------------------------------- /docs/Logic Comparison XOR.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: WAS_Logical_XOR 3 | - Category: Logical Operations 4 | - Output node: False 5 | - Repo Ref: https://github.com/WASasquatch/was-node-suite-comfyui 6 | 7 | WAS_Logical_XOR节点旨在对两个布尔输入执行逻辑异或操作。它在逻辑电路和决策过程中是基础性的，为二进制差异提供了一个简单而强大的机制。 8 | 9 | # Input types 10 | ## Required 11 | - boolean_a 12 | - XOR操作的第一个布尔输入。它在确定逻辑比较的结果中起着关键作用，因为节点的功能取决于对两个输入的评估。 13 | - Comfy dtype: bool 14 | - Python dtype: bool 15 | - boolean_b 16 | - XOR操作的第二个布尔输入。它在逻辑评估中与第一个输入同等重要，对节点操作的最终布尔结果有贡献。 17 | - Comfy dtype: bool 18 | - Python dtype: bool 19 | 20 | # Output types 21 | - result 22 | - 逻辑异或操作的输出，是一个单一的布尔值，代表两个输入的互斥或非关系。 23 | - Comfy dtype: bool 24 | - Python dtype: bool 25 | 26 | # Usage tips 27 | - Infra type: CPU 28 | 29 | # Source code 30 | ``` 31 | class WAS_Logical_XOR(WAS_Logical_Comparisons): 32 | 33 | def do(self, boolean_a, boolean_b): 34 | return (boolean_a != boolean_b,) 35 | ``` -------------------------------------------------------------------------------- /docs/Loop.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: Loop 3 | - Category: DragNUWA 4 | - Output node: False 5 | - Repo Ref: https://github.com/chaojie/ComfyUI-DragNUWA.git 6 | 7 | Loop节点类封装了迭代处理过程，能够执行一系列操作或算法的循环。它旨在方便重复任务的控制流，允许动态调整并结合用户定义的逻辑在循环结构中。 8 | 9 | # Input types 10 | ## Required 11 | - required 12 | - 该参数对于定义循环执行的条件至关重要。它作为一个守门人，确保只有满足指定要求时循环才会运行，从而影响整体的执行流程和操作结果。 13 | - Comfy dtype: COMBO[None] 14 | - Python dtype: Dict[str, Any] 15 | 16 | # Output types 17 | - LOOP 18 | - Loop节点的输出是节点本身，封装了迭代过程的结果。它代表了循环操作序列的高潮，提供了一种结构化和受控的方式来输出循环执行的最终状态。 19 | - Comfy dtype: NODE[Loop] 20 | - Python dtype: Loop 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class Loop: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {}} 32 | RETURN_TYPES = ('LOOP',) 33 | FUNCTION = 'run' 34 | CATEGORY = 'DragNUWA' 35 | 36 | def run(self): 37 | return (self,) 38 | ``` -------------------------------------------------------------------------------- /docs/Manga2Anime_LineArt_Preprocessor_Provider_for_SEGS __Inspire.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: Manga2Anime_LineArt_Preprocessor_Provider_for_SEGS __Inspire 4 | - Category: InspirePack/SEGS/ControlNet 5 | - Output node: False 6 | 7 | 该节点提供了一个专门用于将漫画线稿转换为适合SEGS（语义边缘引导合成）应用的预处理器。它主要关注于将漫画风格的插图调整为可用于动画风格图像生成或修改的格式。 8 | 9 | # Input types 10 | ## Required 11 | 本节点没有必需的输入参数。 12 | 13 | # Output types 14 | - segs_preprocessor 15 | - 输出是一个预处理器，配置用于将漫画线稿转换为动画风格的格式，可直接用于SEGS应用中的后续处理或生成任务。 16 | - Comfy dtype: SEGS_PREPROCESSOR 17 | - Python dtype: AnimeLineArt_Preprocessor_wrapper 18 | 19 | 20 | ## Usage tips 21 | - Infra type: `CPU` 22 | - Common nodes: unknown 23 | 24 | 25 | ## Source code 26 | ```python 27 | class Manga2Anime_LineArt_Preprocessor_Provider_for_SEGS: 28 | @classmethod 29 | def INPUT_TYPES(s): 30 | return {"required": {}} 31 | RETURN_TYPES = ("SEGS_PREPROCESSOR",) 32 | FUNCTION = "doit" 33 | 34 | CATEGORY = "InspirePack/SEGS/ControlNet" 35 | 36 | def doit(self): 37 | obj = Manga2Anime_LineArt_Preprocessor_wrapper() 38 | return (obj, ) 39 | 40 | ``` 41 | -------------------------------------------------------------------------------- /docs/MarigoldDepthEstimation.md: -------------------------------------------------------------------------------- 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clamp 5 | - Output node: False 6 | 7 | MaskClamp节点旨在不做任何修改地传递掩码数据，在数据处理管道中充当一个占位符或检查点的角色。 8 | 9 | # Input types 10 | ## Required 11 | - mask 12 | - mask输入代表将通过节点不变地传递的掩码数据。它对于在整个处理流程中保持掩码信息的完整性至关重要。 13 | - Comfy dtype: MASK 14 | - Python dtype: Tuple[str] 15 | 16 | # Output types 17 | - mask 18 | - 输出未经改变的掩码数据，确保工作流程中掩码信息的连续性。 19 | - Comfy dtype: MASK 20 | - Python dtype: Tuple[str] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class MaskClamp: 31 | def __init__(self): 32 | pass 33 | 34 | @classmethod 35 | def INPUT_TYPES(cls): 36 | return { 37 | "required": { 38 | "mask": ("MASK",), 39 | }, 40 | } 41 | 42 | RETURN_TYPES = ("MASK",) 43 | FUNCTION = "node" 44 | CATEGORY = "clamp" 45 | 46 | def node(self, mask): 47 | return (mask,) 48 | 49 | ``` 50 | -------------------------------------------------------------------------------- /docs/MaskExpandBatch+.md: 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type: `CPU` 22 | - Common nodes: unknown 23 | 24 | 25 | ## Source code 26 | ```python 27 | class MeshGraphormerDepthMapPreprocessorProvider_for_SEGS: 28 | @classmethod 29 | def INPUT_TYPES(s): 30 | return {"required": {}} 31 | RETURN_TYPES = ("SEGS_PREPROCESSOR",) 32 | FUNCTION = "doit" 33 | 34 | CATEGORY = "InspirePack/SEGS/ControlNet" 35 | 36 | def doit(self): 37 | obj = MeshGraphormerDepthMapPreprocessorProvider_wrapper() 38 | return (obj, ) 39 | 40 | ``` 41 | -------------------------------------------------------------------------------- /docs/Model Patch Seamless (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Model Patch Seamless (mtb).md -------------------------------------------------------------------------------- /docs/ModelCompile+.md: -------------------------------------------------------------------------------- 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该节点不需要任何输入参数。它被设计为在不需要外部输入的情况下返回π的值，使其成为访问这个数学常数的自包含函数。 13 | - Comfy dtype: None 14 | - Python dtype: None 15 | 16 | # Output types 17 | - pi_value 18 | - number_pi 方法的输出是数学常数π，它被表示为一个浮点数。这个值对于广泛的数学和科学应用至关重要，在这些应用中精度是至关重要的。