diff --git a/comfy_extras/nodes_advanced_samplers.py b/comfy_extras/nodes_advanced_samplers.py index 567c37be0..20717ca38 100644 --- a/comfy_extras/nodes_advanced_samplers.py +++ b/comfy_extras/nodes_advanced_samplers.py @@ -45,7 +45,7 @@ class SamplerLCMUpscale(io.ComfyNode): def define_schema(cls) -> io.Schema: return io.Schema( node_id="SamplerLCMUpscale", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[ io.Float.Input("scale_ratio", default=1.0, min=0.1, max=20.0, step=0.01, advanced=True), io.Int.Input("scale_steps", default=-1, min=-1, max=1000, step=1, advanced=True), @@ -123,7 +123,7 @@ class SamplerEulerCFGpp(io.ComfyNode): return io.Schema( node_id="SamplerEulerCFGpp", display_name="SamplerEulerCFG++", - category="experimental", # "sampling/custom_sampling/samplers" + category="experimental", # "sampling/samplers" inputs=[ io.Combo.Input("version", options=["regular", "alternative"], advanced=True), ], diff --git a/comfy_extras/nodes_align_your_steps.py b/comfy_extras/nodes_align_your_steps.py index 4fc511d2c..307f41337 100644 --- a/comfy_extras/nodes_align_your_steps.py +++ b/comfy_extras/nodes_align_your_steps.py @@ -29,7 +29,7 @@ class AlignYourStepsScheduler(io.ComfyNode): return io.Schema( node_id="AlignYourStepsScheduler", search_aliases=["AYS scheduler"], - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Combo.Input("model_type", options=["SD1", "SDXL", "SVD"]), io.Int.Input("steps", default=10, min=1, max=10000), diff --git a/comfy_extras/nodes_ar_video.py b/comfy_extras/nodes_ar_video.py index b36588b14..1a15facfa 100644 --- a/comfy_extras/nodes_ar_video.py +++ b/comfy_extras/nodes_ar_video.py @@ -53,7 +53,7 @@ class SamplerARVideo(io.ComfyNode): return io.Schema( node_id="SamplerARVideo", display_name="Sampler AR Video", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[ io.Int.Input( "num_frame_per_block", diff --git a/comfy_extras/nodes_bg_removal.py b/comfy_extras/nodes_bg_removal.py index 8d046b8d4..793fd802b 100644 --- a/comfy_extras/nodes_bg_removal.py +++ b/comfy_extras/nodes_bg_removal.py @@ -34,6 +34,7 @@ class RemoveBackground(IO.ComfyNode): node_id="RemoveBackground", display_name="Remove Background", category="image/background removal", + description="Generates a foreground mask to remove the background from an image using a background removal model.", inputs=[ IO.Image.Input("image", tooltip="Input image to remove the background from"), IO.BackgroundRemoval.Input("bg_removal_model", tooltip="Background removal model used to generate the mask") diff --git a/comfy_extras/nodes_canny.py b/comfy_extras/nodes_canny.py index 648b4279d..462f6fea0 100644 --- a/comfy_extras/nodes_canny.py +++ b/comfy_extras/nodes_canny.py @@ -11,9 +11,9 @@ class Canny(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="Canny", - display_name="Canny", + display_name="Detect Edges (Canny)", search_aliases=["edge detection", "outline", "contour detection", "line art"], - category="image/preprocessors", + category="image/filters", essentials_category="Image Tools", inputs=[ io.Image.Input("image"), diff --git a/comfy_extras/nodes_compositing.py b/comfy_extras/nodes_compositing.py index 720efc629..8fcbe720e 100644 --- a/comfy_extras/nodes_compositing.py +++ b/comfy_extras/nodes_compositing.py @@ -111,7 +111,7 @@ class PorterDuffImageComposite(io.ComfyNode): node_id="PorterDuffImageComposite", search_aliases=["alpha composite", "blend modes", "layer blend", "transparency blend"], display_name="Porter-Duff Image Composite", - category="mask/compositing", + category="image/compositing", inputs=[ io.Image.Input("source"), io.Mask.Input("source_alpha"), @@ -168,7 +168,7 @@ class SplitImageWithAlpha(io.ComfyNode): node_id="SplitImageWithAlpha", search_aliases=["extract alpha", "separate transparency", "remove alpha"], display_name="Split Image with Alpha", - category="mask/compositing", + category="image/compositing", inputs=[ io.Image.Input("image"), ], @@ -192,7 +192,7 @@ class JoinImageWithAlpha(io.ComfyNode): node_id="JoinImageWithAlpha", search_aliases=["add