{"KSampler": {"input": {"required": {"model": ["MODEL", {"tooltip": "The model used for denoising the input latent."}], "seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615, "tooltip": "The random seed used for creating the noise."}], "steps": ["INT", {"default": 20, "min": 1, "max": 10000, "tooltip": "The number of steps used in the denoising process."}], "cfg": ["FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0, "step": 0.1, "round": 0.01, "tooltip": "The Classifier-Free Guidance scale balances creativity and adherence to the prompt. Higher values result in images more closely matching the prompt however too high values will negatively impact quality."}], "sampler_name": [["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2", "dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_2s_ancestral_cfg_pp", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "ipndm", "ipndm_v", "deis", "ddim", "uni_pc", "uni_pc_bh2"], {"tooltip": "The algorithm used when sampling, this can affect the quality, speed, and style of the generated output."}], "scheduler": [["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta"], {"tooltip": "The scheduler controls how noise is gradually removed to form the image."}], "positive": ["CONDITIONING", {"tooltip": "The conditioning describing the attributes you want to include in the image."}], "negative": ["CONDITIONING", {"tooltip": "The conditioning describing the attributes you want to exclude from the image."}], "latent_image": ["LATENT", {"tooltip": "The latent image to denoise."}], "denoise": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "The amount of denoising applied, lower values will maintain the structure of the initial image allowing for image to image sampling."}]}}, "input_order": {"required": ["model", "seed", "steps", "cfg", "sampler_name", "scheduler", "positive", "negative", "latent_image", "denoise"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "KSampler", "display_name": "KSampler", "description": "Uses the provided model, positive and negative conditioning to denoise the latent image.", "python_module": "nodes", "category": "sampling", "output_node": false, "output_tooltips": ["The denoised latent."]}, "CheckpointLoaderSimple": {"input": {"required": {"ckpt_name": [["juggernautXL_juggXIByRundiffusion.safetensors", "realvisxlV50_v50Bakedvae.safetensors"], {"tooltip": "The name of the checkpoint (model) to load."}]}}, "input_order": {"required": ["ckpt_name"]}, "output": ["MODEL", "CLIP", "VAE"], "output_is_list": [false, false, false], "output_name": ["MODEL", "CLIP", "VAE"], "name": "CheckpointLoaderSimple", "display_name": "Load Checkpoint", "description": "Loads a diffusion model checkpoint, diffusion models are used to denoise latents.", "python_module": "nodes", "category": "loaders", "output_node": false, "output_tooltips": ["The model used for denoising latents.", "The CLIP model used for encoding text prompts.", "The VAE model used for encoding and decoding images to and from latent space."]}, "CLIPTextEncode": {"input": {"required": {"text": ["STRING", {"multiline": true, "dynamicPrompts": true, "tooltip": "The text to be encoded."}], "clip": ["CLIP", {"tooltip": "The CLIP model used for encoding the text."}]}}, "input_order": {"required": ["text", "clip"]}, "output": ["CONDITIONING"], "output_is_list": [false], "output_name": ["CONDITIONING"], "name": "CLIPTextEncode", "display_name": "CLIP Text Encode (Prompt)", "description": "Encodes a text prompt using a CLIP model into an embedding that can be used to guide the diffusion model towards generating specific images.", "python_module": "nodes", "category": "conditioning", "output_node": false, "output_tooltips": ["A conditioning containing the embedded text used to guide the diffusion model."]}, "CLIPSetLastLayer": {"input": {"required": {"clip": ["CLIP"], "stop_at_clip_layer": ["INT", {"default": -1, "min": -24, "max": -1, "step": 1}]}}, "input_order": {"required": ["clip", "stop_at_clip_layer"]}, "output": ["CLIP"], "output_is_list": [false], "output_name": ["CLIP"], "name": "CLIPSetLastLayer", "display_name": "CLIP Set Last Layer", "description": "", "python_module": "nodes", "category": "conditioning", "output_node": false}, "VAEDecode": {"input": {"required": {"samples": ["LATENT", {"tooltip": "The latent to be decoded."}], "vae": ["VAE", {"tooltip": "The VAE model used for decoding the latent."}]}}, "input_order": {"required": ["samples", "vae"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "VAEDecode", "display_name": "VAE Decode", "description": "Decodes latent images back into pixel space images.", "python_module": "nodes", "category": "latent", "output_node": false, "output_tooltips": ["The decoded image."]}, "VAEEncode": {"input": {"required": {"pixels": ["IMAGE"], "vae": ["VAE"]}}, "input_order": {"required": ["pixels", "vae"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "VAEEncode", "display_name": "VAE Encode", "description": "", "python_module": "nodes", "category": "latent", "output_node": false}, "VAEEncodeForInpaint": {"input": {"required": {"pixels": ["IMAGE"], "vae": ["VAE"], "mask": ["MASK"], "grow_mask_by": ["INT", {"default": 6, "min": 0, "max": 64, "step": 1}]}}, "input_order": {"required": ["pixels", "vae", "mask", "grow_mask_by"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "VAEEncodeForInpaint", "display_name": "VAE Encode (for Inpainting)", "description": "", "python_module": "nodes", "category": "latent/inpaint", "output_node": false}, "VAELoader": {"input": {"required": {"vae_name": [["Flux/ae.safetensors", "SDXL/sdxl_vae.safetensors"]]}}, "input_order": {"required": ["vae_name"]}, "output": ["VAE"], "output_is_list": [false], "output_name": ["VAE"], "name": "VAELoader", "display_name": "Load VAE", "description": "", "python_module": "nodes", "category": "loaders", "output_node": false}, "EmptyLatentImage": {"input": {"required": {"width": ["INT", {"default": 512, "min": 16, "max": 16384, "step": 8, "tooltip": "The width of the latent images in pixels."}], "height": ["INT", {"default": 512, "min": 16, "max": 16384, "step": 8, "tooltip": "The height of the latent images in pixels."}], "batch_size": ["INT", {"default": 1, "min": 1, "max": 4096, "tooltip": "The number of latent images in the batch."}]}}, "input_order": {"required": ["width", "height", "batch_size"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "EmptyLatentImage", "display_name": "Empty Latent Image", "description": "Create a new batch of empty latent images to be denoised via sampling.", "python_module": "nodes", "category": "latent", "output_node": false, "output_tooltips": ["The empty latent image batch."]}, "LatentUpscale": {"input": {"required": {"samples": ["LATENT"], "upscale_method": [["nearest-exact", "bilinear", "area", "bicubic", "bislerp"]], "width": ["INT", {"default": 512, "min": 0, "max": 16384, "step": 8}], "height": ["INT", {"default": 512, "min": 0, "max": 16384, "step": 8}], "crop": [["disabled", "center"]]}}, "input_order": {"required": ["samples", "upscale_method", "width", "height", "crop"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "LatentUpscale", "display_name": "Upscale Latent", "description": "", "python_module": "nodes", "category": "latent", "output_node": false}, "LatentUpscaleBy": {"input": {"required": {"samples": ["LATENT"], "upscale_method": [["nearest-exact", "bilinear", "area", "bicubic", "bislerp"]], "scale_by": ["FLOAT", {"default": 1.5, "min": 0.01, "max": 8.0, "step": 0.01}]}}, "input_order": {"required": ["samples", "upscale_method", "scale_by"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "LatentUpscaleBy", "display_name": "Upscale Latent By", "description": "", "python_module": "nodes", "category": "latent", "output_node": false}, "LatentFromBatch": {"input": {"required": {"samples": ["LATENT"], "batch_index": ["INT", {"default": 0, "min": 0, "max": 63}], "length": ["INT", {"default": 1, "min": 1, "max": 64}]}}, "input_order": {"required": ["samples", "batch_index", "length"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "LatentFromBatch", "display_name": "Latent From Batch", "description": "", "python_module": "nodes", "category": "latent/batch", "output_node": false}, "RepeatLatentBatch": {"input": {"required": {"samples": ["LATENT"], "amount": ["INT", {"default": 1, "min": 1, "max": 64}]}}, "input_order": {"required": ["samples", "amount"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "RepeatLatentBatch", "display_name": "Repeat Latent Batch", "description": "", "python_module": "nodes", "category": "latent/batch", "output_node": false}, "SaveImage": {"input": {"required": {"images": ["IMAGE", {"tooltip": "The images to save."}], "filename_prefix": ["STRING", {"default": "ComfyUI", "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes."}]}, "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}}, "input_order": {"required": ["images", "filename_prefix"], "hidden": ["prompt", "extra_pnginfo"]}, "output": [], "output_is_list": [], "output_name": [], "name": "SaveImage", "display_name": "Save Image", "description": "Saves the input images to your ComfyUI output directory.", "python_module": "nodes", "category": "image", "output_node": true}, "PreviewImage": {"input": {"required": {"images": ["IMAGE"]}, "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}}, "input_order": {"required": ["images"], "hidden": ["prompt", "extra_pnginfo"]}, "output": [], "output_is_list": [], "output_name": [], "name": "PreviewImage", "display_name": "Preview Image", "description": "Saves the input images to your ComfyUI output directory.", "python_module": "nodes", "category": "image", "output_node": true}, "LoadImage": {"input": {"required": {"image": [["example.png"], {"image_upload": true}]}}, "input_order": {"required": ["image"]}, "output": ["IMAGE", "MASK"], "output_is_list": [false, false], "output_name": ["IMAGE", "MASK"], "name": "LoadImage", "display_name": "Load Image", "description": "", "python_module": "nodes", "category": "image", "output_node": false}, "LoadImageMask": {"input": {"required": {"image": [["example.png"], {"image_upload": true}], "channel": [["alpha", "red", "green", "blue"]]}}, "input_order": {"required": ["image", "channel"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["MASK"], "name": "LoadImageMask", "display_name": "Load Image (as Mask)", "description": "", "python_module": "nodes", "category": "mask", "output_node": false}, "ImageScale": {"input": {"required": {"image": ["IMAGE"], "upscale_method": [["nearest-exact", "bilinear", "area", "bicubic", "lanczos"]], "width": ["INT", {"default": 512, "min": 0, "max": 16384, "step": 1}], "height": ["INT", {"default": 512, "min": 0, "max": 16384, "step": 1}], "crop": [["disabled", "center"]]}}, "input_order": {"required": ["image", "upscale_method", "width", "height", "crop"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageScale", "display_name": "Upscale Image", "description": "", "python_module": "nodes", "category": "image/upscaling", "output_node": false}, "ImageScaleBy": {"input": {"required": {"image": ["IMAGE"], "upscale_method": [["nearest-exact", "bilinear", "area", "bicubic", "lanczos"]], "scale_by": ["FLOAT", {"default": 1.0, "min": 0.01, "max": 8.0, "step": 0.01}]}}, "input_order": {"required": ["image", "upscale_method", "scale_by"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageScaleBy", "display_name": "Upscale Image By", "description": "", "python_module": "nodes", "category": "image/upscaling", "output_node": false}, "ImageInvert": {"input": {"required": {"image": ["IMAGE"]}}, "input_order": {"required": ["image"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageInvert", "display_name": "Invert Image", "description": "", "python_module": "nodes", "category": "image", "output_node": false}, "ImageBatch": {"input": {"required": {"image1": ["IMAGE"], "image2": ["IMAGE"]}}, "input_order": {"required": ["image1", "image2"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageBatch", "display_name": "Batch Images", "description": "", "python_module": "nodes", "category": "image", "output_node": false}, "ImagePadForOutpaint": {"input": {"required": {"image": ["IMAGE"], "left": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "top": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "right": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "bottom": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "feathering": ["INT", {"default": 40, "min": 0, "max": 16384, "step": 1}]}}, "input_order": {"required": ["image", "left", "top", "right", "bottom", "feathering"]}, "output": ["IMAGE", "MASK"], "output_is_list": [false, false], "output_name": ["IMAGE", "MASK"], "name": "ImagePadForOutpaint", "display_name": "Pad Image for Outpainting", "description": "", "python_module": "nodes", "category": "image", "output_node": false}, "EmptyImage": {"input": {"required": {"width": ["INT", {"default": 512, "min": 1, "max": 16384, "step": 1}], "height": ["INT", {"default": 512, "min": 1, "max": 16384, "step": 1}], "batch_size": ["INT", {"default": 1, "min": 1, "max": 4096}], "color": ["INT", {"default": 0, "min": 0, "max": 16777215, "step": 1, "display": "color"}]}}, "input_order": {"required": ["width", "height", "batch_size", "color"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "EmptyImage", "display_name": "EmptyImage", "description": "", "python_module": "nodes", "category": "image", "output_node": false}, "ConditioningAverage": {"input": {"required": {"conditioning_to": ["CONDITIONING"], "conditioning_from": ["CONDITIONING"], "conditioning_to_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}]}}, "input_order": {"required": ["conditioning_to", "conditioning_from", "conditioning_to_strength"]}, "output": ["CONDITIONING"], "output_is_list": [false], "output_name": ["CONDITIONING"], "name": "ConditioningAverage", "display_name": "ConditioningAverage", "description": "", "python_module": "nodes", "category": "conditioning", "output_node": false}, "ConditioningCombine": {"input": {"required": {"conditioning_1": ["CONDITIONING"], "conditioning_2": ["CONDITIONING"]}}, "input_order": {"required": ["conditioning_1", "conditioning_2"]}, "output": ["CONDITIONING"], "output_is_list": [false], "output_name": ["CONDITIONING"], "name": "ConditioningCombine", "display_name": "Conditioning (Combine)", "description": "", "python_module": "nodes", "category": "conditioning", "output_node": false}, "ConditioningConcat": {"input": {"required": {"conditioning_to": ["CONDITIONING"], "conditioning_from": ["CONDITIONING"]}}, "input_order": {"required": ["conditioning_to", "conditioning_from"]}, "output": ["CONDITIONING"], "output_is_list": [false], "output_name": ["CONDITIONING"], "name": "ConditioningConcat", "display_name": "Conditioning (Concat)", "description": "", "python_module": "nodes", "category": "conditioning", "output_node": false}, "ConditioningSetArea": {"input": {"required": {"conditioning": ["CONDITIONING"], "width": ["INT", {"default": 64, "min": 64, "max": 16384, "step": 8}], "height": ["INT", {"default": 64, "min": 64, "max": 16384, "step": 8}], "x": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "y": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}]}}, "input_order": {"required": ["conditioning", "width", "height", "x", "y", "strength"]}, "output": ["CONDITIONING"], "output_is_list": [false], "output_name": ["CONDITIONING"], "name": "ConditioningSetArea", "display_name": "Conditioning (Set Area)", "description": "", "python_module": "nodes", "category": "conditioning", "output_node": false}, "ConditioningSetAreaPercentage": {"input": {"required": {"conditioning": ["CONDITIONING"], "width": ["FLOAT", {"default": 1.0, "min": 0, "max": 1.0, "step": 0.01}], "height": ["FLOAT", {"default": 1.0, "min": 0, "max": 1.0, "step": 0.01}], "x": ["FLOAT", {"default": 0, "min": 0, "max": 1.0, "step": 0.01}], "y": ["FLOAT", {"default": 0, "min": 0, "max": 1.0, "step": 0.01}], "strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}]}}, "input_order": {"required": ["conditioning", "width", "height", "x", "y", "strength"]}, "output": ["CONDITIONING"], "output_is_list": [false], "output_name": ["CONDITIONING"], "name": "ConditioningSetAreaPercentage", "display_name": "Conditioning (Set Area with Percentage)", "description": "", "python_module": "nodes", "category": "conditioning", "output_node": false}, "ConditioningSetAreaStrength": {"input": {"required": {"conditioning": ["CONDITIONING"], "strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}]}}, "input_order": {"required": ["conditioning", "strength"]}, "output": ["CONDITIONING"], "output_is_list": [false], "output_name": ["CONDITIONING"], "name": "ConditioningSetAreaStrength", "display_name": "ConditioningSetAreaStrength", "description": "", "python_module": "nodes", "category": "conditioning", "output_node": false}, "ConditioningSetMask": {"input": {"required": {"conditioning": ["CONDITIONING"], "mask": ["MASK"], "strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "set_cond_area": [["default", "mask bounds"]]}}, "input_order": {"required": ["conditioning", "mask", "strength", "set_cond_area"]}, "output": ["CONDITIONING"], "output_is_list": [false], "output_name": ["CONDITIONING"], "name": "ConditioningSetMask", "display_name": "Conditioning (Set