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: float 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class WAS_Number_PI: 28 | 29 | def __init__(self): 30 | pass 31 | 32 | @classmethod 33 | def INPUT_TYPES(cls): 34 | return {'required': {}} 35 | RETURN_TYPES = ('NUMBER', 'FLOAT') 36 | FUNCTION = 'number_pi' 37 | CATEGORY = 'WAS Suite/Number' 38 | 39 | def number_pi(self): 40 | return (math.pi, math.pi) 41 | ``` -------------------------------------------------------------------------------- /docs/Number to Text.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: WAS_Number_To_Text 3 | - Category: WAS Suite/Number/Operations 4 | - Output node: False 5 | - Repo Ref: https://github.com/WASasquatch/was-node-suite-comfyui 6 | 7 | 该节点将数字输入转换为文本表示，使得数字可以被下游节点或应用程序更容易理解和使用。 8 | 9 | # Input types 10 | ## Required 11 | - number 12 | - ‘number’参数对于节点的操作至关重要，因为它作为将被转换为文本的输入。这是节点执行其主要功能的必要条件。 13 | - Comfy dtype: NUMBER 14 | - Python dtype: Union[int, float, complex] 15 | 16 | # Output types 17 | - text 18 | - 输出‘text’表示输入数字的文本表示形式，是节点转换过程的结果。 19 | - Comfy dtype: TEXT 20 | - Python dtype: str 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class WAS_Number_To_Text: 28 | 29 | def __init__(self): 30 | pass 31 | 32 | @classmethod 33 | def INPUT_TYPES(cls): 34 | return {'required': {'number': ('NUMBER',)}} 35 | RETURN_TYPES = (TEXT_TYPE,) 36 | FUNCTION = 'number_to_text' 37 | CATEGORY = 'WAS Suite/Number/Operations' 38 | 39 | def number_to_text(self, number): 40 | return (str(number),) 41 | ``` -------------------------------------------------------------------------------- /docs/PainterNode.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: PainterNode 4 | - Category: AlekPet Nodes/image 5 | - Output node: False 6 | - Repo Ref: https://github.com/comfyanonymous/ComfyUI 7 | 8 | PainterNode 被设计用于处理图像,主要通过应用变换并生成相应的蒙版(如适用)。它专注于为进一步处理或可视化准备图像,包括调整图像格式、方向和比例。 9 | 10 | # Input types 11 | ## Required 12 | - image 13 | - image 参数指定要处理的图像文件。它对确定将要进行变换和潜在蒙版生成的输入图像至关重要,直接影响节点的输出。 14 | - Comfy dtype: COMBO[STRING] 15 | - Python dtype: str 16 | 17 | # Output types 18 | - image 19 | - 输出的 image 代表经过变换和适当格式化的输入图像版本,为进一步处理或可视化做好了准备。 20 | - Comfy dtype: IMAGE 21 | - Python dtype: torch.Tensor 22 | - mask 23 | - 输出的 mask 提供与输入图像相关的蒙版,对于需要区分图像前景和背景的各种图像处理任务非常有用。 24 | - Comfy dtype: MASK 25 | - Python dtype: torch.Tensor 26 | 27 | 28 | ## Usage tips 29 | - Infra type: `GPU` 30 | - Common nodes: 31 | - [Image Batch](../../was-node-suite-comfyui/Nodes/Image Batch.md) 32 | - [ImageScale](../../Comfy/Nodes/ImageScale.md) 33 | 34 | 35 | 36 | ## Source code 37 | ```python 38 | # Built-in or C extension class, unable to automatically detect source code 39 | ``` 40 | -------------------------------------------------------------------------------- /docs/PhotoMakerAdapter_Loader_local.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/PhotoMakerAdapter_Loader_local.md -------------------------------------------------------------------------------- /docs/Pick From Batch (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Pick From Batch (mtb).md -------------------------------------------------------------------------------- /docs/PixelOEPixelize+.md: 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-------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: PoseNode 4 | - Category: AlekPet Nodes/image 5 | - Output node: False 6 | 7 | PoseNode旨在处理图像以生成其姿势表示。它利用图像处理技术将图像转换为适合姿势分析的格式，抽象化了姿势检测任务中图像操作和转换的复杂性。 8 | 9 | # Input types 10 | ## Required 11 | - image 12 | - 'image'参数指定要进行姿势检测的图像文件。它在节点操作中起着至关重要的作用，作为导出姿势信息的主要输入源。 13 | - Comfy dtype: COMBO[STRING] 14 | - Python dtype: str 15 | 16 | # Output types 17 | - image 18 | - 输出是处理后图像的张量表示，适用于姿势检测任务中的进一步分析或可视化。 19 | - Comfy dtype: IMAGE 20 | - Python dtype: torch.Tensor 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `GPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | # Built-in or C extension class, unable to automatically detect source code 31 | ``` 32 | -------------------------------------------------------------------------------- /docs/Preview Chooser Fabric.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Preview Chooser Fabric.md -------------------------------------------------------------------------------- /docs/PreviewTextNode.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: PreviewTextNode 4 | - Category: AlekPet Nodes/extras 5 | - Output node: True 6 | 7 | PreviewTextNode提供了一个简单的接口，用于生成文本输入的预览。它主要用于以用户友好的格式显示给定的文本，允许在进一步处理或使用之前快速预览。 8 | 9 | # Input types 10 | ## Required 11 | - text 12 | - 生成预览所需的主要文本输入。它对节点的操作至关重要，因为它直接影响显示给用户的输出。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - string 18 | - 处理后的文本作为输出的一部分返回，封装了预览的文本。 19 | - Comfy dtype: STRING 20 | - Python dtype: Tuple[str] 21 | - ui 22 | - 输出包括一个用户界面组件，用于显示输入文本的预览。 23 | 24 | 25 | ## Usage tips 26 | - Infra type: `CPU` 27 | - Common nodes: unknown 28 | 29 | 30 | ## Source code 31 | ```python 32 | # Built-in or C extension class, unable to automatically detect source code 33 | ``` 34 | -------------------------------------------------------------------------------- /docs/Prompt_Styler.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Prompt_Styler.md -------------------------------------------------------------------------------- /docs/Prompts Everywhere.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: Prompts Everywhere 4 | - Category: everywhere 5 | - Output node: True 6 | - Repo Ref: https://github.com/Formfox/comfy-nodes 7 | 8 | "Prompts Everywhere" 节点旨在实现正面和负面提示的灵活整合。