transparency", "apply alpha", "composite alpha", "RGBA"], display_name="Join Image with Alpha", - category="mask/compositing", + category="image/compositing", inputs=[ io.Image.Input("image"), io.Mask.Input("alpha"), diff --git a/comfy_extras/nodes_custom_sampler.py b/comfy_extras/nodes_custom_sampler.py index c67145d2d..58b6d3806 100644 --- a/comfy_extras/nodes_custom_sampler.py +++ b/comfy_extras/nodes_custom_sampler.py @@ -17,7 +17,7 @@ class BasicScheduler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="BasicScheduler", - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Model.Input("model"), io.Combo.Input("scheduler", options=comfy.samplers.SCHEDULER_NAMES), @@ -47,7 +47,7 @@ class KarrasScheduler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="KarrasScheduler", - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Int.Input("steps", default=20, min=1, max=10000), io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, advanced=True), @@ -69,7 +69,7 @@ class ExponentialScheduler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="ExponentialScheduler", - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Int.Input("steps", default=20, min=1, max=10000), io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, advanced=True), @@ -90,7 +90,7 @@ class PolyexponentialScheduler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="PolyexponentialScheduler", - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Int.Input("steps", default=20, min=1, max=10000), io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, advanced=True), @@ -112,7 +112,7 @@ class LaplaceScheduler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="LaplaceScheduler", - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Int.Input("steps", default=20, min=1, max=10000), io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, advanced=True), @@ -136,7 +136,7 @@ class SDTurboScheduler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SDTurboScheduler", - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Model.Input("model"), io.Int.Input("steps", default=1, min=1, max=10), @@ -160,7 +160,7 @@ class BetaSamplingScheduler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="BetaSamplingScheduler", - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Model.Input("model"), io.Int.Input("steps", default=20, min=1, max=10000), @@ -182,7 +182,7 @@ class VPScheduler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="VPScheduler", - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Int.Input("steps", default=20, min=1, max=10000), io.Float.Input("beta_d", default=19.9, min=0.0, max=5000.0, step=0.01, round=False, advanced=True), #TODO: fix default values @@ -204,7 +204,7 @@ class SplitSigmas(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SplitSigmas", - category="sampling/custom_sampling/sigmas", + category="sampling/sigmas", inputs=[ io.Sigmas.Input("sigmas"), io.Int.Input("step", default=0, min=0, max=10000), @@ -228,7 +228,7 @@ class SplitSigmasDenoise(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SplitSigmasDenoise", - category="sampling/custom_sampling/sigmas", + category="sampling/sigmas", inputs=[ io.Sigmas.Input("sigmas"), io.Float.Input("denoise", default=1.0, min=0.0, max=1.0, step=0.01), @@ -254,7 +254,7 @@ class FlipSigmas(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="FlipSigmas", - category="sampling/custom_sampling/sigmas", + category="sampling/sigmas", inputs=[io.Sigmas.Input("sigmas")], outputs=[io.Sigmas.Output()] ) @@ -276,7 +276,7 @@ class SetFirstSigma(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SetFirstSigma", - category="sampling/custom_sampling/sigmas", + category="sampling/sigmas", inputs=[ io.Sigmas.Input("sigmas"), io.Float.Input("sigma", default=136.0, min=0.0, max=20000.0, step=0.001, round=False), @@ -298,7 +298,7 @@ class ExtendIntermediateSigmas(io.ComfyNode): return io.Schema( node_id="ExtendIntermediateSigmas", search_aliases=["interpolate