Mask)", "description": "", "python_module": "nodes", "category": "conditioning", "output_node": false}, "KSamplerAdvanced": {"input": {"required": {"model": ["MODEL"], "add_noise": [["enable", "disable"]], "noise_seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615}], "steps": ["INT", {"default": 20, "min": 1, "max": 10000}], "cfg": ["FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0, "step": 0.1, "round": 0.01}], "sampler_name": [["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2", "dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_2s_ancestral_cfg_pp", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "ipndm", "ipndm_v", "deis", "ddim", "uni_pc", "uni_pc_bh2"]], "scheduler": [["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta"]], "positive": ["CONDITIONING"], "negative": ["CONDITIONING"], "latent_image": ["LATENT"], "start_at_step": ["INT", {"default": 0, "min": 0, "max": 10000}], "end_at_step": ["INT", {"default": 10000, "min": 0, "max": 10000}], "return_with_leftover_noise": [["disable", "enable"]]}}, "input_order": {"required": ["model", "add_noise", "noise_seed", "steps", "cfg", "sampler_name", "scheduler", "positive", "negative", "latent_image", "start_at_step", "end_at_step", "return_with_leftover_noise"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "KSamplerAdvanced", "display_name": "KSampler (Advanced)", "description": "", "python_module": "nodes", "category": "sampling", "output_node": false}, "SetLatentNoiseMask": {"input": {"required": {"samples": ["LATENT"], "mask": ["MASK"]}}, "input_order": {"required": ["samples", "mask"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "SetLatentNoiseMask", "display_name": "Set Latent Noise Mask", "description": "", "python_module": "nodes", "category": "latent/inpaint", "output_node": false}, "LatentComposite": {"input": {"required": {"samples_to": ["LATENT"], "samples_from": ["LATENT"], "x": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "y": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "feather": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}]}}, "input_order": {"required": ["samples_to", "samples_from", "x", "y", "feather"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "LatentComposite", "display_name": "Latent Composite", "description": "", "python_module": "nodes", "category": "latent", "output_node": false}, "LatentBlend": {"input": {"required": {"samples1": ["LATENT"], "samples2": ["LATENT"], "blend_factor": ["FLOAT", {"default": 0.5, "min": 0, "max": 1, "step": 0.01}]}}, "input_order": {"required": ["samples1", "samples2", "blend_factor"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "LatentBlend", "display_name": "Latent Blend", "description": "", "python_module": "nodes", "category": "_for_testing", "output_node": false}, "LatentRotate": {"input": {"required": {"samples": ["LATENT"], "rotation": [["none", "90 degrees", "180 degrees", "270 degrees"]]}}, "input_order": {"required": ["samples", "rotation"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "LatentRotate", "display_name": "Rotate Latent", "description": "", "python_module": "nodes", "category": "latent/transform", "output_node": false}, "LatentFlip": {"input": {"required": {"samples": ["LATENT"], "flip_method": [["x-axis: vertically", "y-axis: horizontally"]]}}, "input_order": {"required": ["samples", "flip_method"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "LatentFlip", "display_name": "Flip Latent", "description": "", "python_module": "nodes", "category": "latent/transform", "output_node": false}, "LatentCrop": {"input": {"required": {"samples": ["LATENT"], "width": ["INT", {"default": 512, "min": 64, "max": 16384, "step": 8}], "height": ["INT", {"default": 512, "min": 64, "max": 16384, "step": 8}], "x": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "y": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}]}}, "input_order": {"required": ["samples", "width", "height", "x", "y"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "LatentCrop", "display_name": "Crop Latent", "description": "", "python_module": "nodes", "category": "latent/transform", "output_node": false}, "LoraLoader": {"input": {"required": {"model": ["MODEL", {"tooltip": "The diffusion model the LoRA will be applied to."}], "clip": ["CLIP", {"tooltip": "The CLIP model the LoRA will be applied to."}], "lora_name": [[], {"tooltip": 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ESAM can only be used if ComfyUI-YoloWorld-EfficientSAM is installed."}], "device_mode": [["AUTO", "Prefer GPU", "CPU"], {"tooltip": "AUTO: Only applicable when a GPU is available. It temporarily loads the SAM_MODEL into VRAM only when the detection function is used.\nPrefer GPU: Tries to keep the SAM_MODEL on the GPU whenever possible. This can be used when there is sufficient VRAM available.\nCPU: Always loads only on the CPU."}]}}, "input_order": {"required": ["model_name", "device_mode"]}, "output": ["SAM_MODEL"], "output_is_list": [false], "output_name": ["SAM_MODEL"], "name": "SAMLoader", "display_name": "SAMLoader (Impact)", "description": "Load the SAM (Segment Anything) model. This can be used in places that utilize SAM detection functionality, such as SAMDetector or SimpleDetector.\nThe SAM detection functionality in Impact Pack must use the SAM_MODEL loaded through this node.", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack", "output_node": false}, "CLIPSegDetectorProvider": {"input": {"required": {"text": ["STRING", {"multiline": false, "tooltip": "Enter the targets to be detected, separated by commas"}], "blur": ["FLOAT", {"min": 0, "max": 15, "step": 0.1, "default": 7, "tooltip": "Blurs the detected mask"}], "threshold": ["FLOAT", {"min": 0, "max": 1, "step": 0.05, "default": 0.4, "tooltip": "Detects only areas that are certain above the threshold."}], "dilation_factor": ["INT", {"min": 0, "max": 10, "step": 1, "default": 4, "tooltip": "Dilates the detected mask."}]}}, "input_order": {"required": ["text", "blur", "threshold", "dilation_factor"]}, "output": ["BBOX_DETECTOR"], "output_is_list": [false], "output_name": ["BBOX_DETECTOR"], "name": "CLIPSegDetectorProvider", "display_name": "CLIPSegDetectorProvider", "description": "Provides a detection function using CLIPSeg, which generates masks based on text prompts.\nTo use this node, the CLIPSeg custom node must be installed.", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false}, "ONNXDetectorProvider": {"input": {"required": {"model_name": [[]]}}, "input_order": {"required": ["model_name"]}, "output": ["BBOX_DETECTOR"], "output_is_list": [false], "output_name": ["BBOX_DETECTOR"], "name": "ONNXDetectorProvider", "display_name": "ONNXDetectorProvider", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack", "output_node": false}, "BitwiseAndMaskForEach": {"input": {"required": {"base_segs": ["SEGS"], "mask_segs": ["SEGS"]}}, "input_order": {"required": ["base_segs", "mask_segs"]}, "output": ["SEGS"], "output_is_list": [false], "output_name": ["SEGS"], "name": "BitwiseAndMaskForEach", "display_name": "Pixelwise(SEGS & SEGS)", "description": "Retains only the overlapping areas between the masks included in base_segs and the mask regions of mask_segs. SEGS with no overlapping mask areas are filtered out.", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Operation", "output_node": false}, "SubtractMaskForEach": {"input": {"required": {"base_segs": ["SEGS"], "mask_segs": ["SEGS"]}}, "input_order": {"required": ["base_segs", "mask_segs"]}, "output": ["SEGS"], "output_is_list": [false], "output_name": ["SEGS"], "name": "SubtractMaskForEach", "display_name": "Pixelwise(SEGS - SEGS)", "description": "Removes only the overlapping areas between the masks included in base_segs and the mask regions of mask_segs. SEGS with no overlapping mask areas are filtered out.", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Operation", "output_node": false}, "DetailerForEach": {"input": {"required": {"image": ["IMAGE"], "segs": ["SEGS"], "model": ["MODEL"], "clip": ["CLIP"], "vae": ["VAE"], "guide_size": ["FLOAT", {"default": 512, "min": 64, "max": 16384, "step": 8}], "guide_size_for": ["BOOLEAN", {"default": true, "label_on": "bbox", "label_off": "crop_region"}], "max_size": ["FLOAT", {"default": 1024, "min": 64, "max": 16384, "step": 8}], "seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615}], "steps": ["INT", {"default": 20, "min": 1, "max": 10000}], "cfg": ["FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}], "sampler_name": [["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2", "dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_2s_ancestral_cfg_pp", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "ipndm", "ipndm_v", "deis", "ddim", "uni_pc", "uni_pc_bh2"]], "scheduler": [["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta", "AYS SDXL", "AYS SD1", "AYS SVD", "GITS[coeff=1.2]"]], "positive": ["CONDITIONING"], "negative": ["CONDITIONING"], "denoise": ["FLOAT", {"default": 0.5, "min": 0.0001, "max": 1.0, "step": 0.01}], "feather": ["INT", {"default": 5, "min": 0, "max": 100, "step": 1}], "noise_mask": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled"}], "force_inpaint": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled"}], "wildcard": ["STRING", {"multiline": true, "dynamicPrompts": false}], "cycle": ["INT", {"default": 1, "min": 1, "max": 10, "step": 1}]}, "optional": {"detailer_hook": ["DETAILER_HOOK"], "inpaint_model": ["BOOLEAN", {"default": false, "label_on": "enabled", "label_off": "disabled"}], "noise_mask_feather": ["INT", {"default": 20, "min": 0, "max": 100, "step": 1}], "scheduler_func_opt": ["SCHEDULER_FUNC"]}}, "input_order": {"required": ["image", "segs", "model", "clip", "vae", "guide_size", "guide_size_for", "max_size", "seed", "steps", "cfg", "sampler_name", "scheduler", "positive", "negative", "denoise", "feather", "noise_mask", "force_inpaint", "wildcard", "cycle"], "optional": ["detailer_hook", "inpaint_model", "noise_mask_feather", "scheduler_func_opt"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "DetailerForEach", "display_name": "Detailer (SEGS)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Detailer", "output_node": false}, "DetailerForEachDebug": {"input": {"required": {"image": ["IMAGE"], "segs": ["SEGS"], "model": ["MODEL"], "clip": ["CLIP"], "vae": ["VAE"], "guide_size": ["FLOAT", {"default": 512, "min": 64, "max": 16384, "step": 8}], "guide_size_for": ["BOOLEAN", {"default": true, "label_on": "bbox", "label_off": "crop_region"}], "max_size": ["FLOAT", {"default": 1024, "min": 64, "max": 16384, "step": 8}], "seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615}], "steps": ["INT", {"default": 20, "min": 1, "max": 10000}], "cfg": ["FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}], "sampler_name": [["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2", "dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_2s_ancestral_cfg_pp", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "ipndm", "ipndm_v", "deis", "ddim", "uni_pc", "uni_pc_bh2"]], "scheduler": [["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta", "AYS SDXL", "AYS SD1", "AYS SVD", "GITS[coeff=1.2]"]], "positive": ["CONDITIONING"], "negative": ["CONDITIONING"], "denoise": ["FLOAT", {"default": 0.5, "min": 0.0001, "max": 1.0, "step": 0.01}], "feather": ["INT", {"default": 5, "min": 0, "max": 100, "step": 1}], "noise_mask": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled"}], "force_inpaint": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled"}], "wildcard": ["STRING", {"multiline": true, "dynamicPrompts": false}], "cycle": ["INT", {"default": 1, "min": 1, "max": 10, "step": 1}]}, "optional": {"detailer_hook": ["DETAILER_HOOK"], "inpaint_model": ["BOOLEAN", {"default": false, "label_on": "enabled", "label_off": "disabled"}], "noise_mask_feather": ["INT", {"default": 20, "min": 0, "max": 100, "step": 1}], "scheduler_func_opt": ["SCHEDULER_FUNC"]}}, "input_order": {"required": ["image", "segs", "model", "clip", "vae", "guide_size", "guide_size_for", "max_size", "seed", "steps", "cfg", "sampler_name", "scheduler", "positive", "negative", "denoise", "feather", "noise_mask", "force_inpaint", "wildcard", "cycle"], "optional": ["detailer_hook", "inpaint_model", "noise_mask_feather", "scheduler_func_opt"]}, "output": ["IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE"], "output_is_list": [false, true, true, true, true], "output_name": ["image", "cropped", "cropped_refined", "cropped_refined_alpha", "cnet_images"], "name": "DetailerForEachDebug", "display_name": "DetailerDebug (SEGS)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Detailer", "output_node": false}, "DetailerForEachPipe": {"input": {"required": {"image": ["IMAGE"], "segs": ["SEGS"], "guide_size": ["FLOAT", {"default": 512, "min": 64, "max": 16384, "step": 8}], "guide_size_for": ["BOOLEAN", {"default": true, "label_on": "bbox", "label_off": "crop_region"}], "max_size": ["FLOAT", {"default": 1024, "min": 64, "max": 16384, "step": 8}], "seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615}], "steps": ["INT", {"default": 20, "min": 1, "max": 10000}], "cfg": ["FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}], "sampler_name": [["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2", "dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_2s_ancestral_cfg_pp", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "ipndm", "ipndm_v", "deis", "ddim", "uni_pc", "uni_pc_bh2"]], "scheduler": [["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta", "AYS SDXL", "AYS SD1", "AYS SVD", "GITS[coeff=1.2]"]], "denoise": ["FLOAT", {"default": 0.5, "min": 0.0001, "max": 1.0, "step": 0.01}], "feather": ["INT", {"default": 5, "min": 0, "max": 100, "step": 1}], "noise_mask": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled"}], "force_inpaint": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled"}], "basic_pipe": ["BASIC_PIPE"], "wildcard": ["STRING", {"multiline": true, "dynamicPrompts": false}], "refiner_ratio": ["FLOAT", {"default": 0.2, "min": 0.0, "max": 1.0}], "cycle": ["INT", {"default": 1, "min": 1, "max": 10, "step": 1}]}, "optional": {"detailer_hook": ["DETAILER_HOOK"], "refiner_basic_pipe_opt": ["BASIC_PIPE"], "inpaint_model": ["BOOLEAN", {"default": false, "label_on": "enabled", "label_off": "disabled"}], "noise_mask_feather": ["INT", {"default": 20, "min": 0, "max": 100, "step": 1}], "scheduler_func_opt": ["SCHEDULER_FUNC"]}}, "input_order": {"required": ["image", "segs", "guide_size", "guide_size_for", "max_size", "seed", "steps", "cfg", "sampler_name", "scheduler", "denoise", "feather", "noise_mask", "force_inpaint", "basic_pipe", "wildcard", "refiner_ratio", "cycle"], "optional": ["detailer_hook", "refiner_basic_pipe_opt", "inpaint_model", "noise_mask_feather", "scheduler_func_opt"]}, "output": ["IMAGE", "SEGS", "BASIC_PIPE", "IMAGE"], "output_is_list": [false, false, false, true], "output_name": ["image", "segs", "basic_pipe", "cnet_images"], "name": "DetailerForEachPipe", "display_name": "Detailer (SEGS/pipe)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Detailer", "output_node": false}, "DetailerForEachDebugPipe": {"input": {"required": {"image": ["IMAGE"], "segs": ["SEGS"], "guide_size": ["FLOAT", {"default": 512, "min": 64, "max": 16384, "step": 8}], "guide_size_for": ["BOOLEAN", {"default": true, "label_on": "bbox", "label_off": "crop_region"}], "max_size": ["FLOAT", {"default": 1024, "min": 64, "max": 16384, "step": 8}], "seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615}], "steps": ["INT", {"default": 20, "min": 1, "max": 10000}], "cfg": ["FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}], "sampler_name": [["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2", "dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_2s_ancestral_cfg_pp", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "ipndm", "ipndm_v", "deis", "ddim", "uni_pc", "uni_pc_bh2"]], "scheduler": [["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta", "AYS SDXL", "AYS SD1", "AYS SVD", "GITS[coeff=1.2]"]], "denoise": ["FLOAT", {"default": 0.5, "min": 0.0001, "max": 1.0, "step": 0.01}], "feather": ["INT", {"default": 5, "min": 0, "max": 100, "step": 1}], "noise_mask": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled"}], "force_inpaint": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled"}], "basic_pipe": ["BASIC_PIPE"], "wildcard": ["STRING", {"multiline": true, "dynamicPrompts": false}], "refiner_ratio": ["FLOAT", {"default": 0.2, "min": 0.0, "max": 1.0}], "cycle": ["INT", {"default": 1, "min": 1, "max": 10, "step": 1}]}, "optional": {"detailer_hook": ["DETAILER_HOOK"], "refiner_basic_pipe_opt": ["BASIC_PIPE"], "inpaint_model": ["BOOLEAN", {"default": false, "label_on": "enabled", "label_off": "disabled"}], "noise_mask_feather": ["INT", {"default": 20, "min": 0, "max": 100, "step": 1}], "scheduler_func_opt": ["SCHEDULER_FUNC"]}}, "input_order": {"required": ["image", "segs", "guide_size", "guide_size_for", "max_size", "seed", "steps", "cfg", "sampler_name", "scheduler", "denoise", "feather", "noise_mask", "force_inpaint", "basic_pipe", "wildcard", "refiner_ratio", "cycle"], "optional": ["detailer_hook", "refiner_basic_pipe_opt", "inpaint_model", "noise_mask_feather", "scheduler_func_opt"]}, "output": ["IMAGE", "SEGS", "BASIC_PIPE", "IMAGE", "IMAGE", "IMAGE", "IMAGE"], "output_is_list": [false, false, false, true, true, true, true], "output_name": ["image", "segs", "basic_pipe", "cropped", "cropped_refined", "cropped_refined_alpha", "cnet_images"], "name": "DetailerForEachDebugPipe", "display_name": "DetailerDebug (SEGS/pipe)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Detailer", "output_node": false}, "DetailerForEachPipeForAnimateDiff": {"input": {"required": {"image_frames": ["IMAGE"], "segs": ["SEGS"], "guide_size": ["FLOAT", {"default": 512, "min": 64, "max": 16384, "step": 8}], "guide_size_for": ["BOOLEAN", {"default": true, "label_on": "bbox", "label_off": "crop_region"}], "max_size": ["FLOAT", {"default": 1024, "min": 64, "max": 16384, "step": 8}], "seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615}], "steps": ["INT", {"default": 20, "min": 1, "max": 10000}], "cfg": ["FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}], "sampler_name": [["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2", "dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_2s_ancestral_cfg_pp", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "ipndm", "ipndm_v", "deis", "ddim", "uni_pc", "uni_pc_bh2"]], "scheduler": [["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta", "AYS SDXL", "AYS SD1", "AYS SVD", "GITS[coeff=1.2]"]], "denoise": ["FLOAT", {"default": 0.5, "min": 0.0001, "max": 1.0, "step": 0.01}], "feather": ["INT", {"default": 5, "min": 0, "max": 100, "step": 1}], "basic_pipe": ["BASIC_PIPE"], "refiner_ratio": ["FLOAT", {"default": 0.2, "min": 0.0, "max": 1.0}]}, "optional": {"detailer_hook": ["DETAILER_HOOK"], "refiner_basic_pipe_opt": ["BASIC_PIPE"], "noise_mask_feather": ["INT", {"default": 20, "min": 0, "max": 100, "step": 1}], "scheduler_func_opt": ["SCHEDULER_FUNC"]}}, "input_order": {"required": ["image_frames", "segs", "guide_size", "guide_size_for", "max_size", "seed", "steps", "cfg", "sampler_name", "scheduler", "denoise", "feather", "basic_pipe", "refiner_ratio"], "optional": ["detailer_hook", "refiner_basic_pipe_opt", "noise_mask_feather", "scheduler_func_opt"]}, "output": ["IMAGE", "SEGS", "BASIC_PIPE", "IMAGE"], "output_is_list": [false, false, false, true], "output_name": ["image", "segs", "basic_pipe", "cnet_images"], "name": "DetailerForEachPipeForAnimateDiff", "display_name": "Detailer For AnimateDiff (SEGS/pipe)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Detailer", "output_node": false}, "SAMDetectorCombined": {"input": {"required": {"sam_model": ["SAM_MODEL", {"tooltip": "Segment Anything Model for Silhouette Detection.