它可以适用于多种场景，支持广泛的输入类型，且对输入的格式或内容没有严格限制。这种设计使得用户能够在各种情况下自由地运用提示，增强了节点的通用性和适应性。 9 | 10 | # Input types 11 | ## Optional 12 | - +ve 13 | - 代表正面提示，可以是任何类型和数量。这种灵活性允许用户广泛而自由地指定对操作有积极贡献的输入。 14 | - Comfy dtype: * 15 | - Python dtype: Any 16 | - -ve 17 | - 代表负面提示，同样可以是任何类型和数量。这为用户提供了一种方式，可以指定在操作中应被视为负面或应被排除的输入。 18 | - Comfy dtype: * 19 | - Python dtype: Any 20 | 21 | # Output types 22 | 该节点没有输出类型。 23 | 24 | 25 | ## Usage tips 26 | - Infra type: `CPU` 27 | - Common nodes: unknown 28 | 29 | 30 | ## Source code 31 | ```python 32 | class AnythingEverywherePrompts(Base): 33 | @classmethod 34 | def INPUT_TYPES(s): 35 | return {"required":{}, 36 | "optional": { "+ve" : ("*", {}), "-ve" : ("*", {}), } } 37 | 38 | def func(self, **kwargs): 39 | return () 40 | 41 | ``` 42 | -------------------------------------------------------------------------------- /docs/Qr Code (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Qr Code (mtb).md -------------------------------------------------------------------------------- /docs/RandomNoise.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: RandomNoise 3 | - Category: Noise Generation 4 | - Output node: False 5 | - Repo Ref: https://github.com/comfyanonymous/ComfyUI 6 | 7 | RandomNoise节点旨在生成随机噪声模式，这些模式可以作为各种生成模型中随机性的来源。它作为创建合成数据的基础组件，确保生成样本的多样性和不可预测性。 8 | 9 | # Input types 10 | ## Required 11 | - noise_seed 12 | - noise_seed参数对于RandomNoise节点至关重要，因为它决定了生成随机噪声的初始状态。这确保了产生的噪声模式是可复现的，这对于生成模型在不同运行中获得一致的结果至关重要。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - noise 18 | - RandomNoise节点的输出是一个包含生成噪声的张量。这个张量非常重要，因为它构成了生成模型中进一步处理的基础，影响最终输出的多样性和质量。 19 | - Comfy dtype: TENSOR 20 | - Python dtype: torch.Tensor 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class RandomNoise(DisableNoise): 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'noise_seed': ('INT', {'default': 0, 'min': 0, 'max': 18446744073709551615})}} 32 | 33 | def get_noise(self, noise_seed): 34 | return (Noise_RandomNoise(noise_seed),) 35 | ``` -------------------------------------------------------------------------------- /docs/ReActorImageDublicator.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ReActorImageDublicator 4 | - Category: 🌌 ReActor 5 | - Output node: False 6 | 7 | ReActorImageDublicator节点是ReActor套件的一部分，旨在创建图像的副本，可能以列表格式呈现。这一功能对于需要同一图像的多个实例进行处理或分析的操作至关重要，从而增强图像操作和增强任务中的工作流程。 8 | 9 | # Input types 10 | ## Required 11 | - image 12 | - 指定要复制的原始图像。 13 | - Comfy dtype: IMAGE 14 | - Python dtype: torch.Tensor 15 | - count 16 | - 确定要从原始图像创建的副本数量。 17 | - Comfy dtype: INT 18 | - Python dtype: int 19 | 20 | # Output types 21 | - IMAGES 22 | - 返回基于指定数量的复制图像列表。 23 | - Comfy dtype: IMAGE 24 | - Python dtype: List[torch.Tensor] 25 | 26 | 27 | ## Usage tips 28 | - Infra type: `CPU` 29 | - Common nodes: unknown 30 | 31 | 32 | ## Source code 33 | ```python 34 | # Built-in or C extension class, unable to automatically detect source code 35 | ``` 36 | -------------------------------------------------------------------------------- /docs/Read Playlist (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Read Playlist (mtb).md -------------------------------------------------------------------------------- /docs/Ref_Image_Preprocessing.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Ref_Image_Preprocessing.md -------------------------------------------------------------------------------- /docs/RemBGSession+.md: 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-------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: RemoveNoiseMask 3 | - Category: ImpactPack/Util 4 | - Output node: False 5 | - Repo Ref: https://github.com/ltdrdata/ComfyUI-Impact-Pack.git 6 | 7 | 该节点旨在通过从输入样本中移除不需要的噪声来处理和优化数据，确保后续的分析或处理步骤基于更干净、更可靠的信息。 8 | 9 | # Input types 10 | ## Required 11 | - samples 12 | - “samples”参数是节点的关键输入，因为它包含了将被处理的数据。节点的功能集中在从这些样本中识别并移除噪声，以提高数据的质量。 13 | - Comfy dtype: LATENT 14 | - Python dtype: Dict[str, torch.Tensor] 15 | 16 | # Output types 17 | - res 18 | - “res”输出是节点操作的结果，包含去噪后的样本。它代表了可以用于进一步处理或分析的精炼数据。 19 | - Comfy dtype: LATENT 20 | - Python dtype: Dict[str, torch.Tensor] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class RemoveNoiseMask: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'samples': ('LATENT',)}} 32 | RETURN_TYPES = ('LATENT',) 33 | FUNCTION = 'doit' 34 | CATEGORY = 'ImpactPack/Util' 35 | 36 | def doit(self, samples): 37 | res = {key: value for (key, value) in samples.items() if key != 'noise_mask'} 38 | return (res,) 39 | ``` -------------------------------------------------------------------------------- /docs/RequestInputs.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/RequestInputs.md -------------------------------------------------------------------------------- /docs/Restore Face (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Restore Face (mtb).md -------------------------------------------------------------------------------- /docs/RetrieveBackendDataNumberKey %2F%2FInspire.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: RetrieveBackendDataNumberKey 3 | - Category: Data Retrieval 4 | - Output node: False 5 | - Repo Ref: https://github.com/ltdrdata/ComfyUI-Inspire-Pack.git 6 | 7 | 该节点旨在根据提供的键从后端服务中提取数值数据，便于在无需复杂的数据处理程序的情况下获取特定信息。 8 | 9 | # Input types 10 | ## Required 11 | - key 12 | - ‘key’参数至关重要，因为它唯一标识了从后端所需的数据。它作为节点定位和检索正确数值的参考。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - data 18 | - 输出‘data’代表从后端获取的与输入‘key’对应的数值。它是节点执行的直接结果，对进一步的数据分析或处理具有重要价值。 