sigmas"], - category="sampling/custom_sampling/sigmas", + category="sampling/sigmas", inputs=[ io.Sigmas.Input("sigmas"), io.Int.Input("steps", default=2, min=1, max=100), @@ -351,7 +351,7 @@ class SamplingPercentToSigma(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SamplingPercentToSigma", - category="sampling/custom_sampling/sigmas", + category="sampling/sigmas", inputs=[ io.Model.Input("model"), io.Float.Input("sampling_percent", default=0.0, min=0.0, max=1.0, step=0.0001), @@ -379,7 +379,7 @@ class KSamplerSelect(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="KSamplerSelect", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[io.Combo.Input("sampler_name", options=comfy.samplers.SAMPLER_NAMES)], outputs=[io.Sampler.Output()] ) @@ -396,7 +396,7 @@ class SamplerDPMPP_3M_SDE(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SamplerDPMPP_3M_SDE", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[ io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True), io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True), @@ -421,7 +421,7 @@ class SamplerDPMPP_2M_SDE(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SamplerDPMPP_2M_SDE", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[ io.Combo.Input("solver_type", options=['midpoint', 'heun']), io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True), @@ -448,7 +448,7 @@ class SamplerDPMPP_SDE(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SamplerDPMPP_SDE", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[ io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True), io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True), @@ -474,7 +474,7 @@ class SamplerDPMPP_2S_Ancestral(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SamplerDPMPP_2S_Ancestral", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[ io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False), io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False), @@ -494,7 +494,7 @@ class SamplerEulerAncestral(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SamplerEulerAncestral", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[ io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True), io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True), @@ -515,7 +515,7 @@ class SamplerEulerAncestralCFGPP(io.ComfyNode): return io.Schema( node_id="SamplerEulerAncestralCFGPP", display_name="SamplerEulerAncestralCFG++", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[ io.Float.Input("eta", default=1.0, min=0.0, max=1.0, step=0.01, round=False), io.Float.Input("s_noise", default=1.0, min=0.0, max=10.0, step=0.01, round=False), @@ -537,7 +537,7 @@ class SamplerLMS(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SamplerLMS", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[io.Int.Input("order", default=4, min=1, max=100, advanced=True)], outputs=[io.Sampler.Output()] ) @@ -554,7 +554,7 @@ class SamplerDPMAdaptative(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SamplerDPMAdaptative", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[ io.Int.Input("order", default=3, min=2, max=3, advanced=True), io.Float.Input("rtol", default=0.05, min=0.0, max=100.0, step=0.01, round=False, advanced=True), @@ -585,7 +585,7 @@ class SamplerER_SDE(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SamplerER_SDE", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[ io.Combo.Input("solver_type", options=["ER-SDE", "Reverse-time SDE", "ODE"]), io.Int.Input("max_stage", default=3, min=1, max=3, advanced=True), @@ -623,7 +623,7 @@ class SamplerSASolver(io.ComfyNode): return io.Schema( node_id="SamplerSASolver", search_aliases=["sde"], - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[ io.Model.Input("model"), io.Float.Input("eta", default=1.0, min=0.0, max=10.0, step=0.01, round=False, advanced=True), @@ -668,7 +668,7 @@ class SamplerSEEDS2(io.ComfyNode): return io.Schema( node_id="SamplerSEEDS2", search_aliases=["sde", "exp heun"], - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[ io.Combo.Input("solver_type", options=["phi_1", "phi_2"]), io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, tooltip="Stochastic strength", advanced=True), @@ -793,7 +793,8 @@ class BasicGuider(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="BasicGuider", - category="sampling/custom_sampling/guiders", + display_name="Basic Guider", + category="sampling/guiders", inputs=[ io.Model.Input("model"), io.Conditioning.Input("conditioning"), @@ -814,7 +815,8 @@ class CFGGuider(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="CFGGuider", - category="sampling/custom_sampling/guiders", + display_name="CFG Guider", + category="sampling/guiders", inputs=[ io.Model.Input("model"), io.Conditioning.Input("positive"), @@ -868,7 +870,8 @@ class DualCFGGuider(io.ComfyNode): return io.Schema( node_id="DualCFGGuider", search_aliases=["dual prompt guidance"], - category="sampling/custom_sampling/guiders", + display_name="Dual CFG Guider", + category="sampling/guiders", inputs=[ io.Model.Input("model"), io.Conditioning.Input("cond1"), @@ -896,7 +899,7 @@ class DisableNoise(io.ComfyNode): return io.Schema( node_id="DisableNoise", search_aliases=["zero noise"], - category="sampling/custom_sampling/noise", + category="sampling/noise", inputs=[], outputs=[io.Noise.Output()] ) @@ -913,7 +916,7 @@ class RandomNoise(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="RandomNoise", - category="sampling/custom_sampling/noise", + category="sampling/noise", inputs=[io.Int.Input("noise_seed", default=0, min=0, max=0xffffffffffffffff, control_after_generate=True)], outputs=[io.Noise.Output()] ) diff --git a/comfy_extras/nodes_flux.py b/comfy_extras/nodes_flux.py index 5e04a5f77..997f21c09 100644 --- a/comfy_extras/nodes_flux.py +++ b/comfy_extras/nodes_flux.py @@ -215,7 +215,7 @@ class Flux2Scheduler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="Flux2Scheduler", - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Int.Input("steps", default=20, min=1, max=4096), io.Int.Input("width", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=1), @@ -263,7 +263,7 @@ class FluxKVCache(io.ComfyNode): node_id="FluxKVCache", display_name="Flux KV Cache", description="Enables KV Cache optimization for reference images on Flux family models.", - category="", + category="experimental", is_experimental=True, inputs=[ io.Model.Input("model", tooltip="The model to use KV Cache on."), diff --git a/comfy_extras/nodes_gits.py b/comfy_extras/nodes_gits.py index d48483862..0b7666524 100644 --- a/comfy_extras/nodes_gits.py +++ b/comfy_extras/nodes_gits.py @@ -340,7 +340,7 @@ class GITSScheduler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="GITSScheduler", - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Float.Input("coeff", default=1.20, min=0.80, max=1.50, step=0.05, advanced=True), io.Int.Input("steps", default=10, min=2, max=1000), diff --git a/comfy_extras/nodes_images.py b/comfy_extras/nodes_images.py index 1ac740d1d..07faa01d4 100644 --- a/comfy_extras/nodes_images.py +++ b/comfy_extras/nodes_images.py @@ -160,7 +160,7 @@ class ImageAddNoise(IO.ComfyNode): node_id="ImageAddNoise", search_aliases=["film grain"], display_name="Add Noise to Image", - category="image/postprocessing", + category="image/filters", inputs=[ IO.Image.Input("image"), IO.Int.Input( @@ -192,7 +192,8 @@ class SaveAnimatedWEBP(IO.ComfyNode): def define_schema(cls): return IO.Schema( node_id="SaveAnimatedWEBP", - category="image/animation", + display_name="Save Animated WEBP", + category="image", inputs=[ IO.Image.Input("images"), IO.String.Input("filename_prefix", default="ComfyUI"), @@ -229,7 +230,8 @@ class SaveAnimatedPNG(IO.ComfyNode): def define_schema(cls): return IO.Schema( node_id="SaveAnimatedPNG", - category="image/animation", + display_name="Save Animated PNG", + category="image", inputs=[ IO.Image.Input("images"), IO.String.Input("filename_prefix", default="ComfyUI"), @@ -491,7 +493,7 @@ class SaveSVGNode(IO.ComfyNode): search_aliases=["export