\nBe sure to use the SAM_MODEL loaded through the SAMLoader (Impact) node as input."}], "segs": ["SEGS", {"tooltip": "This is the segment information detected by the detector.\nIt refines the Mask through the SAM (Segment Anything) detector for all areas pointed to by SEGS, and combines all Masks to return as a single Mask."}], "image": ["IMAGE", {"tooltip": "It is assumed that segs contains only the information about the detected areas, and does not include the image. SAM (Segment Anything) operates by referencing this image."}], "detection_hint": [["center-1", "horizontal-2", "vertical-2", "rect-4", "diamond-4", "mask-area", "mask-points", "mask-point-bbox", "none"], {"tooltip": "It is recommended to use only center-1.\nWhen refining the mask of SEGS with the SAM (Segment Anything) model, center-1 uses only the rectangular area of SEGS and a single point at the exact center as hints.\nOther options were added during the experimental stage and do not work well."}], "dilation": ["INT", {"default": 0, "min": -512, "max": 512, "step": 1, "tooltip": "Set the value to dilate the result mask. If the value is negative, it erodes the mask."}], "threshold": ["FLOAT", {"default": 0.93, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "Set the sensitivity threshold for the mask detected by SAM (Segment Anything). A higher value generates a more specific mask with a narrower range. For example, when pointing to a person's area, it might detect clothes, which is a narrower range, instead of the entire person."}], "bbox_expansion": ["INT", {"default": 0, "min": 0, "max": 1000, "step": 1, "tooltip": "When performing SAM (Segment Anything) detection within the SEGS area, the rectangular area of SEGS is expanded and used as a hint."}], "mask_hint_threshold": ["FLOAT", {"default": 0.7, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "When detection_hint is mask-area, the mask of SEGS is used as a point hint for SAM (Segment Anything).\nIn this case, only the areas of the mask with brightness values equal to or greater than mask_hint_threshold are used as hints."}], "mask_hint_use_negative": [["False", "Small", "Outter"], {"tooltip": "When detecting with SAM (Segment Anything), negative hints are applied as follows:\nSmall: When the SEGS is smaller than 10 pixels in size\nOuter: Sampling the image area outside the SEGS region at regular intervals"}]}}, "input_order": {"required": ["sam_model", "segs", "image", "detection_hint", "dilation", "threshold", "bbox_expansion", "mask_hint_threshold", "mask_hint_use_negative"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["MASK"], "name": "SAMDetectorCombined", "display_name": "SAMDetector (combined)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Detector", "output_node": false}, "SAMDetectorSegmented": {"input": {"required": {"sam_model": ["SAM_MODEL", {"tooltip": "Segment Anything Model for Silhouette Detection.\nBe sure to use the SAM_MODEL loaded through the SAMLoader (Impact) node as input."}], "segs": ["SEGS", {"tooltip": "This is the segment information detected by the detector.\nFor the SEGS region, the masks detected by SAM (Segment Anything) are created as a unified mask and a batch of individual masks."}], "image": ["IMAGE", {"tooltip": "It is assumed that segs contains only the information about the detected areas, and does not include the image. SAM (Segment Anything) operates by referencing this image."}], "detection_hint": [["center-1", "horizontal-2", "vertical-2", "rect-4", "diamond-4", "mask-area", "mask-points", "mask-point-bbox", "none"], {"tooltip": "It is recommended to use only center-1.\nWhen refining the mask of SEGS with the SAM (Segment Anything) model, center-1 uses only the rectangular area of SEGS and a single point at the exact center as hints.\nOther options were added during the experimental stage and do not work well."}], "dilation": ["INT", {"default": 0, "min": -512, "max": 512, "step": 1, "tooltip": "Set the value to dilate the result mask. If the value is negative, it erodes the mask."}], "threshold": ["FLOAT", {"default": 0.93, "min": 0.0, "max": 1.0, "step": 0.01}], "bbox_expansion": ["INT", {"default": 0, "min": 0, "max": 1000, "step": 1, "tooltip": "When performing SAM (Segment Anything) detection within the SEGS area, the rectangular area of SEGS is expanded and used as a hint."}], "mask_hint_threshold": ["FLOAT", {"default": 0.7, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "When detection_hint is mask-area, the mask of SEGS is used as a point hint for SAM (Segment Anything).\nIn this case, only the areas of the mask with brightness values equal to or greater than mask_hint_threshold are used as hints."}], "mask_hint_use_negative": [["False", "Small", "Outter"], {"tooltip": "When detecting with SAM (Segment Anything), negative hints are applied as follows:\nSmall: When the SEGS is smaller than 10 pixels in size\nOuter: Sampling the image area outside the SEGS region at regular intervals"}]}}, "input_order": {"required": ["sam_model", "segs", "image", "detection_hint", "dilation", "threshold", "bbox_expansion", "mask_hint_threshold", "mask_hint_use_negative"]}, "output": ["MASK", "MASK"], "output_is_list": [false, false], "output_name": ["combined_mask", "batch_masks"], "name": "SAMDetectorSegmented", "display_name": "SAMDetector (segmented)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Detector", "output_node": false}, "FaceDetailer": {"input": {"required": {"image": ["IMAGE"], "model": ["MODEL"], "clip": ["CLIP"], "vae": ["VAE"], "guide_size": ["FLOAT", {"default": 512, "min": 64, "max": 16384, "step": 8}], "guide_size_for": ["BOOLEAN", {"default": true, "label_on": "bbox", "label_off": "crop_region"}], "max_size": ["FLOAT", {"default": 1024, "min": 64, "max": 16384, "step": 8}], "seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615}], "steps": ["INT", {"default": 20, "min": 1, "max": 10000}], "cfg": ["FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}], "sampler_name": [["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2", "dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_2s_ancestral_cfg_pp", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "ipndm", "ipndm_v", "deis", "ddim", "uni_pc", "uni_pc_bh2"]], "scheduler": [["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta", "AYS SDXL", "AYS SD1", "AYS SVD", "GITS[coeff=1.2]"]], "positive": ["CONDITIONING"], "negative": ["CONDITIONING"], "denoise": ["FLOAT", {"default": 0.5, "min": 0.0001, "max": 1.0, "step": 0.01}], "feather": ["INT", {"default": 5, "min": 0, "max": 100, "step": 1}], "noise_mask": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled"}], "force_inpaint": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled"}], "bbox_threshold": ["FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}], "bbox_dilation": ["INT", {"default": 10, "min": -512, "max": 512, "step": 1}], "bbox_crop_factor": ["FLOAT", {"default": 3.0, "min": 1.0, "max": 10, "step": 0.1}], "sam_detection_hint": [["center-1", "horizontal-2", "vertical-2", "rect-4", "diamond-4", "mask-area", "mask-points", "mask-point-bbox", "none"]], "sam_dilation": ["INT", {"default": 0, "min": -512, "max": 512, "step": 1}], "sam_threshold": ["FLOAT", {"default": 0.93, "min": 0.0, "max": 1.0, "step": 0.01}], "sam_bbox_expansion": ["INT", {"default": 0, "min": 0, "max": 1000, "step": 1}], "sam_mask_hint_threshold": ["FLOAT", {"default": 0.7, "min": 0.0, "max": 1.0, "step": 0.01}], "sam_mask_hint_use_negative": [["False", "Small", "Outter"]], "drop_size": ["INT", {"min": 1, "max": 16384, "step": 1, "default": 10}], "bbox_detector": ["BBOX_DETECTOR"], "wildcard": ["STRING", {"multiline": true, "dynamicPrompts": false}], "cycle": ["INT", {"default": 1, "min": 1, "max": 10, "step": 1}]}, "optional": {"sam_model_opt": ["SAM_MODEL"], "segm_detector_opt": ["SEGM_DETECTOR"], "detailer_hook": ["DETAILER_HOOK"], "inpaint_model": ["BOOLEAN", {"default": false, "label_on": "enabled", "label_off": "disabled"}], "noise_mask_feather": ["INT", {"default": 20, "min": 0, "max": 100, "step": 1}], "scheduler_func_opt": ["SCHEDULER_FUNC"]}}, "input_order": {"required": ["image", "model", "clip", "vae", "guide_size", "guide_size_for", "max_size", "seed", "steps", "cfg", "sampler_name", "scheduler", "positive", "negative", "denoise", "feather", "noise_mask", "force_inpaint", "bbox_threshold", "bbox_dilation", "bbox_crop_factor", "sam_detection_hint", "sam_dilation", "sam_threshold", "sam_bbox_expansion", "sam_mask_hint_threshold", "sam_mask_hint_use_negative", "drop_size", "bbox_detector", "wildcard", "cycle"], "optional": ["sam_model_opt", "segm_detector_opt", "detailer_hook", "inpaint_model", "noise_mask_feather", "scheduler_func_opt"]}, "output": ["IMAGE", "IMAGE", "IMAGE", "MASK", "DETAILER_PIPE", "IMAGE"], "output_is_list": [false, true, true, false, false, true], "output_name": ["image", "cropped_refined", "cropped_enhanced_alpha", "mask", "detailer_pipe", "cnet_images"], "name": "FaceDetailer", "display_name": "FaceDetailer", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Simple", "output_node": false}, "FaceDetailerPipe": {"input": {"required": {"image": ["IMAGE"], "detailer_pipe": ["DETAILER_PIPE"], "guide_size": ["FLOAT", {"default": 512, "min": 64, "max": 16384, "step": 8}], "guide_size_for": ["BOOLEAN", {"default": true, "label_on": "bbox", "label_off": "crop_region"}], "max_size": ["FLOAT", {"default": 1024, "min": 64, "max": 16384, "step": 8}], "seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615}], "steps": ["INT", {"default": 20, "min": 1, "max": 10000}], "cfg": ["FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}], "sampler_name": [["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2", "dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_2s_ancestral_cfg_pp", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "ipndm", "ipndm_v", "deis", "ddim", "uni_pc", "uni_pc_bh2"]], "scheduler": [["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta", "AYS SDXL", "AYS SD1", "AYS SVD", "GITS[coeff=1.2]"]], "denoise": ["FLOAT", {"default": 0.5, "min": 0.0001, "max": 1.0, "step": 0.01}], "feather": ["INT", {"default": 5, "min": 0, "max": 100, "step": 1}], "noise_mask": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled"}], "force_inpaint": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled"}], "bbox_threshold": ["FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}], 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This amount is the noise added at the start, and the higher it is, the more the input latent will be modified before being returned."}], "tile_width": ["INT", {"default": 512, "min": 320, "max": 16384, "step": 64, "tooltip": "Sets the width of the tile to be used in TiledKSampler."}], "tile_height": ["INT", {"default": 512, "min": 320, "max": 16384, "step": 64, "tooltip": "Sets the height of the tile to be used in TiledKSampler."}], "tiling_strategy": [["random", "padded", "simple"], {"tooltip": "Sets the tiling strategy for TiledKSampler."}], "basic_pipe": ["BASIC_PIPE", {"tooltip": "basic_pipe input for sampling"}]}}, "input_order": {"required": ["seed", "steps", "cfg", "sampler_name", "scheduler", "denoise", "tile_width", "tile_height", "tiling_strategy", "basic_pipe"]}, "output": ["KSAMPLER"], "output_is_list": [false], "output_name": ["KSAMPLER"], "name": "TiledKSamplerProvider", "display_name": "TiledKSamplerProvider", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Sampler", "output_node": false, "output_tooltips": ["sampler wrapper. (Can be used when generating a regional_prompt.)"]}, "KSamplerAdvancedProvider": {"input": {"required": {"cfg": ["FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0, "toolip": "classifier free guidance value"}], "sampler_name": [["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2", "dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_2s_ancestral_cfg_pp", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "ipndm", "ipndm_v", "deis", "ddim", "uni_pc", "uni_pc_bh2"], {"toolip": "sampler"}], "scheduler": [["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta", "AYS SDXL", "AYS SD1", "AYS SVD", "GITS[coeff=1.2]"], {"toolip": "noise schedule"}], "sigma_factor": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01, "toolip": "Multiplier of noise schedule"}], "basic_pipe": ["BASIC_PIPE", {"toolip": "basic_pipe input for sampling"}]}, "optional": {"sampler_opt": ["SAMPLER", {"toolip": "[OPTIONAL] Uses the passed sampler instead of internal impact_sampler."}], "scheduler_func_opt": ["SCHEDULER_FUNC", {"toolip": "[OPTIONAL] Noise schedule generation function. If this is set, the scheduler widget will be ignored."}]}}, "input_order": {"required": ["cfg", "sampler_name", "scheduler", "sigma_factor", "basic_pipe"], "optional": ["sampler_opt", "scheduler_func_opt"]}, "output": ["KSAMPLER_ADVANCED"], "output_is_list": [false], "output_name": ["KSAMPLER_ADVANCED"], "name": "KSamplerAdvancedProvider", "display_name": "KSamplerAdvancedProvider", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Sampler", "output_node": false, "output_tooltips": ["sampler wrapper. (Can be used when generating a regional_prompt.)"]}, "TwoAdvancedSamplersForMask": {"input": {"required": {"seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615, "tooltip": "Random seed to use for generating CPU noise for sampling."}], "steps": ["INT", {"default": 20, "min": 1, "max": 10000, "tooltip": "total sampling steps"}], "denoise": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "The amount of noise to remove. This amount is the noise added at the start, and the higher it is, the more the input latent will be modified before being returned."}], "samples": ["LATENT", {"tooltip": "input latent image"}], "base_sampler": ["KSAMPLER_ADVANCED", {"tooltip": "Sampler to apply to the region outside the mask."}], "mask_sampler": ["KSAMPLER_ADVANCED", {"tooltip": "Sampler to apply to the masked region."}], "mask": ["MASK", {"tooltip": "region mask"}], "overlap_factor": ["INT", {"default": 10, "min": 0, "max": 10000, "tooltip": "To smooth the seams of the region boundaries, expand the mask by the overlap_factor amount to overlap with other regions."}]}}, "input_order": {"required": ["seed", "steps", "denoise", "samples", "base_sampler", "mask_sampler", "mask", "overlap_factor"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "TwoAdvancedSamplersForMask", "display_name": "TwoAdvancedSamplersForMask", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Sampler", "output_node": false, "output_tooltips": ["result latent"]}, "ImpactNegativeConditioningPlaceholder": {"input": {"required": {}}, "input_order": {"required": []}, "output": ["CONDITIONING"], "output_is_list": [false], "output_name": ["CONDITIONING"], "name": "ImpactNegativeConditioningPlaceholder", "display_name": "Negative Cond Placeholder", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/sampling", "output_node": false, "output_tooltips": ["This is a Placeholder for the FLUX model that does not use Negative Conditioning."]