19 | - Comfy dtype: NUMBER 20 | - Python dtype: Union[int, float] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class RetrieveBackendDataNumberKey(RetrieveBackendData): 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'key': ('INT', {'default': 0, 'min': 0, 'max': 18446744073709551615})}} 32 | ``` -------------------------------------------------------------------------------- /docs/RetrieveBackendDataNumberKey __Inspire.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: RetrieveBackendDataNumberKey __Inspire 4 | - Category: InspirePack/Backend 5 | - Output node: False 6 | 7 | RetrieveBackendDataNumberKey节点旨在通过数字键从后端缓存中获取并返回相关数据。它抽象了数据检索过程的复杂性，实现了通过键高效访问缓存数据，并支持根据缓存内容结构将数据作为列表处理。 8 | 9 | # Input types 10 | ## Required 11 | - key 12 | - key参数是一个用于从后端缓存中检索特定数据的数字标识符。它在高效访问所需数据方面发挥着至关重要的作用。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - data 18 | - data输出代表使用数字键从后端缓存中检索到的数据。根据缓存内容的结构，它可能以单个项目或列表的形式返回。 19 | - Comfy dtype: * 20 | - Python dtype: Tuple[Any, ...] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class RetrieveBackendDataNumberKey(RetrieveBackendData): 31 | @classmethod 32 | def INPUT_TYPES(s): 33 | return { 34 | "required": { 35 | "key": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}), 36 | } 37 | } 38 | 39 | ``` 40 | -------------------------------------------------------------------------------- /docs/SDXL Empty Latent Image.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/SDXL Empty Latent Image.md -------------------------------------------------------------------------------- /docs/SDXLEmptyLatentSizePicker+.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/SDXLEmptyLatentSizePicker+.md -------------------------------------------------------------------------------- /docs/SaltAudio2VHS.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: SaltAudio2VHS 4 | - Category: SALT/Audio/Util 5 | - Output node: False 6 | 7 | SaltAudio2VHS节点旨在将音频输入转换为模拟VHS磁带音频特性的格式，从而提供一种怀旧或复古的音频效果。 8 | 9 | # Input types 10 | ## Required 11 | - audio 12 | - 'audio'输入是将被处理以模拟VHS磁带音质的原始音频数据。它对于在应用VHS效果之前定义基础音频内容至关重要。 13 | - Comfy dtype: AUDIO 14 | - Python dtype: bytes 15 | 16 | # Output types 17 | - vhs_audio 18 | - Comfy dtype: VHS_AUDIO 19 | - 'vhs_audio'输出是经过处理以模仿VHS磁带音频特性的转换后的音频数据，提供独特的复古音频体验。 20 | - Python dtype: bytes 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class SaltAudio2VHS: 31 | @classmethod 32 | def INPUT_TYPES(cls): 33 | return { 34 | "required": { 35 | "audio": ("AUDIO", ), 36 | }, 37 | } 38 | 39 | RETURN_TYPES = ("VHS_AUDIO",) 40 | RETURN_NAMES = ("vhs_audio",) 41 | 42 | FUNCTION = "convert" 43 | CATEGORY = "SALT/Audio/Util" 44 | 45 | def convert(self, audio): 46 | return (lambda : audio,) 47 | 48 | ``` 49 | -------------------------------------------------------------------------------- /docs/SamplerLCMUpscale.md: 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dtype: float 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class SeargeFloatConstant: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'value': ('FLOAT', {'default': 0.0, 'step': 0.01})}} 32 | RETURN_TYPES = ('FLOAT',) 33 | RETURN_NAMES = ('value',) 34 | FUNCTION = 'get_value' 35 | CATEGORY = 'Searge/_deprecated_/Floats' 36 | 37 | def get_value(self, value): 38 | return (value,) 39 | ``` -------------------------------------------------------------------------------- /docs/SeargeSeparator.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: SeargeSeparator 3 | - Category: UI 4 | - Output node: False 5 | - Repo Ref: https://github.com/jobunk/SeargeSDXL.git 6 | 7 | SeargeSeparator节点旨在作为工作流中的占位符，提供一种分离和组织不同流程段的手段，而不执行任何积极的计算或数据操作。它作为一个结构组件，允许工作流具有清晰和逻辑的布局。 8 | 9 | # Input types 10 | ## Required 11 | - required 12 | - 该参数是SeargeSeparator节点中的关键组件，定义了输入的结构而不指定实际的数据要求。它确保节点在工作流中正确集成，有助于整体组织。 13 | - Comfy dtype: COMBO[{}] 14 | - Python dtype: Dict[str, Any] 15 | 16 | # Output types 17 | - None 18 | - 由于节点的FUNCTION是'do_nothing'，输出故意没有任何数据。这反映了节点作为结构元素而非数据处理元素的角色。 19 | - Comfy dtype: None 20 | - Python dtype: None 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class SeargeSeparator: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls): 31 | return {'required': {}} 32 | RETURN_TYPES = () 33 | RETURN_NAMES = () 34 | FUNCTION = 'do_nothing' 35 | CATEGORY = UI.CATEGORY_UI 36 | 37 | def do_nothing(self): 38 | return () 39 | ``` -------------------------------------------------------------------------------- /docs/SeargeTextInputV2.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: SeargeTextInputV2 3 | - Category: UI_PROMPTING 4 | - Output node: False 5 | - Repo Ref: https://github.com/jobunk/SeargeSDXL.git 6 | 7 | 该节点便于系统从用户那里收集文本输入，支持系统内的交互式通信。它旨在向用户提出问题并捕获他们的回应，作为用户参与和数据收集的基本组件。 8 | 9 | # Input types 10 | ## Required 11 | - prompt 12 | - 提示参数至关重要，因为它定义了向用户展示的问题或陈述，引导他们的输入。它是节点与用户交流的主要方式，影响着收集到的回应的性质和质量。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - prompt_text 18 | - 输出代表了用户对提示的回应，这是进一步处理或分析的宝贵信息源。它是用户输入的直接反映，标志着交互的成功。 19 | - Comfy dtype: SRG_PROMPT_TEXT 20 | - Python dtype: str 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class SeargeTextInputV2: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'prompt': ('STRING', {'default': '', 'multiline': True})}} 32 | RETURN_TYPES = ('SRG_PROMPT_TEXT',) 33 | RETURN_NAMES = ('prompt_text',) 34 | FUNCTION = 'get_value' 35 | CATEGORY = UI.CATEGORY_UI_PROMPTING 36 | 37 | def get_value(self, prompt): 38 | return (prompt,) 39 | ``` -------------------------------------------------------------------------------- /docs/Seed to Number (WLSH).md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: WLSH_Seed_to_Number 3 | - Category: WLSH Nodes/number 4 | - Output node: False 5 | - Repo Ref: https://github.com/wallish77/wlsh_nodes 6 | 7 | 该节点旨在将输入数据转换为数字表示，便于在系统内处理和分析数据。 