vector", "save vector graphics"], display_name="Save SVG", description="Save SVG files on disk.", - category="image/save", + category="image", inputs=[ IO.SVG.Input("svg"), IO.String.Input( diff --git a/comfy_extras/nodes_lt.py b/comfy_extras/nodes_lt.py index 3dc1199c2..5989e8f93 100644 --- a/comfy_extras/nodes_lt.py +++ b/comfy_extras/nodes_lt.py @@ -502,7 +502,7 @@ class LTXVScheduler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="LTXVScheduler", - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Int.Input("steps", default=20, min=1, max=10000), io.Float.Input("max_shift", default=2.05, min=0.0, max=100.0, step=0.01), diff --git a/comfy_extras/nodes_mask.py b/comfy_extras/nodes_mask.py index 96ee1a0f8..ac0824e7f 100644 --- a/comfy_extras/nodes_mask.py +++ b/comfy_extras/nodes_mask.py @@ -83,7 +83,7 @@ class ImageCompositeMasked(IO.ComfyNode): node_id="ImageCompositeMasked", search_aliases=["overlay", "layer", "paste image", "images composition"], display_name="Image Composite Masked", - category="image", + category="image/compositing", inputs=[ IO.Image.Input("destination"), IO.Image.Input("source"), @@ -112,7 +112,7 @@ class MaskToImage(IO.ComfyNode): node_id="MaskToImage", search_aliases=["convert mask"], display_name="Convert Mask to Image", - category="mask", + category="image/mask", inputs=[ IO.Mask.Input("mask"), ], @@ -134,7 +134,7 @@ class ImageToMask(IO.ComfyNode): node_id="ImageToMask", search_aliases=["extract channel", "channel to mask"], display_name="Convert Image to Mask", - category="mask", + category="image/mask", inputs=[ IO.Image.Input("image"), IO.Combo.Input("channel", options=["red", "green", "blue", "alpha"]), @@ -157,7 +157,8 @@ class ImageColorToMask(IO.ComfyNode): return IO.Schema( node_id="ImageColorToMask", search_aliases=["color keying", "chroma key"], - category="mask", + display_name="Convert Image Color to Mask", + category="image/mask", inputs=[ IO.Image.Input("image"), IO.Int.Input("color", default=0, min=0, max=0xFFFFFF, step=1, display_mode=IO.NumberDisplay.number), @@ -180,7 +181,8 @@ class SolidMask(IO.ComfyNode): def define_schema(cls): return IO.Schema( node_id="SolidMask", - category="mask", + display_name="Create Solid Mask", + category="image/mask", inputs=[ IO.Float.Input("value", default=1.0, min=0.0, max=1.0, step=0.01), IO.Int.Input("width", default=512, min=1, max=nodes.MAX_RESOLUTION, step=1), @@ -204,7 +206,7 @@ class InvertMask(IO.ComfyNode): node_id="InvertMask", search_aliases=["reverse mask", "flip mask"], display_name="Invert Mask", - category="mask", + category="image/mask", inputs=[ IO.Mask.Input("mask"), ], @@ -226,7 +228,7 @@ class CropMask(IO.ComfyNode): node_id="CropMask", search_aliases=["cut mask", "extract mask region", "mask slice"], display_name="Crop Mask", - category="mask", + category="image/mask", inputs=[ IO.Mask.Input("mask"), IO.Int.Input("x", default=0, min=0, max=nodes.MAX_RESOLUTION, step=1), @@ -253,7 +255,7 @@ class MaskComposite(IO.ComfyNode): node_id="MaskComposite", search_aliases=["combine masks", "blend masks", "layer masks", "masks composition"], display_name="Combine Masks", - category="mask", + category="image/mask", inputs=[ IO.Mask.Input("destination"), IO.Mask.Input("source"), @@ -304,7 +306,7 @@ class FeatherMask(IO.ComfyNode): node_id="FeatherMask", search_aliases=["soft edge mask", "blur mask edges", "gradient mask edge"], display_name="Feather Mask", - category="mask", + category="image/mask", inputs=[ IO.Mask.Input("mask"), IO.Int.Input("left", default=0, min=0, max=nodes.MAX_RESOLUTION, step=1), @@ -352,7 +354,7 @@ class GrowMask(IO.ComfyNode): node_id="GrowMask", search_aliases=["expand mask", "shrink mask"], display_name="Grow Mask", - category="mask", + category="image/mask", inputs=[ IO.Mask.Input("mask"), IO.Int.Input("expand", default=0, min=-nodes.MAX_RESOLUTION, max=nodes.MAX_RESOLUTION, step=1), @@ -388,7 +390,8 @@ class ThresholdMask(IO.ComfyNode): return IO.Schema( node_id="ThresholdMask", search_aliases=["binary