}, "PreviewBridge": {"input": {"required": {"images": ["IMAGE"], "image": ["STRING", {"default": ""}]}, "optional": {"block": ["BOOLEAN", {"default": false, "label_on": "if_empty_mask", "label_off": "never", "tooltip": "is_empty_mask: If the mask is empty, the execution is stopped.\nnever: The execution is never stopped."}]}, "hidden": {"unique_id": "UNIQUE_ID", "extra_pnginfo": "EXTRA_PNGINFO"}}, "input_order": {"required": ["images", "image"], "optional": ["block"], "hidden": ["unique_id", "extra_pnginfo"]}, "output": ["IMAGE", "MASK"], "output_is_list": [false, false], "output_name": ["IMAGE", "MASK"], "name": "PreviewBridge", "display_name": "Preview Bridge (Image)", "description": "This is a feature that allows you to edit and send a Mask over a image.\nIf the block is set to 'is_empty_mask', the execution is stopped when the mask is empty.", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": true}, "PreviewBridgeLatent": {"input": {"required": {"latent": ["LATENT"], "image": ["STRING", {"default": ""}], "preview_method": [["Latent2RGB-FLUX.1", "Latent2RGB-SDXL", "Latent2RGB-SD15", "Latent2RGB-SD3", "Latent2RGB-SD-X4", "Latent2RGB-Playground-2.5", "Latent2RGB-SC-Prior", "Latent2RGB-SC-B", "TAEF1", "TAESDXL", "TAESD15", "TAESD3"]]}, "optional": {"vae_opt": ["VAE"], "block": ["BOOLEAN", {"default": false, "label_on": "if_empty_mask", "label_off": "never", "tooltip": "is_empty_mask: If the mask is empty, the execution is stopped.\nnever: The execution is never stopped. 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'select_on_prompt' is an option that exists for older versions of ComfyUI, and it makes the decision before the workflow execution."}]}, "optional": {"input1": ["*", {"lazy": true, "tooltip": "Any input. When connected, one more input slot is added."}]}, "hidden": {"unique_id": "UNIQUE_ID", "extra_pnginfo": "EXTRA_PNGINFO"}}, "input_order": {"required": ["select", "sel_mode"], "optional": ["input1"], "hidden": ["unique_id", "extra_pnginfo"]}, "output": ["*", "STRING", "INT"], "output_is_list": [false, false, false], "output_name": ["selected_value", "selected_label", "selected_index"], "name": "LatentSwitch", "display_name": "Switch (latent/legacy)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false, "output_tooltips": ["Output is generated only from the input chosen by the 'select' value.", "Slot label of the selected input slot", "Outputs the select value as is"]}, "SEGSSwitch": {"input": {"required": {"select": ["INT", {"default": 1, "min": 1, "max": 999999, "step": 1, "tooltip": "The input number you want to output among the inputs"}], "sel_mode": ["BOOLEAN", {"default": false, "label_on": "select_on_prompt", "label_off": "select_on_execution", "forceInput": false, "tooltip": "In the case of 'select_on_execution', the selection is dynamically determined at the time of workflow execution. 'select_on_prompt' is an option that exists for older versions of ComfyUI, and it makes the decision before the workflow execution."}]}, "optional": {"input1": ["*", {"lazy": true, "tooltip": "Any input. When connected, one more input slot is added."}]}, "hidden": {"unique_id": "UNIQUE_ID", "extra_pnginfo": "EXTRA_PNGINFO"}}, "input_order": {"required": ["select", "sel_mode"], "optional": ["input1"], "hidden": ["unique_id", "extra_pnginfo"]}, "output": ["*", "STRING", "INT"], "output_is_list": [false, false, false], "output_name": ["selected_value", "selected_label", "selected_index"], "name": "SEGSSwitch", "display_name": "Switch (SEGS/legacy)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false, "output_tooltips": ["Output is generated only from the input chosen by the 'select' value.", "Slot label of the selected input slot", "Outputs the select value as is"]}, "ImpactSwitch": {"input": {"required": {"select": ["INT", {"default": 1, "min": 1, "max": 999999, "step": 1, "tooltip": "The input number you want to output among the inputs"}], "sel_mode": ["BOOLEAN", {"default": false, "label_on": "select_on_prompt", "label_off": "select_on_execution", "forceInput": false, "tooltip": "In the case of 'select_on_execution', the selection is dynamically determined at the time of workflow execution. 'select_on_prompt' is an option that exists for older versions of ComfyUI, and it makes the decision before the workflow execution."}]}, "optional": {"input1": ["*", {"lazy": true, "tooltip": "Any input. When connected, one more input slot is added."}]}, "hidden": {"unique_id": "UNIQUE_ID", "extra_pnginfo": "EXTRA_PNGINFO"}}, "input_order": {"required": ["select", "sel_mode"], "optional": ["input1"], "hidden": ["unique_id", "extra_pnginfo"]}, "output": ["*", "STRING", "INT"], "output_is_list": [false, false, false], "output_name": ["selected_value", "selected_label", "selected_index"], "name": "ImpactSwitch", "display_name": "Switch (Any)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false, "output_tooltips": ["Output is generated only from the input chosen by the 'select' value.", "Slot label of the selected input slot", "Outputs the select value as is"]}, "ImpactInversedSwitch": {"input": {"required": {"select": ["INT", {"default": 1, "min": 1, "max": 999999, "step": 1, "tooltip": "The output number you want to send from the input"}], "input": ["*", {"tooltip": "Any input. When connected, one more input slot is added."}]}, "optional": {"sel_mode": ["BOOLEAN", {"default": false, "label_on": "select_on_prompt", "label_off": "select_on_execution", "forceInput": false, "tooltip": "In the case of 'select_on_execution', the selection is dynamically determined at the time of workflow execution. 'select_on_prompt' is an option that exists for older versions of ComfyUI, and it makes the decision before the workflow execution."}]}, "hidden": {"prompt": "PROMPT", "unique_id": "UNIQUE_ID"}}, "input_order": {"required": ["select", "input"], "optional": ["sel_mode"], "hidden": ["prompt", "unique_id"]}, "output": ["*"], "output_is_list": [false], "output_name": ["*"], "name": "ImpactInversedSwitch", "display_name": "Inversed Switch (Any)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false, "output_tooltips": ["Output occurs only from the output selected by the 'select' value.\nWhen slots are connected, additional slots are created."]}, "ImpactWildcardProcessor": {"input": {"required": {"wildcard_text": ["STRING", {"multiline": true, "dynamicPrompts": false}], "populated_text": ["STRING", {"multiline": true, "dynamicPrompts": false}], "mode": ["BOOLEAN", {"default": true, "label_on": "Populate", "label_off": "Fixed"}], "seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615}], "Select to add Wildcard": [["Select the Wildcard to add to the text"]]}}, "input_order": {"required": ["wildcard_text", "populated_text", "mode", "seed", "Select to add Wildcard"]}, "output": ["STRING"], "output_is_list": [false], "output_name": ["STRING"], "name": "ImpactWildcardProcessor", "display_name": "ImpactWildcardProcessor", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Prompt", "output_node": false}, "ImpactWildcardEncode": {"input": {"required": {"model": ["MODEL"], "clip": ["CLIP"], "wildcard_text": ["STRING", {"multiline": true, "dynamicPrompts": false}], "populated_text": ["STRING", {"multiline": true, "dynamicPrompts": false}], "mode": ["BOOLEAN", {"default": true, "label_on": "Populate", "label_off": "Fixed"}], "Select to add LoRA": [["Select the LoRA to add to the text"]], "Select to add Wildcard": [["Select the Wildcard to add to the text"]], "seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615}]}}, "input_order": {"required": ["model", "clip", "wildcard_text", "populated_text", "mode", "Select to add LoRA", "Select to add Wildcard", "seed"]}, "output": ["MODEL", "CLIP", "CONDITIONING", "STRING"], "output_is_list": [false, false, false, false], "output_name": ["model", "clip", "conditioning", "populated_text"], "name": "ImpactWildcardEncode", "display_name": "ImpactWildcardEncode", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Prompt", "output_node": false}, "SEGSUpscaler": {"input": {"required": {"image": ["IMAGE"], "segs": ["SEGS"], "model": ["MODEL"], "clip": ["CLIP"], "vae": ["VAE"], "rescale_factor": ["FLOAT", {"default": 2, "min": 0.01, "max": 100.0, "step": 0.01}], "resampling_method": [["lanczos", "nearest", "bilinear", "bicubic"]], "supersample": [["true", "false"]], "rounding_modulus": ["INT", {"default": 8, "min": 8, "max": 1024, "step": 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If this is set, the scheduler widget will be ignored."}]}}, "input_order": {"required": ["basic_pipe", "add_noise", "noise_seed", "steps", "cfg", "sampler_name", "scheduler", "latent_image", "start_at_step", "end_at_step", "return_with_leftover_noise"], "optional": ["scheduler_func_opt"]}, "output": ["BASIC_PIPE", "LATENT", "VAE"], "output_is_list": [false, false, false], "output_name": ["BASIC_PIPE", "LATENT", "VAE"], "name": "ImpactKSamplerAdvancedBasicPipe", "display_name": "KSampler (Advanced/pipe)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/sampling", "output_node": false, "output_tooltips": ["passthrough input basic_pipe", "result latent", "VAE in basic_pipe"]}, "ReencodeLatent": {"input": {"required": {"samples": ["LATENT"], "tile_mode": [["None", "Both", "Decode(input) only", "Encode(output) only"]], "input_vae": ["VAE"], "output_vae": ["VAE"], "tile_size": ["INT", {"default": 512, "min": 320, "max": 4096, "step": 64}]}}, "input_order": {"required": ["samples", "tile_mode", "input_vae", "output_vae", "tile_size"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "ReencodeLatent", "display_name": "Reencode Latent", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false}, "ReencodeLatentPipe": {"input": {"required": {"samples": ["LATENT"], "tile_mode": [["None", "Both", "Decode(input) only", "Encode(output) only"]], "input_basic_pipe": ["BASIC_PIPE"], "output_basic_pipe": ["BASIC_PIPE"]}}, "input_order": {"required": ["samples", "tile_mode", "input_basic_pipe", "output_basic_pipe"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "ReencodeLatentPipe", "display_name": "Reencode Latent (pipe)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false}, "ImpactImageBatchToImageList": {"input": {"required": {"image": ["IMAGE"]}}, "input_order": {"required": ["image"]}, "output": ["IMAGE"], "output_is_list": [true], "output_name": ["IMAGE"], "name": "ImpactImageBatchToImageList", "display_name": "Image Batch to Image List", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false}, "ImpactMakeImageList": {"input": {"required": {"image1": ["IMAGE"]}}, "input_order": {"required": ["image1"]}, "output": ["IMAGE"], "output_is_list": [true], "output_name": ["IMAGE"], "name": "ImpactMakeImageList", "display_name": "Make Image List", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false}, "ImpactMakeImageBatch": {"input": {"required": {"image1": ["IMAGE"]}}, "input_order": {"required": ["image1"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImpactMakeImageBatch", "display_name": "Make Image Batch", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false}, "ImpactMakeAnyList": {"input": {"required": {}, "optional": {"value1": ["*"]}}, "input_order": {"required": [], "optional": ["value1"]}, "output": ["*"], "output_is_list": [true], "output_name": ["*"], "name": "ImpactMakeAnyList", "display_name": "Make List (Any)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false}, "ImpactMakeMaskList": {"input": {"required": {"mask1": ["MASK"]}}, "input_order": {"required": ["mask1"]}, "output": ["MASK"], "output_is_list": [true], "output_name": ["MASK"], "name": "ImpactMakeMaskList", "display_name": "Make Mask List", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false}, "ImpactMakeMaskBatch": {"input": {"required": {"mask1": ["MASK"]}}, "input_order": {"required": ["mask1"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["MASK"], "name": "ImpactMakeMaskBatch", "display_name": "Make Mask Batch", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false}, "RegionalSampler": {"input": {"required": {"seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615, "tooltip": "Random seed to use for generating CPU noise for sampling."}], "seed_2nd": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615, "tooltip": "Additional noise seed. The behavior is determined by seed_2nd_mode."}], "seed_2nd_mode": [["ignore", "fixed", "seed+seed_2nd", "seed-seed_2nd", "increment", "decrement", "randomize"], {"tooltip": "application method of seed_2nd. 1) ignore: Do not use seed_2nd. In the base only sampling stage, the seed is applied as a noise seed, and in the regional sampling stage, denoising is performed as it is without additional noise. 2) Others: In the base only sampling stage, the seed is applied as a noise seed, and once it is closed so that there is no leftover noise, new noise is added with seed_2nd and the regional samping stage is performed. a) fixed: Use seed_2nd as it is as an additional noise seed. b) seed+seed_2nd: Apply the value of seed+seed_2nd as an additional noise seed. c) seed-seed_2nd: Apply the value of seed-seed_2nd as an additional noise seed. d) increment: Not implemented yet. Same with fixed. e) decrement: Not implemented yet. Same with fixed. f) randomize: Not implemented yet. Same with fixed."}], "steps": ["INT", {"default": 20, "min": 1, "max": 10000, "tooltip": "total sampling steps"}], "base_only_steps": ["INT", {"default": 2, "min": 0, "max": 10000, "tooltip": "total sampling steps"}], "denoise": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "The amount of noise to remove. This amount is the noise added at the start, and the higher it is, the more the input latent will be modified before being returned."}], "samples": ["LATENT", {"tooltip": "input latent image"}], "base_sampler": ["KSAMPLER_ADVANCED", {"tooltip": "The sampler applied outside the area set by the regional_prompt."}], "regional_prompts": ["REGIONAL_PROMPTS", {"tooltip": "The prompt applied to each region"}], "overlap_factor": ["INT", {"default": 10, "min": 0, "max": 10000, "tooltip": "To smooth the seams of the region boundaries, expand the mask set in regional_prompts by the overlap_factor amount to overlap with other regions."}], "restore_latent": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled", "tooltip": "At each step, restore the noise outside the mask area to its original state, as per the principle of inpainting. This option is provided for backward compatibility, and it is recommended to always set it to true."}], "additional_mode": [["DISABLE", "ratio additional", "ratio between"], {"default": "ratio between", "tooltip": "..._sde or uni_pc and other special samplers are used, the region is not properly denoised, and it causes a phenomenon that destroys the overall harmony. To compensate for this, a recovery operation is performed using another sampler. This requires a longer time for sampling because a second sampling is performed at each step in each region using a special sampler. 1) DISABLE: Disable this feature. 2) ratio additional: After performing the denoise amount to be performed in the step with the sampler set in the region, the recovery sampler is additionally applied by the additional_sigma_ratio. If you use this option, the total denoise amount increases by additional_sigma_ratio. 3) ratio between: The denoise amount to be performed in the step with the sampler set in the region and the denoise amount to be applied to the recovery sampler are divided by additional_sigma_ratio, and denoise is performed for each denoise amount. If you use this option, the total denoise amount does not change."}], "additional_sampler": [["AUTO", "euler", "heun", "heunpp2", "dpm_2", "dpm_fast", "dpmpp_2m", "ddpm"], {"tooltip": "1) AUTO: Automatically set the recovery sampler. If the sampler is uni_pc, uni_pc_bh2, dpmpp_sde, dpmpp_sde_gpu, the dpm_fast sampler is selected If the sampler is dpmpp_2m_sde, dpmpp_2m_sde_gpu, dpmpp_3m_sde, dpmpp_3m_sde_gpu, the dpmpp_2m sampler is selected. 2) Others: Manually set the recovery sampler."}], "additional_sigma_ratio": ["FLOAT", {"default": 0.3, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "Multiplier of noise schedule to be applied according to additional_mode."}]}, "hidden": {"unique_id": "UNIQUE_ID"}}, "input_order": {"required": ["seed", "seed_2nd", "seed_2nd_mode", "steps", "base_only_steps", "denoise", "samples", "base_sampler", "regional_prompts", "overlap_factor", "restore_latent", "additional_mode", "additional_sampler", "additional_sigma_ratio"], "hidden": ["unique_id"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "RegionalSampler", "display_name": "RegionalSampler", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Regional", "output_node": false, "output_tooltips": ["result latent"]}, "RegionalSamplerAdvanced": {"input": {"required": {"add_noise": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled", "tooltip": "Whether to add noise"}], "noise_seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615, "tooltip": "Random seed to use for generating CPU noise for sampling."}], "steps": ["INT", {"default": 20, "min": 1, "max": 10000, "tooltip": "total sampling steps"}], "start_at_step": ["INT", {"default": 0, "min": 0, "max": 10000, "tooltip": "The starting step of the sampling to be applied at this node within the range of 'steps'."