8 | 9 | # Input types 10 | ## Required 11 | - seed 12 | - 种子参数至关重要，因为它提供了节点执行转换功能所必需的原始数据。 13 | - Comfy dtype: SEED 14 | - Python dtype: Dict[str, Any] 15 | 16 | # Output types 17 | - number 18 | - 输出是从输入派生的数字表示，这对于系统内进一步的计算过程至关重要。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class WLSH_Seed_to_Number: 28 | 29 | def __init__(self): 30 | pass 31 | 32 | @classmethod 33 | def INPUT_TYPES(cls): 34 | return {'required': {'seed': ('SEED',)}} 35 | RETURN_TYPES = ('INT',) 36 | FUNCTION = 'number_to_seed' 37 | CATEGORY = 'WLSH Nodes/number' 38 | 39 | def number_to_seed(self, seed): 40 | return (int(seed['seed']),) 41 | ``` -------------------------------------------------------------------------------- /docs/Seed_.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: CreateSeedNode 3 | - Category: ♾️Mixlab/Utils 4 | - Output node: True 5 | - Repo Ref: https://github.com/shadowcz007/comfyui-mixlab-nodes.git 6 | 7 | 该节点用于生成用于各种随机化过程的种子值，确保随机性在需要时可以控制和复制。 8 | 9 | # Input types 10 | ## Required 11 | - seed 12 | - 种子参数对于初始化随机数生成器至关重要，可以在随机过程中产生可重复和可预测的结果。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - seed 18 | - 输出的种子值作为初始化的随机化过程的参考，指示从中派生随机性的特定状态。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class CreateSeedNode: 28 | 29 | def __init__(self): 30 | pass 31 | 32 | @classmethod 33 | def INPUT_TYPES(cls): 34 | return {'required': {'seed': ('INT', {'default': 0, 'min': 0, 'max': 18446744073709551615})}} 35 | RETURN_TYPES = ('INT',) 36 | RETURN_NAMES = ('seed',) 37 | OUTPUT_NODE = True 38 | FUNCTION = 'run' 39 | CATEGORY = '♾️Mixlab/Utils' 40 | 41 | def run(self, seed): 42 | return (seed,) 43 | ``` -------------------------------------------------------------------------------- /docs/SetRequestStateToComplete.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/SetRequestStateToComplete.md -------------------------------------------------------------------------------- /docs/Sharpen (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Sharpen (mtb).md -------------------------------------------------------------------------------- /docs/SimpleMath+.md: 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unknown 27 | 28 | 29 | ## Source code 30 | ```python 31 | class SingleString: 32 | 33 | @classmethod 34 | def INPUT_TYPES(cls): 35 | return { 36 | "required": { 37 | "string": ("STRING", {"default": '', "multiline": True}), 38 | } 39 | } 40 | RETURN_TYPES = ("STRING",) 41 | FUNCTION = "passtring" 42 | 43 | CATEGORY = "String" 44 | 45 | def passtring(self, string): 46 | return (string, ) 47 | 48 | ``` 49 | -------------------------------------------------------------------------------- /docs/Smart Step (mtb).md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/docs/Smart Step (mtb).md -------------------------------------------------------------------------------- /docs/SplitSigmasDenoise.md: -------------------------------------------------------------------------------- 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‘string’参数对于定义节点将输出的常量字符串值至关重要。它在节点的操作中起着关键作用，因为它直接决定了将传递给下游流程的数据。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - output 18 | - ‘output’参数代表节点返回的字符串值。它很重要，因为它是节点的唯一输出，确保所提供的字符串在工作流的后续步骤中被正确使用。 19 | - Comfy dtype: STRING 20 | - Python dtype: str 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class StringConstant: 28 | 29 | @classmethod 30 | def INPUT_TYPES(cls): 31 | return {'required': {'string': ('STRING', {'default': '', 'multiline': False})}} 32 | RETURN_TYPES = ('STRING',) 33 | FUNCTION = 'passtring' 34 | CATEGORY = 'KJNodes/constants' 35 | 36 | def passtring(self, string): 37 | return (string,) 38 | ``` -------------------------------------------------------------------------------- /docs/StringToInt.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: StringToInt 4 | - Category: Art Venture/Utils 5 | - Output node: False 6 | 7 | StringToInt节点提供了一种简单直接的方法，将数字的字符串表示转换为整数形式。这个功能对于解析和利用以文本形式表示的数值数据非常有用。 8 | 9 | # Input types 10 | ## Required 11 | - string 12 | - string参数接收需要转换为整数的数字文本。这个输入对于转换过程至关重要，因为它决定了最终返回的数值。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - int 18 | - 输出的int是输入字符串的整数表示。这使得系统可以进行数值运算和处理。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class UtilStringToInt: 31 | @classmethod 32 | def INPUT_TYPES(s): 33 | return { 34 | "required": {"string": ("STRING", {"default": "0"})}, 35 | } 36 | 37 | RETURN_TYPES = ("INT",) 38 | CATEGORY = "Art Venture/Utils" 39 | FUNCTION = "string_to_int" 40 | 41 | def string_to_int(self, string: str): 42 | return (int(string),) 43 | 44 | ``` 45 | -------------------------------------------------------------------------------- /docs/Styles Loader (mtb).md: 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-------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ToColorList 4 | - Category: Bmad/Lists/Make or Intercalate 5 | - Output node: False 6 | 7 | ToColorList节点旨在将一组颜色相关数据转换成结构化的列表格式，专门用于处理颜色信息。该节点有助于组织和操作颜色数据，使其在各种计算机颜色分析和处理任务中更易于处理和使用。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 代表要转换为列表的颜色数据集合。这个参数对节点的操作至关重要，因为它决定了生成的颜色列表的内容，进而影响后续的处理和分析。 13 | - Comfy dtype: INT 14 | - Python dtype: List[Union[str, Tuple[int, int, int]]] 15 | 16 | # Output types 17 | - color 18 | - 结构化的颜色数据列表，经过组织以便于在后续的颜色相关计算任务中进行高效处理和操作。 