mask"], - category="mask", + display_name="Threshold Mask", + category="image/mask", inputs=[ IO.Mask.Input("mask"), IO.Float.Input("value", default=0.5, min=0.0, max=1.0, step=0.01), @@ -414,7 +417,7 @@ class MaskPreview(IO.ComfyNode): node_id="MaskPreview", search_aliases=["show mask", "view mask", "inspect mask", "debug mask"], display_name="Preview Mask", - category="mask", + category="image/mask", description="Saves the input images to your ComfyUI output directory.", inputs=[ IO.Mask.Input("mask"), diff --git a/comfy_extras/nodes_morphology.py b/comfy_extras/nodes_morphology.py index c01b9436d..0142040dd 100644 --- a/comfy_extras/nodes_morphology.py +++ b/comfy_extras/nodes_morphology.py @@ -13,8 +13,8 @@ class Morphology(io.ComfyNode): return io.Schema( node_id="Morphology", search_aliases=["erode", "dilate"], - display_name="ImageMorphology", - category="image/postprocessing", + display_name="Apply Morphology", + category="image/filters", inputs=[ io.Image.Input("image"), io.Combo.Input( diff --git a/comfy_extras/nodes_nop.py b/comfy_extras/nodes_nop.py index 953061bcb..f9c1357c3 100644 --- a/comfy_extras/nodes_nop.py +++ b/comfy_extras/nodes_nop.py @@ -13,7 +13,7 @@ class wanBlockSwap(io.ComfyNode): return io.Schema( node_id="wanBlockSwap", category="", - description="NOP", + description="Intercept wanBlockSwap custom node that causes major instability and make it no-op.", inputs=[ io.Model.Input("model"), ], diff --git a/comfy_extras/nodes_number_convert.py b/comfy_extras/nodes_number_convert.py index ab3f2aa8a..e38a33c15 100644 --- a/comfy_extras/nodes_number_convert.py +++ b/comfy_extras/nodes_number_convert.py @@ -20,7 +20,7 @@ class NumberConvertNode(io.ComfyNode): def define_schema(cls) -> io.Schema: return io.Schema( node_id="ComfyNumberConvert", - display_name="Number Convert", + display_name="Convert Number", category="utils", search_aliases=[ "int to float", "float to int", "number convert", diff --git a/comfy_extras/nodes_optimalsteps.py b/comfy_extras/nodes_optimalsteps.py index 73f0104d8..5beeaa7db 100644 --- a/comfy_extras/nodes_optimalsteps.py +++ b/comfy_extras/nodes_optimalsteps.py @@ -31,7 +31,7 @@ class OptimalStepsScheduler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="OptimalStepsScheduler", - category="sampling/custom_sampling/schedulers", + category="sampling/schedulers", inputs=[ io.Combo.Input("model_type", options=["FLUX", "Wan", "Chroma"]), io.Int.Input("steps", default=20, min=3, max=1000), diff --git a/comfy_extras/nodes_post_processing.py b/comfy_extras/nodes_post_processing.py index 1fa14d2d2..c30052d76 100644 --- a/comfy_extras/nodes_post_processing.py +++ b/comfy_extras/nodes_post_processing.py @@ -22,7 +22,7 @@ class Blend(io.ComfyNode): node_id="ImageBlend", search_aliases=["mix images"], display_name="Blend Images", - category="image/postprocessing", + category="image/filters", essentials_category="Image Tools", inputs=[ io.Image.Input("image1"), @@ -80,8 +80,8 @@ class Blur(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="ImageBlur", - display_name="Image Blur", - category="image/postprocessing", + display_name="Blur Image", + category="image/filters", inputs=[ io.Image.Input("image"), io.Int.Input("blur_radius", default=1, min=1, max=31, step=1), @@ -117,7 +117,7 @@ class Quantize(io.ComfyNode): return io.Schema( node_id="ImageQuantize", display_name="Quantize Image", - category="image/postprocessing", + category="image/filters", inputs=[ io.Image.Input("image"), io.Int.Input("colors", default=256, min=1, max=256, step=1), @@ -183,7 +183,7 @@ class Sharpen(io.ComfyNode): return io.Schema( node_id="ImageSharpen", display_name="Sharpen Image", - category="image/postprocessing", + category="image/filters", inputs=[ io.Image.Input("image"), io.Int.Input("sharpen_radius", default=1, min=1, max=31, step=1, advanced=True), @@ -595,7 +595,7 @@ class BatchMasksNode(io.ComfyNode): node_id="BatchMasksNode", search_aliases=["combine masks", "stack masks", "merge masks"], display_name="Batch