}], "end_at_step": ["INT", {"default": 10000, "min": 0, "max": 10000, "tooltip": "The step at which sampling applied at this node will stop within the range of steps (if greater than steps, sampling will continue only up to steps)."}], "overlap_factor": ["INT", {"default": 10, "min": 0, "max": 10000, "tooltip": "To smooth the seams of the region boundaries, expand the mask set in regional_prompts by the overlap_factor amount to overlap with other regions."}], "restore_latent": ["BOOLEAN", {"default": true, "label_on": "enabled", "label_off": "disabled", "tooltip": "At each step, restore the noise outside the mask area to its original state, as per the principle of inpainting. This option is provided for backward compatibility, and it is recommended to always set it to true."}], "return_with_leftover_noise": ["BOOLEAN", {"default": false, "label_on": "enabled", "label_off": "disabled", "tooltip": "Whether to return the latent with noise remaining if the noise has not been completely removed according to the noise schedule, or to completely remove the noise before returning it."}], "latent_image": ["LATENT", {"tooltip": "input latent image"}], "base_sampler": ["KSAMPLER_ADVANCED", {"tooltip": "The sampler applied outside the area set by the regional_prompt."}], "regional_prompts": ["REGIONAL_PROMPTS", {"tooltip": "The prompt applied to each region"}], "additional_mode": [["DISABLE", "ratio additional", "ratio between"], {"default": "ratio between", "tooltip": "..._sde or uni_pc and other special samplers are used, the region is not properly denoised, and it causes a phenomenon that destroys the overall harmony. To compensate for this, a recovery operation is performed using another sampler. This requires a longer time for sampling because a second sampling is performed at each step in each region using a special sampler. 1) DISABLE: Disable this feature. 2) ratio additional: After performing the denoise amount to be performed in the step with the sampler set in the region, the recovery sampler is additionally applied by the additional_sigma_ratio. If you use this option, the total denoise amount increases by additional_sigma_ratio. 3) ratio between: The denoise amount to be performed in the step with the sampler set in the region and the denoise amount to be applied to the recovery sampler are divided by additional_sigma_ratio, and denoise is performed for each denoise amount. If you use this option, the total denoise amount does not change."}], "additional_sampler": [["AUTO", "euler", "heun", "heunpp2", "dpm_2", "dpm_fast", "dpmpp_2m", "ddpm"], {"tooltip": "1) AUTO: Automatically set the recovery sampler. If the sampler is uni_pc, uni_pc_bh2, dpmpp_sde, dpmpp_sde_gpu, the dpm_fast sampler is selected If the sampler is dpmpp_2m_sde, dpmpp_2m_sde_gpu, dpmpp_3m_sde, dpmpp_3m_sde_gpu, the dpmpp_2m sampler is selected. 2) Others: Manually set the recovery sampler."}], "additional_sigma_ratio": ["FLOAT", {"default": 0.3, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "Multiplier of noise schedule to be applied according to additional_mode."}]}, "hidden": {"unique_id": "UNIQUE_ID"}}, "input_order": {"required": ["add_noise", "noise_seed", "steps", "start_at_step", "end_at_step", "overlap_factor", "restore_latent", "return_with_leftover_noise", "latent_image", "base_sampler", "regional_prompts", "additional_mode", "additional_sampler", "additional_sigma_ratio"], "hidden": ["unique_id"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "RegionalSamplerAdvanced", "display_name": "RegionalSamplerAdvanced", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Regional", "output_node": false, "output_tooltips": ["result latent"]}, "CombineRegionalPrompts": {"input": {"required": {"regional_prompts1": ["REGIONAL_PROMPTS", {"tooltip": "input regional_prompts. (Connecting to the input slot increases the number of additional slots.)"}]}}, "input_order": {"required": ["regional_prompts1"]}, "output": ["REGIONAL_PROMPTS"], "output_is_list": [false], "output_name": ["REGIONAL_PROMPTS"], "name": "CombineRegionalPrompts", "display_name": "CombineRegionalPrompts", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Regional", "output_node": false, "output_tooltips": ["Combined REGIONAL_PROMPTS"]}, "RegionalPrompt": {"input": {"required": {"mask": ["MASK", {"tooltip": "region mask"}], "advanced_sampler": ["KSAMPLER_ADVANCED", {"tooltip": "sampler for specified region"}]}, "optional": {"variation_seed": ["INT", {"default": 0, "min": 0, "max": 18446744073709551615, "tooltip": "Sets the extra seed to be used for noise variation."}], "variation_strength": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "Sets the strength of the noise variation."}], "variation_method": [["linear", "slerp"], {"tooltip": "Sets how the original noise and extra noise are blended together."}]}}, "input_order": {"required": ["mask", "advanced_sampler"], "optional": ["variation_seed", "variation_strength", "variation_method"]}, "output": ["REGIONAL_PROMPTS"], "output_is_list": [false], "output_name": ["REGIONAL_PROMPTS"], "name": "RegionalPrompt", "display_name": "RegionalPrompt", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Regional", "output_node": false, "output_tooltips": ["regional prompts. 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"ImpactSEGSLabelFilter": {"input": {"required": {"segs": ["SEGS"], "preset": [["all", "hand", "face", "mouth", "eyes", "eyebrows", "pupils", "left_eyebrow", "left_eye", "left_pupil", "right_eyebrow", "right_eye", "right_pupil", "short_sleeved_shirt", "long_sleeved_shirt", "short_sleeved_outwear", "long_sleeved_outwear", "vest", "sling", "shorts", "trousers", "skirt", "short_sleeved_dress", "long_sleeved_dress", "vest_dress", "sling_dress", "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella", "handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat", "baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut", "cake", "chair", "couch", "potted plant", "bed", "dining table", "toilet", "tv", "laptop", "mouse", "remote", "keyboard", "cell phone", "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors", "teddy bear", "hair drier", "toothbrush"]], "labels": ["STRING", {"multiline": true, "placeholder": "List the types of segments to be allowed, separated by commas"}]}}, "input_order": {"required": ["segs", "preset", "labels"]}, "output": ["SEGS", "SEGS"], "output_is_list": [false, false], "output_name": ["filtered_SEGS", "remained_SEGS"], "name": "ImpactSEGSLabelFilter", "display_name": "SEGS Filter (label)", "description": "", "python_module": "custom_nodes.ComfyUI-Impact-Pack", "category": "ImpactPack/Util", "output_node": false}, "ImpactSEGSRangeFilter": {"input": {"required": {"segs": ["SEGS"], "target": [["area(=w*h)", "width", "height", "x1", "y1", "x2", "y2", "length_percent", "confidence(0-100)"]], "mode": 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"negative_2", "mask_1", "mask_2", "mask_1_strength", "mask_2_strength", "set_cond_area"]}, "output": ["CONDITIONING", "CONDITIONING"], "output_is_list": [false, false], "output_name": ["combined_positive", "combined_negative"], "name": "ConditioningSetMaskAndCombine", "display_name": "ConditioningSetMaskAndCombine", "description": "\nBundles multiple conditioning mask and combine nodes into one,functionality is identical to ComfyUI native nodes\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/conditioning", "output_node": false}, "ConditioningSetMaskAndCombine3": {"input": {"required": {"positive_1": ["CONDITIONING"], "negative_1": ["CONDITIONING"], "positive_2": ["CONDITIONING"], "negative_2": ["CONDITIONING"], "positive_3": ["CONDITIONING"], "negative_3": ["CONDITIONING"], "mask_1": ["MASK"], "mask_2": ["MASK"], "mask_3": ["MASK"], "mask_1_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "mask_2_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "mask_3_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "set_cond_area": [["default", "mask bounds"]]}}, "input_order": {"required": ["positive_1", "negative_1", "positive_2", "negative_2", "positive_3", "negative_3", "mask_1", "mask_2", "mask_3", "mask_1_strength", "mask_2_strength", "mask_3_strength", "set_cond_area"]}, "output": ["CONDITIONING", "CONDITIONING"], "output_is_list": [false, false], "output_name": ["combined_positive", "combined_negative"], "name": "ConditioningSetMaskAndCombine3", "display_name": "ConditioningSetMaskAndCombine3", "description": "\nBundles multiple conditioning mask and combine nodes into one,functionality is identical to ComfyUI native nodes\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/conditioning", "output_node": false}, "ConditioningSetMaskAndCombine4": {"input": {"required": {"positive_1": ["CONDITIONING"], "negative_1": ["CONDITIONING"], "positive_2": ["CONDITIONING"], "negative_2": ["CONDITIONING"], "positive_3": ["CONDITIONING"], "negative_3": ["CONDITIONING"], "positive_4": ["CONDITIONING"], "negative_4": ["CONDITIONING"], "mask_1": ["MASK"], "mask_2": ["MASK"], "mask_3": ["MASK"], "mask_4": ["MASK"], "mask_1_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "mask_2_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "mask_3_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "mask_4_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "set_cond_area": [["default", "mask bounds"]]}}, "input_order": {"required": ["positive_1", "negative_1", "positive_2", "negative_2", "positive_3", "negative_3", "positive_4", "negative_4", "mask_1", "mask_2", "mask_3", "mask_4", "mask_1_strength", "mask_2_strength", "mask_3_strength", "mask_4_strength", "set_cond_area"]}, "output": ["CONDITIONING", "CONDITIONING"], "output_is_list": [false, false], "output_name": ["combined_positive", "combined_negative"], "name": "ConditioningSetMaskAndCombine4", "display_name": "ConditioningSetMaskAndCombine4", "description": "\nBundles multiple conditioning mask and combine nodes into one,functionality is identical to ComfyUI native nodes\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/conditioning", "output_node": false}, "ConditioningSetMaskAndCombine5": {"input": {"required": {"positive_1": ["CONDITIONING"], "negative_1": ["CONDITIONING"], "positive_2": ["CONDITIONING"], "negative_2": ["CONDITIONING"], "positive_3": ["CONDITIONING"], "negative_3": ["CONDITIONING"], "positive_4": ["CONDITIONING"], "negative_4": ["CONDITIONING"], "positive_5": ["CONDITIONING"], "negative_5": ["CONDITIONING"], "mask_1": ["MASK"], "mask_2": ["MASK"], "mask_3": ["MASK"], "mask_4": ["MASK"], "mask_5": ["MASK"], "mask_1_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "mask_2_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "mask_3_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "mask_4_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "mask_5_strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "set_cond_area": [["default", "mask bounds"]]}}, "input_order": {"required": ["positive_1", "negative_1", "positive_2", "negative_2", "positive_3", "negative_3", "positive_4", "negative_4", "positive_5", "negative_5", "mask_1", "mask_2", "mask_3", "mask_4", "mask_5", "mask_1_strength", "mask_2_strength", "mask_3_strength", "mask_4_strength", "mask_5_strength", "set_cond_area"]}, "output": ["CONDITIONING", "CONDITIONING"], "output_is_list": [false, false], "output_name": ["combined_positive", "combined_negative"], "name": "ConditioningSetMaskAndCombine5", "display_name": "ConditioningSetMaskAndCombine5", "description": "\nBundles multiple conditioning mask and combine nodes into one,functionality is identical to ComfyUI native nodes\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/conditioning", "output_node": false}, "CondPassThrough": {"input": {"required": {}, "optional": {"positive": ["CONDITIONING"], "negative": ["CONDITIONING"]}}, "input_order": {"required": [], "optional": ["positive", "negative"]}, "output": ["CONDITIONING", "CONDITIONING"], "output_is_list": [false, false], "output_name": ["positive", "negative"], "name": "CondPassThrough", "display_name": "CondPassThrough", "description": "\n Simply passes through the positive and negative conditioning,\n workaround for Set node not allowing bypassed inputs.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/misc", "output_node": false}, "DownloadAndLoadCLIPSeg": {"input": {"required": {"model": [["Kijai/clipseg-rd64-refined-fp16", "CIDAS/clipseg-rd64-refined"]]}}, "input_order": {"required": ["model"]}, "output": ["CLIPSEGMODEL"], "output_is_list": [false], "output_name": ["clipseg_model"], "name": "DownloadAndLoadCLIPSeg", "display_name": "(Down)load CLIPSeg", "description": "\nDownloads and loads CLIPSeg model with huggingface_hub, \nto ComfyUI/models/clip_seg\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "BatchCLIPSeg": {"input": {"required": {"images": ["IMAGE"], "text": ["STRING", {"multiline": false}], "threshold": ["FLOAT", {"default": 0.5, "min": 0.0, "max": 10.0, "step": 0.001}], "binary_mask": ["BOOLEAN", {"default": true}], "combine_mask": ["BOOLEAN", {"default": false}], "use_cuda": ["BOOLEAN", {"default": true}]}, "optional": {"blur_sigma": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 100.0, "step": 0.1}], "opt_model": ["CLIPSEGMODEL"], "prev_mask": ["MASK", {"default": null}], "image_bg_level": ["FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}], "invert": ["BOOLEAN", {"default": false}]}}, "input_order": {"required": ["images", "text", "threshold", "binary_mask", "combine_mask", "use_cuda"], "optional": ["blur_sigma", "opt_model", "prev_mask", "image_bg_level", "invert"]}, "output": ["MASK", "IMAGE"], "output_is_list": [false, false], "output_name": ["Mask", "Image"], "name": "BatchCLIPSeg", "display_name": "Batch CLIPSeg", "description": "\nSegments an image or batch of images using CLIPSeg.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "ColorToMask": {"input": {"required": {"images": ["IMAGE"], "invert": ["BOOLEAN", {"default": false}], "red": ["INT", {"default": 0, "min": 0, "max": 255, "step": 1}], "green": ["INT", {"default": 0, "min": 0, "max": 255, "step": 1}], "blue": ["INT", {"default": 0, "min": 0, "max": 255, "step": 1}], "threshold": ["INT", {"default": 10, "min": 0, "max": 255, "step": 1}], "per_batch": ["INT", {"default": 16, "min": 1, "max": 4096, "step": 1}]}}, "input_order": {"required": ["images", "invert", "red", "green", "blue", "threshold", "per_batch"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["MASK"], "name": "ColorToMask", "display_name": "Color To Mask", "description": "\nConverts chosen RGB value to a mask. \nWith batch inputs, the **per_batch** \ncontrols the number of images processed at once.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "CreateGradientMask": {"input": {"required": {"invert": ["BOOLEAN", {"default": false}], "frames": ["INT", {"default": 0, "min": 0, "max": 255, "step": 1}], "width": ["INT", {"default": 256, "min": 16, "max": 4096, "step": 1}], "height": ["INT", {"default": 256, "min": 16, "max": 4096, "step": 1}]}}, "input_order": {"required": ["invert", "frames", "width", "height"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["MASK"], "name": "CreateGradientMask", "display_name": "Create Gradient Mask", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/generate", "output_node": false}, "CreateTextMask": {"input": {"required": {"invert": ["BOOLEAN", {"default": false}], "frames": ["INT", {"default": 1, "min": 1, "max": 4096, "step": 1}], "text_x": ["INT", {"default": 0, "min": 0, "max": 4096, "step": 1}], "text_y": ["INT", {"default": 0, "min": 0, "max": 4096, "step": 1}], "font_size": ["INT", {"default": 32, "min": 8, "max": 4096, "step": 1}], "font_color": ["STRING", {"default": "white"}], "text": ["STRING", {"default": "HELLO!", "multiline": true}], "font": [["FreeMono.ttf", "FreeMonoBoldOblique.otf", "TTNorms-Black.otf"]], "width": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "height": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "start_rotation": ["INT", {"default": 0, "min": 0, "max": 359, "step": 1}], "end_rotation": ["INT", {"default": 0, "min": -359, "max": 359, "step": 1}]}}, "input_order": {"required": ["invert", "frames", "text_x", "text_y", "font_size", "font_color", "text", "font", "width", "height", "start_rotation", "end_rotation"]}, "output": ["IMAGE", "MASK"], "output_is_list": [false, false], "output_name": ["IMAGE", "MASK"], "name": "CreateTextMask", "display_name": "Create Text Mask", "description": "\nCreates a text image and mask. \nLooks for fonts from this folder: \nComfyUI/custom_nodes/ComfyUI-KJNodes/fonts\n \nIf start_rotation and/or end_rotation are different values, \ncreates animation between them.