19 | - Comfy dtype: COLOR 20 | - Python dtype: List[Union[str, Tuple[int, int, int]]] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ToColorList(metaclass=MakeListMeta): TYPE = "COLOR" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ToCondList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ToCondList 4 | - Category: Bmad/Lists/Make or Intercalate 5 | - Output node: False 6 | 7 | ToCondList节点旨在从单独的条件输入创建条件数据列表。它简化了将多个条件元素聚合到单个有组织列表中的过程，从而便于在后续处理中更轻松地操作和应用。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 'inputs_len'参数指定要聚合到列表中的单个条件元素的数量。这个参数对于确定结果列表的大小至关重要，从而影响节点的执行和输出的特征。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - conditioning 18 | - 输出是一个条件数据列表，由提供给节点的单个条件输入聚合而成。这个列表可以直接用于需要集合格式条件数据的处理过程中。 19 | - Comfy dtype: CONDITIONING 20 | - Python dtype: List[CONDITIONING] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ToCondList(metaclass=MakeListMeta): TYPE = "CONDITIONING" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ToFloatList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ToFloatList 4 | - Category: Bmad/Lists/Make or Intercalate 5 | - Output node: False 6 | 7 | ToFloatList节点设计用于将单个浮点值聚合成一个列表，便于需要对多个浮点条目进行集体处理或操作的场景。该节点作为一个实用工具，将离散的浮点输入转换为结构化的列表格式，从而在后续的计算任务中实现更高效的处理和应用。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 指定要聚合到列表中的浮点输入数量。该参数决定了生成的浮点列表的大小，允许基于输入数量动态创建列表。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - float 18 | - 生成一个由聚合的浮点输入组成的列表。这个列表作为浮点值的结构化集合，可以在后续操作中进行进一步的处理或操作。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: List[float] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ToFloatList(metaclass=MakeListMeta): TYPE = "FLOAT" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ToImageList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ToImageList 4 | - Category: Bmad/Lists/Make or Intercalate 5 | - Output node: False 6 | - Repo Ref: https://github.com/bmad4ever/ComfyUI-Bmad-Custom-Nodes 7 | 8 | ToImageList节点旨在将一组图像转换为标准化的列表格式。这一功能对于以统一的方式处理多个图像至关重要，使得对整个图像集合进行操作、分析和应用图像处理变得更加容易。 9 | 10 | # Input types 11 | ## Required 12 | - inputs_len 13 | - 'inputs_len'参数代表要转换为列表的图像集合。这个输入对节点的操作至关重要，因为它决定了将要进行转换处理的图像集合。 14 | - Comfy dtype: INT 15 | - Python dtype: List[torch.Tensor] 16 | 17 | # Output types 18 | - image 19 | - 'image'输出是一个由输入集合转换而来的图像列表。这种标准化的格式便于对图像进行进一步的处理和操作。 20 | - Comfy dtype: IMAGE 21 | - Python dtype: List[torch.Tensor] 22 | 23 | 24 | ## Usage tips 25 | - Infra type: `CPU` 26 | - Common nodes: unknown 27 | 28 | 29 | ## Source code 30 | ```python 31 | class ToImageList(metaclass=MakeListMeta): TYPE = "IMAGE" 32 | 33 | ``` 34 | -------------------------------------------------------------------------------- /docs/ToIntList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ToIntList 4 | - Category: Bmad/Lists/Make or Intercalate 5 | - Output node: False 6 | 7 | ToIntList 节点旨在将多个整数输入汇总成一个单一的列表。这一功能在需要将多个整数作为一个整体进行处理或操作的场景中至关重要，它简化了涉及多个整数值的操作流程。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 指定要聚合到列表中的整数输入的数量。这个参数决定了结果列表的大小，通过规定要考虑的整数值的数量，在节点的操作中起着关键作用。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - int 18 | - 输出是由提供给节点的整数输入组成的列表。这个列表作为单个整数的综合集合，有助于需要将多个整数作为统一结构处理的操作。 19 | - Comfy dtype: INT 20 | - Python dtype: List[int] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ToIntList(metaclass=MakeListMeta): TYPE = "INT" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ToLatentList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ToLatentList 4 | - Category: Bmad/Lists/Make or Intercalate 5 | - Output node: False 6 | 7 | ToLatentList节点旨在将单独的潜在表示聚合成一个结构化的列表格式。该节点通过将分散的潜在样本转换为一个连贯的列表，便于处理和操作多个潜在样本，从而促进了潜在数据的组织和处理。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - inputs_len参数代表了需要被聚合成列表的单独潜在样本。这个参数对于收集和构建潜在数据到一个更易管理的格式中至关重要，便于进一步的处理或分析。 13 | - Comfy dtype: INT 14 | - Python dtype: List[torch.Tensor] 15 | 16 | # Output types 17 | - latent 18 | - 输出的latent参数代表了聚合后的潜在样本列表。这种结构化的格式允许更容易地将多个潜在样本作为一个整体进行操作和分析。 19 | - Comfy dtype: LATENT 20 | - Python dtype: List[torch.Tensor] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ToLatentList(metaclass=MakeListMeta): TYPE = "LATENT" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ToMaskList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ToMaskList 4 | - Category: Bmad/Lists/Make or Intercalate 5 | - Output node: False 6 | - Repo Ref: https://github.com/comfyanonymous/ComfyUI 7 | 8 | ToMaskList节点旨在将一系列输入转换为掩码列表。该节点在组织和准备掩码数据以供进一步处理或操作方面发挥着关键作用，确保数据格式正确，可供后续需要掩码输入的节点使用。 9 | 10 | # Input types 11 | ## Required 12 | - inputs_len 13 | - 'inputs_len'参数代表将要转换为掩码列表的输入集合。这个参数对节点的操作至关重要，因为它直接影响输出掩码列表的组成，决定了可供进一步处理的数据。 14 | - Comfy dtype: INT 15 | - Python dtype: List[torch.Tensor] 16 | 17 | # Output types 18 | - mask 19 | - 输出是一个掩码列表，其结构旨在便于在管道中进行涉及掩码数据的进一步操作。 20 | - Comfy dtype: MASK 21 | - Python dtype: List[torch.Tensor] 22 | 23 | 24 | ## Usage tips 25 | - Infra type: `CPU` 26 | - Common nodes: unknown 27 | 28 | 29 | ## Source code 30 | ```python 31 | class ToMaskList(metaclass=MakeListMeta): TYPE = "MASK" 32 | 33 | ``` 34 | -------------------------------------------------------------------------------- /docs/ToModelList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ToModelList 4 | - Category: Bmad/Lists/Make or Intercalate 5 | - Output node: False 6 | 7 | ToModelList节点旨在将多个与模型相关的输入聚合成一个单一列表。这一功能对于需要同时处理多个模型的操作至关重要，如批处理或模型比较任务。它通过提供一种简化的方式来将多个输入分组，从而抽象掉管理多个输入的复杂性。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 指定要聚合到列表中的模型输入数量。该参数决定了结果列表的大小，并在节点的执行中起着至关重要的作用，因为它规定了将考虑多少个模型输入。