Masks", - category="mask", + category="image/mask", inputs=[ io.Autogrow.Input("masks", template=autogrow_template) ], @@ -670,8 +670,8 @@ class ColorTransfer(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="ColorTransfer", - display_name="Color Transfer", - category="image/postprocessing", + display_name="Transfer Color", + category="image/filters", description="Match the colors of one image to another using various algorithms.", search_aliases=["color match", "color grading", "color correction", "match colors", "color transform", "mkl", "reinhard", "histogram"], inputs=[ diff --git a/comfy_extras/nodes_rtdetr.py b/comfy_extras/nodes_rtdetr.py index a321577c7..e5a9b3902 100644 --- a/comfy_extras/nodes_rtdetr.py +++ b/comfy_extras/nodes_rtdetr.py @@ -15,7 +15,7 @@ class RTDETR_detect(io.ComfyNode): return io.Schema( node_id="RTDETR_detect", display_name="RT-DETR Detect", - category="detection", + category="image/detection", search_aliases=["bbox", "bounding box", "object detection", "coco"], inputs=[ io.Model.Input("model", display_name="model"), @@ -71,7 +71,7 @@ class DrawBBoxes(io.ComfyNode): return io.Schema( node_id="DrawBBoxes", display_name="Draw BBoxes", - category="detection", + category="image/detection", search_aliases=["bbox", "bounding box", "object detection", "rt_detr", "visualize detections", "coco"], inputs=[ io.Image.Input("image", optional=True), diff --git a/comfy_extras/nodes_sam3.py b/comfy_extras/nodes_sam3.py index 4ea9221e9..daac52f9b 100644 --- a/comfy_extras/nodes_sam3.py +++ b/comfy_extras/nodes_sam3.py @@ -93,7 +93,7 @@ class SAM3_Detect(io.ComfyNode): return io.Schema( node_id="SAM3_Detect", display_name="SAM3 Detect", - category="detection", + category="image/detection", search_aliases=["sam3", "segment anything", "open vocabulary", "text detection", "segment"], inputs=[ io.Model.Input("model", display_name="model"), @@ -265,7 +265,7 @@ class SAM3_VideoTrack(io.ComfyNode): return io.Schema( node_id="SAM3_VideoTrack", display_name="SAM3 Video Track", - category="detection", + category="image/detection", search_aliases=["sam3", "video", "track", "propagate"], inputs=[ io.Image.Input("images", display_name="images", tooltip="Video frames as batched images"), @@ -320,7 +320,7 @@ class SAM3_TrackPreview(io.ComfyNode): return io.Schema( node_id="SAM3_TrackPreview", display_name="SAM3 Track Preview", - category="detection", + category="image/detection", inputs=[ SAM3TrackData.Input("track_data", display_name="track_data"), io.Image.Input("images", display_name="images", optional=True), @@ -478,7 +478,7 @@ class SAM3_TrackToMask(io.ComfyNode): return io.Schema( node_id="SAM3_TrackToMask", display_name="SAM3 Track to Mask", - category="detection", + category="image/detection", inputs=[ SAM3TrackData.Input("track_data", display_name="track_data"), io.String.Input("object_indices", display_name="object_indices", default="", diff --git a/comfy_extras/nodes_sdpose.py b/comfy_extras/nodes_sdpose.py index 96b6821bd..20d459b00 100644 --- a/comfy_extras/nodes_sdpose.py +++ b/comfy_extras/nodes_sdpose.py @@ -353,7 +353,8 @@ class SDPoseDrawKeypoints(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SDPoseDrawKeypoints", - category="image/preprocessors", + display_name="SDPose Draw Keypoints", + category="image/detection", search_aliases=["openpose", "pose detection", "preprocessor", "keypoints", "pose"], inputs=[ io.Custom("POSE_KEYPOINT").Input("keypoints"), @@ -421,7 +422,8 @@ class SDPoseKeypointExtractor(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SDPoseKeypointExtractor", - category="image/preprocessors", + display_name="SDPose Keypoint Extractor", + category="image/detection", search_aliases=["openpose", "pose detection", "preprocessor", "keypoints", "sdpose"], description="Extract pose keypoints from images using the SDPose model: https://huggingface.co/Comfy-Org/SDPose/tree/main/checkpoints", inputs=[ @@ -595,7 +597,8 @@ class