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/text", "output_node": false}, "CreateAudioMask": {"input": {"required": {"invert": ["BOOLEAN", {"default": false}], "frames": ["INT", {"default": 16, "min": 1, "max": 255, "step": 1}], "scale": ["FLOAT", {"default": 0.5, "min": 0.0, "max": 2.0, "step": 0.01}], "audio_path": ["STRING", {"default": "audio.wav"}], "width": ["INT", {"default": 256, "min": 16, "max": 4096, "step": 1}], "height": ["INT", {"default": 256, "min": 16, "max": 4096, "step": 1}]}}, "input_order": {"required": ["invert", "frames", "scale", "audio_path", "width", "height"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "CreateAudioMask", "display_name": "Create Audio Mask", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/deprecated", "output_node": false}, "CreateFadeMask": {"input": {"required": {"invert": ["BOOLEAN", {"default": false}], "frames": ["INT", {"default": 2, "min": 2, "max": 255, "step": 1}], "width": ["INT", {"default": 256, "min": 16, "max": 4096, "step": 1}], "height": ["INT", {"default": 256, "min": 16, "max": 4096, "step": 1}], "interpolation": [["linear", "ease_in", "ease_out", "ease_in_out"]], "start_level": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}], "midpoint_level": ["FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}], "end_level": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01}], "midpoint_frame": ["INT", {"default": 0, "min": 0, "max": 4096, "step": 1}]}}, "input_order": {"required": ["invert", "frames", "width", "height", "interpolation", "start_level", "midpoint_level", "end_level", "midpoint_frame"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["MASK"], "name": "CreateFadeMask", "display_name": "Create Fade Mask", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/deprecated", "output_node": false}, "CreateFadeMaskAdvanced": {"input": {"required": {"points_string": ["STRING", {"default": "0:(0.0),\n7:(1.0),\n15:(0.0)\n", "multiline": true}], "invert": ["BOOLEAN", {"default": false}], "frames": ["INT", {"default": 16, "min": 2, "max": 255, "step": 1}], "width": ["INT", {"default": 512, "min": 1, "max": 4096, "step": 1}], "height": ["INT", {"default": 512, "min": 1, "max": 4096, "step": 1}], "interpolation": [["linear", "ease_in", "ease_out", "ease_in_out"]]}}, "input_order": {"required": ["points_string", "invert", "frames", "width", "height", "interpolation"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["MASK"], "name": "CreateFadeMaskAdvanced", "display_name": "Create Fade Mask Advanced", "description": "\nCreate a batch of masks interpolated between given frames and values. \nUses same syntax as Fizz' BatchValueSchedule.\nFirst value is the frame index (not that this starts from 0, not 1) \nand the second value inside the brackets is the float value of the mask in range 0.0 - 1.0 \n\nFor example the default values: \n0:(0.0) \n7:(1.0) \n15:(0.0) \n \nWould create a mask batch fo 16 frames, starting from black, \ninterpolating with the chosen curve to fully white at the 8th frame, \nand interpolating from that to fully black at the 16th frame.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/generate", "output_node": false}, "CreateFluidMask": {"input": {"required": {"invert": ["BOOLEAN", {"default": false}], "frames": ["INT", {"default": 1, "min": 1, "max": 4096, "step": 1}], "width": ["INT", {"default": 256, "min": 16, "max": 4096, "step": 1}], "height": ["INT", {"default": 256, "min": 16, "max": 4096, "step": 1}], "inflow_count": ["INT", {"default": 3, "min": 0, "max": 255, "step": 1}], "inflow_velocity": ["INT", {"default": 1, "min": 0, "max": 255, "step": 1}], "inflow_radius": ["INT", {"default": 8, "min": 0, "max": 255, "step": 1}], "inflow_padding": ["INT", {"default": 50, "min": 0, "max": 255, "step": 1}], "inflow_duration": ["INT", {"default": 60, "min": 0, "max": 255, "step": 1}]}}, "input_order": {"required": ["invert", "frames", "width", "height", "inflow_count", "inflow_velocity", "inflow_radius", "inflow_padding", "inflow_duration"]}, "output": ["IMAGE", "MASK"], "output_is_list": [false, false], "output_name": ["IMAGE", "MASK"], "name": "CreateFluidMask", "display_name": "Create Fluid Mask", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/generate", "output_node": false}, "CreateShapeMask": {"input": {"required": {"shape": [["circle", "square", "triangle"], {"default": "circle"}], "frames": ["INT", {"default": 1, "min": 1, "max": 4096, "step": 1}], "location_x": ["INT", {"default": 256, "min": 0, "max": 4096, "step": 1}], "location_y": ["INT", {"default": 256, "min": 0, "max": 4096, "step": 1}], "grow": ["INT", {"default": 0, "min": -512, "max": 512, "step": 1}], "frame_width": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "frame_height": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "shape_width": ["INT", {"default": 128, "min": 8, "max": 4096, "step": 1}], "shape_height": ["INT", {"default": 128, "min": 8, "max": 4096, "step": 1}]}}, "input_order": {"required": ["shape", "frames", "location_x", "location_y", "grow", "frame_width", "frame_height", "shape_width", "shape_height"]}, "output": ["MASK", "MASK"], "output_is_list": [false, false], "output_name": ["mask", "mask_inverted"], "name": "CreateShapeMask", "display_name": "Create Shape Mask", "description": "\nCreates a mask or batch of masks with the specified shape. \nLocations are center locations. \nGrow value is the amount to grow the shape on each frame, creating animated masks.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/generate", "output_node": false}, "CreateVoronoiMask": {"input": {"required": {"frames": ["INT", {"default": 16, "min": 2, "max": 4096, "step": 1}], "num_points": ["INT", {"default": 15, "min": 1, "max": 4096, "step": 1}], "line_width": ["INT", {"default": 4, "min": 1, "max": 4096, "step": 1}], "speed": ["FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}], "frame_width": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "frame_height": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}]}}, "input_order": {"required": ["frames", "num_points", "line_width", "speed", "frame_width", "frame_height"]}, "output": ["MASK", "MASK"], "output_is_list": [false, false], "output_name": ["mask", "mask_inverted"], "name": "CreateVoronoiMask", "display_name": "Create Voronoi Mask", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/generate", "output_node": false}, "CreateMagicMask": {"input": {"required": {"frames": ["INT", {"default": 16, "min": 2, "max": 4096, "step": 1}], "depth": ["INT", {"default": 12, "min": 1, "max": 500, "step": 1}], "distortion": ["FLOAT", {"default": 1.5, "min": 0.0, "max": 100.0, "step": 0.01}], "seed": ["INT", {"default": 123, "min": 0, "max": 99999999, "step": 1}], "transitions": ["INT", {"default": 1, "min": 1, "max": 20, "step": 1}], "frame_width": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "frame_height": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}]}}, "input_order": {"required": ["frames", "depth", "distortion", "seed", "transitions", "frame_width", "frame_height"]}, "output": ["MASK", "MASK"], "output_is_list": [false, false], "output_name": ["mask", "mask_inverted"], "name": "CreateMagicMask", "display_name": "Create Magic Mask", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/generate", "output_node": false}, "GetMaskSizeAndCount": {"input": {"required": {"mask": ["MASK"]}}, "input_order": {"required": ["mask"]}, "output": ["MASK", "INT", "INT", "INT"], "output_is_list": [false, false, false, false], "output_name": ["mask", "width", "height", "count"], "name": "GetMaskSizeAndCount", "display_name": "Get Mask Size & Count", "description": "\nReturns the width, height and batch size of the mask, \nand passes it through unchanged. \n\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "GrowMaskWithBlur": {"input": {"required": {"mask": ["MASK"], "expand": ["INT", {"default": 0, "min": -16384, "max": 16384, "step": 1}], "incremental_expandrate": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 100.0, "step": 0.1}], "tapered_corners": ["BOOLEAN", {"default": true}], "flip_input": ["BOOLEAN", {"default": false}], "blur_radius": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 100, "step": 0.1}], "lerp_alpha": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}], "decay_factor": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}]}, "optional": {"fill_holes": ["BOOLEAN", {"default": false}]}}, "input_order": {"required": ["mask", "expand", "incremental_expandrate", "tapered_corners", "flip_input", "blur_radius", "lerp_alpha", "decay_factor"], "optional": ["fill_holes"]}, "output": ["MASK", "MASK"], "output_is_list": [false, false], "output_name": ["mask", "mask_inverted"], "name": "GrowMaskWithBlur", "display_name": "Grow Mask With Blur", "description": "\n# GrowMaskWithBlur\n- mask: Input mask or mask batch\n- expand: Expand or contract mask or mask batch by a given amount\n- incremental_expandrate: increase expand rate by a given amount per frame\n- tapered_corners: use tapered corners\n- flip_input: flip input mask\n- blur_radius: value higher than 0 will blur the mask\n- lerp_alpha: alpha value for interpolation between frames\n- decay_factor: decay value for interpolation between frames\n- fill_holes: fill holes in the mask (slow)", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "MaskBatchMulti": {"input": {"required": {"inputcount": ["INT", {"default": 2, "min": 2, "max": 1000, "step": 1}], "mask_1": ["MASK"], "mask_2": ["MASK"]}}, "input_order": {"required": ["inputcount", "mask_1", "mask_2"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["masks"], "name": "MaskBatchMulti", "display_name": "Mask Batch Multi", "description": "\nCreates an image batch from multiple masks. \nYou can set how many inputs the node has, \nwith the **inputcount** and clicking update.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "OffsetMask": {"input": {"required": {"mask": ["MASK"], "x": ["INT", {"default": 0, "min": -4096, "max": 16384, "step": 1, "display": "number"}], "y": ["INT", {"default": 0, "min": -4096, "max": 16384, "step": 1, "display": "number"}], "angle": ["INT", {"default": 0, "min": -360, "max": 360, "step": 1, "display": "number"}], "duplication_factor": ["INT", {"default": 1, "min": 1, "max": 1000, "step": 1, "display": "number"}], "roll": ["BOOLEAN", {"default": false}], "incremental": ["BOOLEAN", {"default": false}], "padding_mode": [["empty", "border", "reflection"], {"default": "empty"}]}}, "input_order": {"required": ["mask", "x", "y", "angle", "duplication_factor", "roll", "incremental", "padding_mode"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["mask"], "name": "OffsetMask", "display_name": "Offset Mask", "description": "\nOffsets the mask by the specified amount. \n - mask: Input mask or mask batch\n - x: Horizontal offset\n - y: Vertical offset\n - angle: Angle in degrees\n - roll: roll edge wrapping\n - duplication_factor: Number of times to duplicate the mask to form a batch\n - border padding_mode: Padding mode for the mask\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "RemapMaskRange": {"input": {"required": {"mask": ["MASK"], "min": ["FLOAT", {"default": 0.0, "min": -10.0, "max": 1.0, "step": 0.01}], "max": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}]}}, "input_order": {"required": ["mask", "min", "max"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["mask"], "name": "RemapMaskRange", "display_name": "Remap Mask Range", "description": "\nSets new min and max values for the mask.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "ResizeMask": {"input": {"required": {"mask": ["MASK"], "width": ["INT", {"default": 512, "min": 0, "max": 16384, "step": 8, "display": "number"}], "height": ["INT", {"default": 512, "min": 0, "max": 16384, "step": 8, "display": "number"}], "keep_proportions": ["BOOLEAN", {"default": false}]}}, "input_order": {"required": ["mask", "width", "height", "keep_proportions"]}, "output": ["MASK", "INT", "INT"], "output_is_list": [false, false, false], "output_name": ["mask", "width", "height"], "name": "ResizeMask", "display_name": "Resize Mask", "description": "\nResizes the mask or batch of masks to the specified width and height.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "RoundMask": {"input": {"required": {"mask": ["MASK"]}}, "input_order": {"required": ["mask"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["MASK"], "name": "RoundMask", "display_name": "Round Mask", "description": "\nRounds the mask or batch of masks to a binary mask. \n $\"RoundMask$ \n\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "AddLabel": {"input": {"required": {"image": ["IMAGE"], "text_x": ["INT", {"default": 10, "min": 0, "max": 4096, "step": 1}], "text_y": ["INT", {"default": 2, "min": 0, "max": 4096, "step": 1}], "height": ["INT", {"default": 48, "min": 0, "max": 4096, "step": 1}], "font_size": ["INT", {"default": 32, "min": 0, "max": 4096, "step": 1}], "font_color": ["STRING", {"default": "white"}], "label_color": ["STRING", {"default": "black"}], "font": [["FreeMono.ttf", "FreeMonoBoldOblique.otf", "TTNorms-Black.otf"]], "text": ["STRING", {"default": "Text"}], "direction": [["up", "down", "left", "right", "overlay"], {"default": "up"}]}, "optional": {"caption": ["STRING", {"default": "", "forceInput": true}]}}, "input_order": {"required": ["image", "text_x", "text_y", "height", "font_size", "font_color", "label_color", "font", "text", "direction"], "optional": ["caption"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "AddLabel", "display_name": "Add Label", "description": "\nCreates a new with the given text, and concatenates it to \neither above or below the input image. \nNote that this changes the input image's height! \nFonts are loaded from this folder: \nComfyUI/custom_nodes/ComfyUI-KJNodes/fonts\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/text", "output_node": false}, "ColorMatch": {"input": {"required": {"image_ref": ["IMAGE"], "image_target": ["IMAGE"], "method": [["mkl", "hm", "reinhard", "mvgd", "hm-mvgd-hm", "hm-mkl-hm"], {"default": "mkl"}]}, "optional": {"strength": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}]}}, "input_order": {"required": ["image_ref", "image_target", "method"], "optional": ["strength"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["image"], "name": "ColorMatch", "display_name": "Color Match", "description": "\ncolor-matcher enables color transfer across images which comes in handy for automatic \ncolor-grading of photographs, paintings and film sequences as well as light-field \nand stopmotion corrections. \n\nThe methods behind the mappings are based on the approach from Reinhard et al., \nthe Monge-Kantorovich Linearization (MKL) as proposed by Pitie et al. and our analytical solution \nto a Multi-Variate Gaussian Distribution (MVGD) transfer in conjunction with classical histogram \nmatching. As shown below our HM-MVGD-HM compound outperforms existing methods. \nhttps://github.com/hahnec/color-matcher/\n\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "CrossFadeImages": {"input": {"required": {"images_1": ["IMAGE"], "images_2": ["IMAGE"], "interpolation": [["linear", "ease_in", "ease_out", "ease_in_out", "bounce", "elastic", "glitchy", "exponential_ease_out"]], "transition_start_index": ["INT", {"default": 1, "min": 0, "max": 4096, "step": 1}], "transitioning_frames": ["INT", {"default": 1, "min": 0, "max": 4096, "step": 1}], "start_level": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01}], "end_level": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}]}}, "input_order": {"required": ["images_1", "images_2", "interpolation", "transition_start_index", "transitioning_frames", "start_level", "end_level"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "CrossFadeImages", "display_name": "Cross Fade Images", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "GetImagesFromBatchIndexed": {"input": {"required": {"images": ["IMAGE"], "indexes": ["STRING", {"default": "0, 1, 2", "multiline": true}]}}, "input_order": {"required": ["images", "indexes"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "GetImagesFromBatchIndexed", "display_name": "Get Images From Batch Indexed", "description": "\nSelects and returns the images at the specified indices as an image batch.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "GetImageRangeFromBatch": {"input": {"required": {"start_index": ["INT", {"default": 0, "min": -1, "max": 4096, "step": 1}], "num_frames": ["INT", {"default": 1, "min": 1, "max": 4096, "step": 1}]}, "optional": {"images": ["IMAGE"], "masks": ["MASK"]}}, "input_order": {"required": ["start_index", "num_frames"], "optional": ["images", "masks"]}, "output": ["IMAGE", "MASK"], "output_is_list": [false, false], "output_name": ["IMAGE", "MASK"], "name": "GetImageRangeFromBatch", "display_name": "Get Image or Mask Range From Batch", "description": "\nCreates a new batch using images from the input, \nbatch, starting from start_index.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "GetImageSizeAndCount": {"input": {"required": {"image": ["IMAGE"]}}, "input_order": {"required": ["image"]}, "output": ["IMAGE", "INT", "INT", "INT"], "output_is_list": [false, false, false, false], "output_name": ["image", "width", "height", "count"], "name": "GetImageSizeAndCount", "display_name": "Get Image Size & Count", "description": "\nReturns width, height and batch size of the image, \nand passes it through unchanged. \n\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImageAndMaskPreview": {"input": {"required": {"mask_opacity": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}], "mask_color": ["STRING", {"default": "255, 255, 255"}], "pass_through": ["BOOLEAN", {"default": false}]}, "optional": {"image": ["IMAGE"], "mask": ["MASK"]}, "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}}, "input_order": {"required": ["mask_opacity", "mask_color", "pass_through"], "optional": ["image", "mask"], "hidden": ["prompt", "extra_pnginfo"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["composite"], "name": "ImageAndMaskPreview", "display_name": "ImageAndMaskPreview", "description": "\nPreview an image or a mask, when both inputs are used \ncomposites the mask on top of the image.