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - model 18 | - 输出是一个包含聚合模型输入的列表。这个列表便于需要以统一方式处理多个模型的操作，提高了处理模型集合的灵活性和效率。 19 | - Comfy dtype: MODEL 20 | - Python dtype: List[torch.nn.Module] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ToModelList(metaclass=MakeListMeta): TYPE = "MODEL" 31 | 32 | ``` 33 | -------------------------------------------------------------------------------- /docs/ToStringList.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: ToStringList 4 | - Category: Bmad/Lists/Make or Intercalate 5 | - Output node: False 6 | 7 | ToStringList节点旨在将多个字符串输入聚合为单个列表，从而便于进行需要集体处理字符串的操作。它抽象了处理单个字符串的复杂性，实现了高效的批处理和操作。 8 | 9 | # Input types 10 | ## Required 11 | - inputs_len 12 | - 指定要聚合到列表中的字符串输入数量。此参数允许根据提供的输入数量动态调整列表大小。 13 | - Comfy dtype: INT 14 | - Python dtype: int 15 | 16 | # Output types 17 | - string 18 | - 输出由聚合的字符串输入组成的列表。该列表可以作为一个整体进行进一步的处理或操作。 19 | - Comfy dtype: STRING 20 | - Python dtype: List[str] 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class ToStringList(metaclass=MakeListMeta): TYPE = "STRING" 31 | 32 | ``` 33 | 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-------------------------------------------------------------------------------- /docs/VaeClamp.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: VaeClamp 4 | - Category: clamp 5 | - Output node: False 6 | 7 | VaeClamp节点旨在不做任何修改地传递变分自编码器(VAE)模型。它在处理管道中充当实用工具，确保兼容性或强制执行约束，而不改变VAE模型本身。 8 | 9 | # Input types 10 | ## Required 11 | - vae 12 | - 'vae'输入是一个变分自编码器(VAE)模型，该节点接收此模型作为输入并原样返回。它对于在处理管道中维护VAE模型的完整性至关重要。 13 | - Comfy dtype: VAE 14 | - Python dtype: comfy.sd.VAE 15 | 16 | # Output types 17 | - vae 18 | - 返回传入节点的未经修改的变分自编码器(VAE)模型。 19 | - Comfy dtype: VAE 20 | - Python dtype: comfy.sd.VAE 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class VaeClamp: 31 | def __init__(self): 32 | pass 33 | 34 | @classmethod 35 | def INPUT_TYPES(cls): 36 | return { 37 | "required": { 38 | "vae": ("VAE",), 39 | } 40 | } 41 | 42 | RETURN_TYPES = ("VAE",) 43 | FUNCTION = "node" 44 | CATEGORY = "clamp" 45 | 46 | def node(self, vae): 47 | return (vae,) 48 | 49 | ``` 50 | -------------------------------------------------------------------------------- /docs/easy boolean.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: Boolean 3 | - Category: EasyUse/Logic/Type 4 | - Output node: False 5 | - Repo Ref: https://github.com/yolain/ComfyUI-Easy-Use.git 6 | 7 | 该节点类封装了处理布尔值的逻辑，使得对逻辑数据处理的基本操作和转换成为可能。 8 | 9 | # Input types 10 | ## Required 11 | - value 12 | - ‘value’参数至关重要，因为它决定了布尔操作的输入。它是应用节点逻辑的基础元素，并直接影响节点执行的结果。 13 | - Comfy dtype: BOOLEAN 14 | - Python dtype: bool 15 | 16 | # Output types 17 | - boolean 18 | - 输出‘boolean’代表节点执行的布尔操作的结果。这是一个关键的数据片段，可以用于进一步的逻辑决策或作为工作流中的条件。 19 | - Comfy dtype: BOOLEAN 20 | - Python dtype: bool 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class Boolean: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'value': ('BOOLEAN', {'default': False})}} 32 | RETURN_TYPES = ('BOOLEAN',) 33 | RETURN_NAMES = ('boolean',) 34 | FUNCTION = 'execute' 35 | CATEGORY = 'EasyUse/Logic/Type' 36 | 37 | def execute(self, value): 38 | return (value,) 39 | ``` -------------------------------------------------------------------------------- /docs/easy ckptNames.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: easy ckptNames 4 | - Category: EasyUse/Util 5 | - Output node: False 6 | 7 | 此节点旨在简化管道中检查点名称的选择和管理过程。它允许用户轻松指定和检索各种检查点的名称，以便在模型加载或其他需要特定检查点标识的操作中使用。 8 | 9 | # Input types 10 | ## Required 11 | - ckpt_name 12 | - 指定要选择或管理的检查点名称。该参数对于确定后续操作中使用哪个检查点至关重要，直接影响节点的执行和结果。 13 | - Comfy dtype: COMBO[STRING] 14 | - Python dtype: str 15 | 16 | # Output types 17 | - ckpt_name 18 | - 返回指定的检查点名称，使其能够在进一步的处理或模型加载操作中使用。 19 | - Comfy dtype: * 20 | - Python dtype: str 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class setCkptName: 31 | @classmethod 32 | def INPUT_TYPES(cls): 33 | return {"required": { 34 | "ckpt_name": (folder_paths.get_filename_list("checkpoints"),), 35 | } 36 | } 37 | 38 | RETURN_TYPES = (AlwaysEqualProxy('*'),) 39 | RETURN_NAMES = ("ckpt_name",) 40 | FUNCTION = "set_name" 41 | CATEGORY = "EasyUse/Util" 42 | 43 | def set_name(self, ckpt_name): 44 | return (ckpt_name,) 45 | 46 | ``` 47 | -------------------------------------------------------------------------------- /docs/easy float.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: Float 3 | - Category: EasyUse/Logic/Type 4 | - Output node: False 5 | - Repo Ref: https://github.com/yolain/ComfyUI-Easy-Use.git 6 | 7 | 该节点提供基础的浮点数处理操作，专注于在指定精度内对小数值进行操作和计算。 8 | 9 | # Input types 10 | ## Required 11 | - value 12 | - ‘value’参数对节点的操作至关重要，它是节点操作或计算的输入小数值。 13 | - Comfy dtype: FLOAT 14 | - Python dtype: Union[Decimal, float, int] 15 | 16 | # Output types 17 | - float 18 | - 输出‘float’代表节点计算或操作的结果，反映了处理后的数值。 19 | - Comfy dtype: FLOAT 20 | - Python dtype: Union[Decimal, float] 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class Float: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'value': ('FLOAT', {'default': 0, 'step': 0.01})}} 32 | RETURN_TYPES = ('FLOAT',) 33 | RETURN_NAMES = ('float',) 34 | FUNCTION = 'execute' 35 | CATEGORY = 'EasyUse/Logic/Type' 36 | 37 | def execute(self, value): 38 | return (value,) 39 | ``` -------------------------------------------------------------------------------- /docs/easy imageCount.md: -------------------------------------------------------------------------------- 1 | 2 | # Documentation 3 | - Class name: easy imageCount 4 | - Category: EasyUse/Image 5 | - Output node: False 6 | 7 | easy imageCount 节点旨在统计给定批次中的图像数量，为工作流程中的图像集合提供了一种直观的量化方法。 