SDPoseFaceBBoxes(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="SDPoseFaceBBoxes", - category="image/preprocessors", + display_name="SDPose Face Bounding Boxes", + category="image/detection", search_aliases=["face bbox", "face bounding box", "pose", "keypoints"], inputs=[ io.Custom("POSE_KEYPOINT").Input("keypoints"), @@ -652,7 +655,8 @@ class CropByBBoxes(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="CropByBBoxes", - category="image/preprocessors", + display_name="Crop By Bounding Boxes", + category="image/transform", search_aliases=["crop", "face crop", "bbox crop", "pose", "bounding box"], description="Crop and resize regions from the input image batch based on provided bounding boxes.", inputs=[ diff --git a/comfy_extras/nodes_video_model.py b/comfy_extras/nodes_video_model.py index 0f3881a24..8f19895a1 100644 --- a/comfy_extras/nodes_video_model.py +++ b/comfy_extras/nodes_video_model.py @@ -65,7 +65,7 @@ class VideoLinearCFGGuidance: RETURN_TYPES = ("MODEL",) FUNCTION = "patch" - CATEGORY = "sampling/video_models" + CATEGORY = "sampling/guiders" def patch(self, model, min_cfg): def linear_cfg(args): @@ -89,7 +89,7 @@ class VideoTriangleCFGGuidance: RETURN_TYPES = ("MODEL",) FUNCTION = "patch" - CATEGORY = "sampling/video_models" + CATEGORY = "sampling/guiders" def patch(self, model, min_cfg): def linear_cfg(args): @@ -157,5 +157,7 @@ NODE_CLASS_MAPPINGS = { } NODE_DISPLAY_NAME_MAPPINGS = { - "ImageOnlyCheckpointLoader": "Image Only Checkpoint Loader (img2vid model)", + "ImageOnlyCheckpointLoader": "Load Checkpoint Image Only (img2vid model)", + "VideoLinearCFGGuidance": "Video Linear CFG Guidance", + "VideoTriangleCFGGuidance": "Video Triangle CFG Guidance", } diff --git a/comfy_extras/nodes_void.py b/comfy_extras/nodes_void.py index e7a8f3757..be724371a 100644 --- a/comfy_extras/nodes_void.py +++ b/comfy_extras/nodes_void.py @@ -122,7 +122,8 @@ class VOIDQuadmaskPreprocess(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="VOIDQuadmaskPreprocess", - category="mask/video", + display_name="VOID Quadmask Preprocessor", + category="image/mask", inputs=[ io.Mask.Input("mask"), io.Int.Input("dilate_width", default=0, min=0, max=50, step=1, @@ -392,7 +393,7 @@ class VOIDWarpedNoiseSource(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="VOIDWarpedNoiseSource", - category="sampling/custom_sampling/noise", + category="sampling/noise", inputs=[ io.Latent.Input("warped_noise", tooltip="Warped noise latent from VOIDWarpedNoise"), @@ -454,7 +455,7 @@ class VOIDSampler(io.ComfyNode): def define_schema(cls): return io.Schema( node_id="VOIDSampler", - category="sampling/custom_sampling/samplers", + category="sampling/samplers", inputs=[], outputs=[io.Sampler.Output()], ) diff --git a/nodes.py b/nodes.py index 2b63f9fbb..223154d52 100644 --- a/nodes.py +++ b/nodes.py @@ -691,7 +691,7 @@ class LoraLoader: FUNCTION = "load_lora" CATEGORY = "loaders" - DESCRIPTION = "LoRAs are used to modify diffusion and CLIP models, altering the way in which latents are denoised such as applying styles. Multiple LoRA nodes can be linked together." + DESCRIPTION = "This LoRA loader is used to modify both diffusion and CLIP models, altering the way in which latents are denoised such as applying styles. Multiple LoRA nodes can be linked together." SEARCH_ALIASES = ["lora", "load lora", "apply lora", "lora loader", "lora model"] def load_lora(self, model, clip, lora_name, strength_model, strength_clip): @@ -721,6 +721,7 @@ class LoraLoaderModelOnly(LoraLoader): "strength_model": ("FLOAT", {"default": 1.0, "min": -100.0, "max": 100.0, "step": 0.01}), }} RETURN_TYPES = ("MODEL",) + DESCRIPTION = "This LoRAs loader is used to modify the diffusion model, altering the way in which latents are denoised such as applying styles. Multiple LoRA nodes can be linked together." FUNCTION = "load_lora_model_only" def load_lora_model_only(self, model, lora_name, strength_model): @@ -1771,7 +1772,7 @@ class LoadImageMask(LoadImage): } } - CATEGORY = "mask" + CATEGORY = "image" RETURN_TYPES = ("MASK",) FUNCTION = "load_image_mask"