\nwith pass_through on the preview is disabled and the \ncomposite is returned from the composite slot instead, \nthis allows for the preview to be passed for video combine \nnodes for example.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes", "output_node": true}, "ImageAddMulti": {"input": {"required": {"inputcount": ["INT", {"default": 2, "min": 2, "max": 1000, "step": 1}], "image_1": ["IMAGE"], "image_2": ["IMAGE"], "blending": [["add", "subtract", "multiply", "difference"], {"default": "add"}]}}, "input_order": {"required": ["inputcount", "image_1", "image_2", "blending"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["images"], "name": "ImageAddMulti", "display_name": "Image Add Multi", "description": "\nAdd blends multiple images together. \nYou can set how many inputs the node has, \nwith the **inputcount** and clicking update.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImageBatchMulti": {"input": {"required": {"inputcount": ["INT", {"default": 2, "min": 2, "max": 1000, "step": 1}], "image_1": ["IMAGE"], "image_2": ["IMAGE"]}}, "input_order": {"required": ["inputcount", "image_1", "image_2"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["images"], "name": "ImageBatchMulti", "display_name": "Image Batch Multi", "description": "\nCreates an image batch from multiple images. \nYou can set how many inputs the node has, \nwith the **inputcount** and clicking update.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImageBatchRepeatInterleaving": {"input": {"required": {"images": ["IMAGE"], "repeats": ["INT", {"default": 1, "min": 1, "max": 4096}]}}, "input_order": {"required": ["images", "repeats"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageBatchRepeatInterleaving", "display_name": "ImageBatchRepeatInterleaving", "description": "\nRepeats each image in a batch by the specified number of times. \nExample batch of 5 images: 0, 1 ,2, 3, 4 \nwith repeats 2 becomes batch of 10 images: 0, 0, 1, 1, 2, 2, 3, 3, 4, 4 \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImageBatchTestPattern": {"input": {"required": {"batch_size": ["INT", {"default": 1, "min": 1, "max": 255, "step": 1}], "start_from": ["INT", {"default": 0, "min": 0, "max": 255, "step": 1}], "text_x": ["INT", {"default": 256, "min": 0, "max": 4096, "step": 1}], "text_y": ["INT", {"default": 256, "min": 0, "max": 4096, "step": 1}], "width": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "height": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "font": [["FreeMono.ttf", "FreeMonoBoldOblique.otf", "TTNorms-Black.otf"]], "font_size": ["INT", {"default": 255, "min": 8, "max": 4096, "step": 1}]}}, "input_order": {"required": ["batch_size", "start_from", "text_x", "text_y", "width", "height", "font", "font_size"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageBatchTestPattern", "display_name": "Image Batch Test Pattern", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/text", "output_node": false}, "ImageConcanate": {"input": {"required": {"image1": ["IMAGE"], "image2": ["IMAGE"], "direction": [["right", "down", "left", "up"], {"default": "right"}], "match_image_size": ["BOOLEAN", {"default": true}]}}, "input_order": {"required": ["image1", "image2", "direction", "match_image_size"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageConcanate", "display_name": "Image Concatenate", "description": "\nConcatenates the image2 to image1 in the specified direction.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImageConcatFromBatch": {"input": {"required": {"images": ["IMAGE"], "num_columns": ["INT", {"default": 3, "min": 1, "max": 255, "step": 1}], "match_image_size": ["BOOLEAN", {"default": false}], "max_resolution": ["INT", {"default": 4096}]}}, "input_order": {"required": ["images", "num_columns", "match_image_size", "max_resolution"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageConcatFromBatch", "display_name": "Image Concatenate From Batch", "description": "\n Concatenates images from a batch into a grid with a specified number of columns.\n ", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImageConcatMulti": {"input": {"required": {"inputcount": ["INT", {"default": 2, "min": 2, "max": 1000, "step": 1}], "image_1": ["IMAGE"], "image_2": ["IMAGE"], "direction": [["right", "down", "left", "up"], {"default": "right"}], "match_image_size": ["BOOLEAN", {"default": false}]}}, "input_order": {"required": ["inputcount", "image_1", "image_2", "direction", "match_image_size"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["images"], "name": "ImageConcatMulti", "display_name": "Image Concatenate Multi", "description": "\nCreates an image from multiple images. \nYou can set how many inputs the node has, \nwith the **inputcount** and clicking update.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImageGrabPIL": {"input": {"required": {"x": ["INT", {"default": 0, "min": 0, "max": 4096, "step": 1}], "y": ["INT", {"default": 0, "min": 0, "max": 4096, "step": 1}], "width": ["INT", {"default": 512, "min": 0, "max": 4096, "step": 1}], "height": ["INT", {"default": 512, "min": 0, "max": 4096, "step": 1}], "num_frames": ["INT", {"default": 1, "min": 1, "max": 255, "step": 1}], "delay": ["FLOAT", {"default": 0.1, "min": 0.0, "max": 10.0, "step": 0.01}]}}, "input_order": {"required": ["x", "y", "width", "height", "num_frames", "delay"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["image"], "name": "ImageGrabPIL", "display_name": "Image Grab PIL", "description": "\nCaptures an area specified by screen coordinates. \nCan be used for realtime diffusion with autoqueue.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": false}, "ImageGridComposite2x2": {"input": {"required": {"image1": ["IMAGE"], "image2": ["IMAGE"], "image3": ["IMAGE"], "image4": ["IMAGE"]}}, "input_order": {"required": ["image1", "image2", "image3", "image4"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageGridComposite2x2", "display_name": "Image Grid Composite 2x2", "description": "\nConcatenates the 4 input images into a 2x2 grid. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImageGridComposite3x3": {"input": {"required": {"image1": ["IMAGE"], "image2": ["IMAGE"], "image3": ["IMAGE"], "image4": ["IMAGE"], "image5": ["IMAGE"], "image6": ["IMAGE"], "image7": ["IMAGE"], "image8": ["IMAGE"], "image9": ["IMAGE"]}}, "input_order": {"required": ["image1", "image2", "image3", "image4", "image5", "image6", "image7", "image8", "image9"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageGridComposite3x3", "display_name": "Image Grid Composite 3x3", "description": "\nConcatenates the 9 input images into a 3x3 grid. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImageGridtoBatch": {"input": {"required": {"image": ["IMAGE"], "columns": ["INT", {"default": 3, "min": 2, "max": 8, "tooltip": "The number of columns in the grid."}]}}, "input_order": {"required": ["image", "columns"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageGridtoBatch", "display_name": "Image Grid To Batch", "description": "Converts a grid of images to a batch of images.", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImageNormalize_Neg1_To_1": {"input": {"required": {"images": ["IMAGE"]}}, "input_order": {"required": ["images"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageNormalize_Neg1_To_1", "display_name": "Image Normalize -1 to 1", "description": "\nNormalize the images to be in the range [-1, 1] \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImagePass": {"input": {"required": {}, "optional": {"image": ["IMAGE"]}}, "input_order": {"required": [], "optional": ["image"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImagePass", "display_name": "ImagePass", "description": "\nPasses the image through without modifying it.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImagePadForOutpaintMasked": {"input": {"required": {"image": ["IMAGE"], "left": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "top": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "right": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "bottom": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "feathering": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 1}]}, "optional": {"mask": ["MASK"]}}, "input_order": {"required": ["image", "left", "top", "right", "bottom", "feathering"], "optional": ["mask"]}, "output": ["IMAGE", "MASK"], "output_is_list": [false, false], "output_name": ["IMAGE", "MASK"], "name": "ImagePadForOutpaintMasked", "display_name": "Image Pad For Outpaint Masked", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "image", "output_node": false}, "ImagePadForOutpaintTargetSize": {"input": {"required": {"image": ["IMAGE"], "target_width": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "target_height": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 8}], "feathering": ["INT", {"default": 0, "min": 0, "max": 16384, "step": 1}], "upscale_method": [["nearest-exact", "bilinear", "area", "bicubic", "lanczos"]]}, "optional": {"mask": ["MASK"]}}, "input_order": {"required": ["image", "target_width", "target_height", "feathering", "upscale_method"], "optional": ["mask"]}, "output": ["IMAGE", "MASK"], "output_is_list": [false, false], "output_name": ["IMAGE", "MASK"], "name": "ImagePadForOutpaintTargetSize", "display_name": "Image Pad For Outpaint Target Size", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "image", "output_node": false}, "ImageResizeKJ": {"input": {"required": {"image": ["IMAGE"], "width": ["INT", {"default": 512, "min": 0, "max": 16384, "step": 8}], "height": ["INT", {"default": 512, "min": 0, "max": 16384, "step": 8}], "upscale_method": [["nearest-exact", "bilinear", "area", "bicubic", "lanczos"]], "keep_proportion": ["BOOLEAN", {"default": false}], "divisible_by": ["INT", {"default": 2, "min": 0, "max": 512, "step": 1}]}, "optional": {"width_input": ["INT", {"forceInput": true}], "height_input": ["INT", {"forceInput": true}], "get_image_size": ["IMAGE"], "crop": [["disabled", "center"]]}}, "input_order": {"required": ["image", "width", "height", "upscale_method", "keep_proportion", "divisible_by"], "optional": ["width_input", "height_input", "get_image_size", "crop"]}, "output": ["IMAGE", "INT", "INT"], "output_is_list": [false, false, false], "output_name": ["IMAGE", "width", "height"], "name": "ImageResizeKJ", "display_name": "Resize Image", "description": "\nResizes the image to the specified width and height. \nSize can be retrieved from the inputs, and the final scale \nis determined in this order of importance: \n- get_image_size \n- width_input and height_input \n- width and height widgets \n \nKeep proportions keeps the aspect ratio of the image, by \nhighest dimension. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ImageUpscaleWithModelBatched": {"input": {"required": {"upscale_model": ["UPSCALE_MODEL"], "images": ["IMAGE"], "per_batch": ["INT", {"default": 16, "min": 1, "max": 4096, "step": 1}]}}, "input_order": {"required": ["upscale_model", "images", "per_batch"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageUpscaleWithModelBatched", "display_name": "Image Upscale With Model Batched", "description": "\nSame as ComfyUI native model upscaling node, \nbut allows setting sub-batches for reduced VRAM usage.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "InsertImagesToBatchIndexed": {"input": {"required": {"original_images": ["IMAGE"], "images_to_insert": ["IMAGE"], "indexes": ["STRING", {"default": "0, 1, 2", "multiline": true}]}}, "input_order": {"required": ["original_images", "images_to_insert", "indexes"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "InsertImagesToBatchIndexed", "display_name": "Insert Images To Batch Indexed", "description": "\nInserts images at the specified indices into the original image batch.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "LoadAndResizeImage": {"input": {"required": {"image": [["example.png"], {"image_upload": true}], "resize": ["BOOLEAN", {"default": false}], "width": ["INT", {"default": 512, "min": 0, "max": 16384, "step": 8}], "height": ["INT", {"default": 512, "min": 0, "max": 16384, "step": 8}], "repeat": ["INT", {"default": 1, "min": 1, "max": 4096, "step": 1}], "keep_proportion": ["BOOLEAN", {"default": false}], "divisible_by": ["INT", {"default": 2, "min": 0, "max": 512, "step": 1}], "mask_channel": [["alpha", "red", "green", "blue"], {"tooltip": "Channel to use for the mask output"}], "background_color": ["STRING", {"default": "", "tooltip": "Fills the alpha channel with the specified color."}]}}, "input_order": {"required": ["image", "resize", "width", "height", "repeat", "keep_proportion", "divisible_by", "mask_channel", "background_color"]}, "output": ["IMAGE", "MASK", "INT", "INT", "STRING"], "output_is_list": [false, false, false, false, false], "output_name": ["image", "mask", "width", "height", "image_path"], "name": "LoadAndResizeImage", "display_name": "Load & Resize Image", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "LoadImagesFromFolderKJ": {"input": {"required": {"folder": ["STRING", {"default": ""}]}, "optional": {"image_load_cap": ["INT", {"default": 0, "min": 0, "step": 1}], "start_index": ["INT", {"default": 0, "min": 0, "step": 1}]}}, "input_order": {"required": ["folder"], "optional": ["image_load_cap", "start_index"]}, "output": ["IMAGE", "MASK", "INT", "STRING"], "output_is_list": [false, false, false, false], "output_name": ["image", "mask", "count", "image_path"], "name": "LoadImagesFromFolderKJ", "display_name": "Load Images From Folder (KJ)", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "image", "output_node": false}, "MergeImageChannels": {"input": {"required": {"red": ["IMAGE"], "green": ["IMAGE"], "blue": ["IMAGE"]}, "optional": {"alpha": ["MASK", {"default": null}]}}, "input_order": {"required": ["red", "green", "blue"], "optional": ["alpha"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["image"], "name": "MergeImageChannels", "display_name": "Merge Image Channels", "description": "\nMerges channel data into an image. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "PreviewAnimation": {"input": {"required": {"fps": ["FLOAT", {"default": 8.0, "min": 0.01, "max": 1000.0, "step": 0.01}]}, "optional": {"images": ["IMAGE"], "masks": ["MASK"]}}, "input_order": {"required": ["fps"], "optional": ["images", "masks"]}, "output": [], "output_is_list": [], "output_name": [], "name": "PreviewAnimation", "display_name": "Preview Animation", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": true}, "RemapImageRange": {"input": {"required": {"image": ["IMAGE"], "min": ["FLOAT", {"default": 0.0, "min": -10.0, "max": 1.0, "step": 0.01}], "max": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "clamp": ["BOOLEAN", {"default": true}]}}, "input_order": {"required": ["image", "min", "max", "clamp"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "RemapImageRange", "display_name": "Remap Image Range", "description": "\nRemaps the image values to the specified range. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ReverseImageBatch": {"input": {"required": {"images": ["IMAGE"]}}, "input_order": {"required": ["images"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ReverseImageBatch", "display_name": "Reverse Image Batch", "description": "\nReverses the order of the images in a batch.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "ReplaceImagesInBatch": {"input": {"required": {"original_images": ["IMAGE"], "replacement_images": ["IMAGE"], "start_index": ["INT", {"default": 1, "min": 0, "max": 4096, "step": 1}]}}, "input_order": {"required": ["original_images", "replacement_images", "start_index"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ReplaceImagesInBatch", "display_name": "Replace Images In Batch", "description": "\nReplaces the images in a batch, starting from the specified start index, \nwith the replacement images.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "SaveImageWithAlpha": {"input": {"required": {"images": ["IMAGE"], "mask": ["MASK"], "filename_prefix": ["STRING", {"default": "ComfyUI"}]}, "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}}, "input_order": {"required": ["images", "mask", "filename_prefix"], "hidden": ["prompt", "extra_pnginfo"]}, "output": [], "output_is_list": [], "output_name": [], "name": "SaveImageWithAlpha", "display_name": "Save Image With Alpha", "description": "\nSaves an image and mask as .PNG with the mask as the alpha channel. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": true}, "SaveImageKJ": {"input": {"required": {"images": ["IMAGE", {"tooltip": "The images to save."}], "filename_prefix": ["STRING", {"default": "ComfyUI", "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes."}], "output_folder": ["STRING", {"default": "output", "tooltip": "The folder to save the images to."}]}, "optional": {"caption_file_extension": ["STRING", {"default": ".txt", "tooltip": "The extension for the caption file."