8 | 9 | # Input types 10 | ## Required 11 | - images 12 | - images 参数代表要统计的图像批次。它对于确定存在的图像总数至关重要，直接影响节点的输出结果。 13 | - Comfy dtype: IMAGE 14 | - Python dtype: torch.Tensor 15 | 16 | # Output types 17 | - count 18 | - count 输出代表输入批次中的图像总数，提供一个简单的整数计数。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | 23 | ## Usage tips 24 | - Infra type: `CPU` 25 | - Common nodes: unknown 26 | 27 | 28 | ## Source code 29 | ```python 30 | class imageCount: 31 | @classmethod 32 | def INPUT_TYPES(s): 33 | return { 34 | "required": { 35 | "images": ("IMAGE",), 36 | } 37 | } 38 | 39 | CATEGORY = "EasyUse/Image" 40 | 41 | RETURN_TYPES = ("INT",) 42 | RETURN_NAMES = ("count",) 43 | FUNCTION = "get_count" 44 | 45 | def get_count(self, images): 46 | return (images.size(0),) 47 | 48 | ``` 49 | -------------------------------------------------------------------------------- /docs/easy int.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: Int 3 | - Category: EasyUse/Logic/Type 4 | - Output node: False 5 | - Repo Ref: https://github.com/yolain/ComfyUI-Easy-Use.git 6 | 7 | 该节点通过将输入转换为整数来促进算术运算的执行，确保计算过程中的数据完整性和类型一致性。 8 | 9 | # Input types 10 | ## Required 11 | - value 12 | - ‘value’参数至关重要，因为它是节点操作的主要输入。它通过确定将被转换为整数的数据来影响节点的处理。 13 | - Comfy dtype: INT 14 | - Python dtype: Union[int, float, str, Decimal] 15 | 16 | # Output types 17 | - int 18 | - 输出‘int’代表整数转换过程的结果，这对于确保在后续操作中使用正确的数据类型至关重要。 19 | - Comfy dtype: INT 20 | - Python dtype: int 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class Int: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'value': ('INT', {'default': 0})}} 32 | RETURN_TYPES = ('INT',) 33 | RETURN_NAMES = ('int',) 34 | FUNCTION = 'execute' 35 | CATEGORY = 'EasyUse/Logic/Type' 36 | 37 | def execute(self, value): 38 | return (value,) 39 | ``` -------------------------------------------------------------------------------- /docs/easy string.md: -------------------------------------------------------------------------------- 1 | # Documentation 2 | - Class name: String 3 | - Category: EasyUse/Logic/Type 4 | - Output node: False 5 | - Repo Ref: https://github.com/yolain/ComfyUI-Easy-Use.git 6 | 7 | 该节点便于对字符串数据进行处理和操作，使用户能够对文本输入执行各种操作。它旨在以直接的方式处理字符串的转换、变换和分析，使其成为涉及文本数据任务的基本组件。 8 | 9 | # Input types 10 | ## Required 11 | - value 12 | - ‘value’参数对于节点的操作至关重要，它代表将要处理的文本输入。它是所有字符串操作和转换的基础，直接影响输出结果和节点执行的有效性。 13 | - Comfy dtype: STRING 14 | - Python dtype: str 15 | 16 | # Output types 17 | - string 18 | - 输出‘string’代表节点执行的字符串处理的结果。它包含了对输入文本执行的操作的结果，标志着节点的主要功能及其对工作流的贡献。 19 | - Comfy dtype: STRING 20 | - Python dtype: str 21 | 22 | # Usage tips 23 | - Infra type: CPU 24 | 25 | # Source code 26 | ``` 27 | class String: 28 | 29 | @classmethod 30 | def INPUT_TYPES(s): 31 | return {'required': {'value': ('STRING', {'default': ''})}} 32 | RETURN_TYPES = ('STRING',) 33 | RETURN_NAMES = ('string',) 34 | FUNCTION = 'execute' 35 | CATEGORY = 'EasyUse/Logic/Type' 36 | 37 | def execute(self, value): 38 | return (value,) 39 | ``` -------------------------------------------------------------------------------- /examples/2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/examples/2.png -------------------------------------------------------------------------------- /logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/logo.png -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [project] 2 | name = "comfyui-nodes-docs" 3 | description = "This is a plugin for displaying documentation for each comfyui node. " 4 | version = "1.1.1" 5 | license = "LICENSE" 6 | 7 | [project.urls] 8 | Repository = "https://github.com/CavinHuang/comfyui-nodes-docs" 9 | # Used by Comfy Registry https://comfyregistry.org 10 | 11 | [tool.comfy] 12 | PublisherId = "cavinhuang" 13 | DisplayName = "comfyui-nodes-docs" 14 | Icon = "" 15 | -------------------------------------------------------------------------------- /server/__init__.py: -------------------------------------------------------------------------------- 1 | from .request import * -------------------------------------------------------------------------------- /web/comfyui/constants.js: -------------------------------------------------------------------------------- 1 | export const ENABLED_SETTING_KEY = 'comfyui-nodes-docs.enabled' 2 | -------------------------------------------------------------------------------- /web/comfyui/index.css: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CavinHuang/comfyui-nodes-docs/2da55d0ba1801ea8374d3f719c4fc1b95db1e585/web/comfyui/index.css -------------------------------------------------------------------------------- /web/comfyui/utils.js: -------------------------------------------------------------------------------- 1 | 2 | /** 3 | * 节流函数 4 | */ 5 | export const throttle = function(fn, delay) { 6 | let lastTime = 0 7 | return function() { 8 | const now = Date.now() 9 | if(now - lastTime > delay) { 10 | fn.apply(this, arguments) 11 | lastTime = now 12 | } 13 | } 14 | } 15 | 16 | 17 | export function svgToBase64(svgString) { 18 | // 对SVG字符串进行编码 19 | const encodedSvg = encodeURIComponent(svgString).replace(/%([0-9A-F]{2})/g, function(match, p1) { 20 | return String.fromCharCode('0x' + p1); 21 | }); 22 | 23 | // 将编码后的字符串转换为base64 24 | const base64 = btoa(encodedSvg); 25 | return 'data:image/svg+xml;base64,' + base64; 26 | } --------------------------------------------------------------------------------