}], "caption": ["STRING", {"forceInput": true, "tooltip": "string to save as .txt file"}]}, "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}}, "input_order": {"required": ["images", "filename_prefix", "output_folder"], "optional": ["caption_file_extension", "caption"], "hidden": ["prompt", "extra_pnginfo"]}, "output": ["STRING"], "output_is_list": [false], "output_name": ["filename"], "name": "SaveImageKJ", "display_name": "Save Image KJ", "description": "Saves the input images to your ComfyUI output directory.", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "image", "output_node": true}, "SplitImageChannels": {"input": {"required": {"image": ["IMAGE"]}}, "input_order": {"required": ["image"]}, "output": ["IMAGE", "IMAGE", "IMAGE", "MASK"], "output_is_list": [false, false, false, false], "output_name": ["red", "green", "blue", "mask"], "name": "SplitImageChannels", "display_name": "Split Image Channels", "description": "\nSplits image channels into images where the selected channel \nis repeated for all channels, and the alpha as a mask. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "BatchCropFromMask": {"input": {"required": {"original_images": ["IMAGE"], "masks": ["MASK"], "crop_size_mult": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}], "bbox_smooth_alpha": ["FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}]}}, "input_order": {"required": ["original_images", "masks", "crop_size_mult", "bbox_smooth_alpha"]}, "output": ["IMAGE", "IMAGE", "BBOX", "INT", "INT"], "output_is_list": [false, false, false, false, false], "output_name": ["original_images", "cropped_images", "bboxes", "width", "height"], "name": "BatchCropFromMask", "display_name": "Batch Crop From Mask", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "BatchCropFromMaskAdvanced": {"input": {"required": {"original_images": ["IMAGE"], "masks": ["MASK"], "crop_size_mult": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "bbox_smooth_alpha": ["FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}]}}, "input_order": {"required": ["original_images", "masks", "crop_size_mult", "bbox_smooth_alpha"]}, "output": ["IMAGE", "IMAGE", "MASK", "IMAGE", "MASK", "BBOX", "BBOX", "INT", "INT"], "output_is_list": [false, false, false, false, false, false, false, false, false], "output_name": ["original_images", "cropped_images", "cropped_masks", "combined_crop_image", "combined_crop_masks", "bboxes", "combined_bounding_box", "bbox_width", "bbox_height"], "name": "BatchCropFromMaskAdvanced", "display_name": "Batch Crop From Mask Advanced", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "FilterZeroMasksAndCorrespondingImages": {"input": {"required": {"masks": ["MASK"]}, "optional": {"original_images": ["IMAGE"]}}, "input_order": {"required": ["masks"], "optional": ["original_images"]}, "output": ["MASK", "IMAGE", "IMAGE", "INDEXES"], "output_is_list": [false, false, false, false], "output_name": ["non_zero_masks_out", "non_zero_mask_images_out", "zero_mask_images_out", "zero_mask_images_out_indexes"], "name": "FilterZeroMasksAndCorrespondingImages", "display_name": "FilterZeroMasksAndCorrespondingImages", "description": "\nFilter out all the empty (i.e. all zero) mask in masks \nAlso filter out all the corresponding images in original_images by indexes if provide \n \noriginal_images (optional): If provided, need have same length as masks.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "InsertImageBatchByIndexes": {"input": {"required": {"images": ["IMAGE"], "images_to_insert": ["IMAGE"], "insert_indexes": ["INDEXES"]}}, "input_order": {"required": ["images", "images_to_insert", "insert_indexes"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["images_after_insert"], "name": "InsertImageBatchByIndexes", "display_name": "Insert Image Batch By Indexes", "description": "\nThis node is designed to be use with node FilterZeroMasksAndCorrespondingImages\nIt inserts the images_to_insert into images according to insert_indexes\n\nReturns:\n images_after_insert: updated original images with origonal sequence order\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "BatchUncrop": {"input": {"required": {"original_images": ["IMAGE"], "cropped_images": ["IMAGE"], "bboxes": ["BBOX"], "border_blending": ["FLOAT", {"default": 0.25, "min": 0.0, "max": 1.0, "step": 0.01}], "crop_rescale": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "border_top": ["BOOLEAN", {"default": true}], "border_bottom": ["BOOLEAN", {"default": true}], "border_left": ["BOOLEAN", {"default": true}], "border_right": ["BOOLEAN", {"default": true}]}}, "input_order": {"required": ["original_images", "cropped_images", "bboxes", "border_blending", "crop_rescale", "border_top", "border_bottom", "border_left", "border_right"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "BatchUncrop", "display_name": "Batch Uncrop", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "BatchUncropAdvanced": {"input": {"required": {"original_images": ["IMAGE"], "cropped_images": ["IMAGE"], "cropped_masks": ["MASK"], "combined_crop_mask": ["MASK"], "bboxes": ["BBOX"], "border_blending": ["FLOAT", {"default": 0.25, "min": 0.0, "max": 1.0, "step": 0.01}], "crop_rescale": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}], "use_combined_mask": ["BOOLEAN", {"default": false}], "use_square_mask": ["BOOLEAN", {"default": true}]}, "optional": {"combined_bounding_box": ["BBOX", {"default": null}]}}, "input_order": {"required": ["original_images", "cropped_images", "cropped_masks", "combined_crop_mask", "bboxes", "border_blending", "crop_rescale", "use_combined_mask", "use_square_mask"], "optional": ["combined_bounding_box"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "BatchUncropAdvanced", "display_name": "Batch Uncrop Advanced", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "SplitBboxes": {"input": {"required": {"bboxes": ["BBOX"], "index": ["INT", {"default": 0, "min": 0, "max": 99999999, "step": 1}]}}, "input_order": {"required": ["bboxes", "index"]}, "output": ["BBOX", "BBOX"], "output_is_list": [false, false], "output_name": ["bboxes_a", "bboxes_b"], "name": "SplitBboxes", "display_name": "Split Bboxes", "description": "\nSplits the specified bbox list at the given index into two lists.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "BboxToInt": {"input": {"required": {"bboxes": ["BBOX"], "index": ["INT", {"default": 0, "min": 0, "max": 99999999, "step": 1}]}}, "input_order": {"required": ["bboxes", "index"]}, "output": ["INT", "INT", "INT", "INT", "INT", "INT"], "output_is_list": [false, false, false, false, false, false], "output_name": ["x_min", "y_min", "width", "height", "center_x", "center_y"], "name": "BboxToInt", "display_name": "Bbox To Int", "description": "\nReturns selected index from bounding box list as integers.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "BboxVisualize": {"input": {"required": {"images": ["IMAGE"], "bboxes": ["BBOX"], "line_width": ["INT", {"default": 1, "min": 1, "max": 10, "step": 1}]}}, "input_order": {"required": ["images", "bboxes", "line_width"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["images"], "name": "BboxVisualize", "display_name": "Bbox Visualize", "description": "\nVisualizes the specified bbox on the image.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking", "output_node": false}, "GenerateNoise": {"input": {"required": {"width": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "height": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "batch_size": ["INT", {"default": 1, "min": 1, "max": 4096}], "seed": ["INT", {"default": 123, "min": 0, "max": 18446744073709551615, "step": 1}], "multiplier": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 4096, "step": 0.01}], "constant_batch_noise": ["BOOLEAN", {"default": false}], "normalize": ["BOOLEAN", {"default": false}]}, "optional": {"model": ["MODEL"], "sigmas": ["SIGMAS"], "latent_channels": [["4", "16"]]}}, "input_order": {"required": ["width", "height", "batch_size", "seed", "multiplier", "constant_batch_noise", "normalize"], "optional": ["model", "sigmas", "latent_channels"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "GenerateNoise", "display_name": "Generate Noise", "description": "\nGenerates noise for injection or to be used as empty latents on samplers with add_noise off.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/noise", "output_node": false}, "FlipSigmasAdjusted": {"input": {"required": {"sigmas": ["SIGMAS"], "divide_by_last_sigma": ["BOOLEAN", {"default": false}], "divide_by": ["FLOAT", {"default": 1, "min": 1, "max": 255, "step": 0.01}], "offset_by": ["INT", {"default": 1, "min": -100, "max": 100, "step": 1}]}}, "input_order": {"required": ["sigmas", "divide_by_last_sigma", "divide_by", "offset_by"]}, "output": ["SIGMAS", "STRING"], "output_is_list": [false, false], "output_name": ["SIGMAS", "sigmas_string"], "name": "FlipSigmasAdjusted", "display_name": "Flip Sigmas Adjusted", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/noise", "output_node": false}, "InjectNoiseToLatent": {"input": {"required": {"latents": ["LATENT"], "strength": ["FLOAT", {"default": 0.1, "min": 0.0, "max": 200.0, "step": 0.0001}], "noise": ["LATENT"], "normalize": ["BOOLEAN", {"default": false}], "average": ["BOOLEAN", {"default": false}]}, "optional": {"mask": ["MASK"], "mix_randn_amount": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.001}], "seed": ["INT", {"default": 123, "min": 0, "max": 18446744073709551615, "step": 1}]}}, "input_order": {"required": ["latents", "strength", "noise", "normalize", "average"], "optional": ["mask", "mix_randn_amount", "seed"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "InjectNoiseToLatent", "display_name": "Inject Noise To Latent", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/noise", "output_node": false}, "CustomSigmas": {"input": {"required": {"sigmas_string": ["STRING", {"default": "14.615, 6.475, 3.861, 2.697, 1.886, 1.396, 0.963, 0.652, 0.399, 0.152, 0.029", "multiline": true}], "interpolate_to_steps": ["INT", {"default": 10, "min": 0, "max": 255, "step": 1}]}}, "input_order": {"required": ["sigmas_string", "interpolate_to_steps"]}, "output": ["SIGMAS"], "output_is_list": [false], "output_name": ["SIGMAS"], "name": "CustomSigmas", "display_name": "Custom Sigmas", "description": "\nCreates a sigmas tensor from a string of comma separated values. \nExamples: \n \nNvidia's optimized AYS 10 step schedule for SD 1.5: \n14.615, 6.475, 3.861, 2.697, 1.886, 1.396, 0.963, 0.652, 0.399, 0.152, 0.029 \nSDXL: \n14.615, 6.315, 3.771, 2.181, 1.342, 0.862, 0.555, 0.380, 0.234, 0.113, 0.029 \nSVD: \n700.00, 54.5, 15.886, 7.977, 4.248, 1.789, 0.981, 0.403, 0.173, 0.034, 0.002 \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/noise", "output_node": false}, "WidgetToString": {"input": {"required": {"id": ["INT", {"default": 0}], "widget_name": ["STRING", {"multiline": false}], "return_all": ["BOOLEAN", {"default": false}]}, "optional": {"any_input": ["*", {}], "node_title": ["STRING", {"multiline": false}]}, "hidden": {"extra_pnginfo": "EXTRA_PNGINFO", "prompt": "PROMPT", "unique_id": "UNIQUE_ID"}}, "input_order": {"required": ["id", "widget_name", "return_all"], "optional": ["any_input", "node_title"], "hidden": ["extra_pnginfo", "prompt", "unique_id"]}, "output": ["STRING"], "output_is_list": [false], "output_name": ["STRING"], "name": "WidgetToString", "display_name": "Widget To String", "description": "\nSelects a node and it's specified widget and outputs the value as a string. \nIf no node id or title is provided it will use the 'any_input' link and use that node. \nTo see node id's, enable node id display from Manager badge menu. \nAlternatively you can search with the node title. Node titles ONLY exist if they \nare manually edited! \nThe 'any_input' is required for making sure the node you want the value from exists in the workflow.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/text", "output_node": false}, "DummyOut": {"input": {"required": {"any_input": ["*", {}]}}, "input_order": {"required": ["any_input"]}, "output": ["*"], "output_is_list": [false], "output_name": ["*"], "name": "DummyOut", "display_name": "Dummy Out", "description": "\nDoes nothing, used to trigger generic workflow output. \nA way to get previews in the UI without saving anything to disk.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/misc", "output_node": true}, "GetLatentsFromBatchIndexed": {"input": {"required": {"latents": ["LATENT"], "indexes": ["STRING", {"default": "0, 1, 2", "multiline": true}]}}, "input_order": {"required": ["latents", "indexes"]}, "output": ["LATENT"], "output_is_list": [false], "output_name": ["LATENT"], "name": "GetLatentsFromBatchIndexed", "display_name": "Get Latents From Batch Indexed", "description": "\nSelects and returns the latents at the specified indices as an latent batch.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes", "output_node": false}, "ScaleBatchPromptSchedule": {"input": {"required": {"input_str": ["STRING", {"forceInput": true, "default": "0:(0.0),\n7:(1.0),\n15:(0.0)\n"}], "old_frame_count": ["INT", {"forceInput": true, "default": 1, "min": 1, "max": 4096, "step": 1}], "new_frame_count": ["INT", {"forceInput": true, "default": 1, "min": 1, "max": 4096, "step": 1}]}}, "input_order": {"required": ["input_str", "old_frame_count", "new_frame_count"]}, "output": ["STRING"], "output_is_list": [false], "output_name": ["STRING"], "name": "ScaleBatchPromptSchedule", "display_name": "Scale Batch Prompt Schedule", "description": "\nScales a batch schedule from Fizz' nodes BatchPromptSchedule\nto a different frame count.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes", "output_node": false}, "CameraPoseVisualizer": {"input": {"required": {"pose_file_path": ["STRING", {"default": "", "multiline": false}], "base_xval": ["FLOAT", {"default": 0.2, "min": 0, "max": 100, "step": 0.01}], "zval": ["FLOAT", {"default": 0.3, "min": 0, "max": 100, "step": 0.01}], "scale": ["FLOAT", {"default": 1.0, "min": 0.01, "max": 10.0, "step": 0.01}], "use_exact_fx": ["BOOLEAN", {"default": false}], "relative_c2w": ["BOOLEAN", {"default": true}], "use_viewer": ["BOOLEAN", {"default": false}]}, "optional": {"cameractrl_poses": ["CAMERACTRL_POSES", {"default": null}]}}, "input_order": {"required": ["pose_file_path", "base_xval", "zval", "scale", "use_exact_fx", "relative_c2w", "use_viewer"], "optional": ["cameractrl_poses"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "CameraPoseVisualizer", "display_name": "Camera Pose Visualizer", "description": "\nVisualizes the camera poses, from Animatediff-Evolved CameraCtrl Pose \nor a .txt file with RealEstate camera intrinsics and coordinates, in a 3D plot. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/misc", "output_node": false}, "JoinStrings": {"input": {"required": {"string1": ["STRING", {"default": "", "forceInput": true}], "string2": ["STRING", {"default": "", "forceInput": true}], "delimiter": ["STRING", {"default": " ", "multiline": false}]}}, "input_order": {"required": ["string1", "string2", "delimiter"]}, "output": ["STRING"], "output_is_list": [false], "output_name": ["STRING"], "name": "JoinStrings", "display_name": "Join Strings", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/constants", "output_node": false}, "JoinStringMulti": {"input": {"required": {"inputcount": ["INT", {"default": 2, "min": 2, "max": 1000, "step": 1}], "string_1": ["STRING", {"default": "", "forceInput": true}], "string_2": ["STRING", {"default": "", "forceInput": true}], "delimiter": ["STRING", {"default": " ", "multiline": false}], "return_list": ["BOOLEAN", {"default": false}]}}, "input_order": {"required": ["inputcount", "string_1", "string_2", "delimiter", "return_list"]}, "output": ["STRING"], "output_is_list": [false], "output_name": ["string"], "name": "JoinStringMulti", "display_name": "Join String Multi", "description": "\nCreates single string, or a list of strings, from \nmultiple input strings. \nYou can set how many inputs the node has, \nwith the **inputcount** and clicking update.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes", "output_node": false}, "SomethingToString": {"input": {"required": {"input": ["*", {}]}, "optional": {"prefix": ["STRING", {"default": ""}], "suffix": ["STRING", {"default": ""}]}}, "input_order": {"required": ["input"], "optional": ["prefix", "suffix"]}, "output": ["STRING"], "output_is_list": [false], "output_name": ["STRING"], "name": "SomethingToString", "display_name": "Something To String", "description": "\nConverts any type to a string.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/text", "output_node": false}, "Sleep": {"input": {"required": {"input": ["*", {}], "minutes": ["INT", {"default": 0, "min": 0, "max": 1439}], "seconds": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 59.99, "step": 0.01}]}}, "input_order": {"required": ["input", "minutes", "seconds"]}, "output": ["*"], "output_is_list": [false], "output_name": ["*"], "name": "Sleep", "display_name": "Sleep", "description": "\nDelays the execution for the input amount of time.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/misc", "output_node": false}, "VRAM_Debug": {"input": {"required": {"empty_cache": ["BOOLEAN", {"default": true}], "gc_collect": ["BOOLEAN", {"default": true}], "unload_all_models": ["BOOLEAN", {"default": false}]}, "optional": {"any_input": ["*", {}], "image_pass": ["IMAGE"], "model_pass": ["MODEL"]}}, "input_order": {"required": ["empty_cache", "gc_collect", "unload_all_models"], "optional": ["any_input", "image_pass", "model_pass"]}, "output": ["*", "IMAGE", "MODEL", "INT", "INT"], "output_is_list": [false, false, false, false, false], "output_name": ["any_output", "image_pass", "model_pass", "freemem_before", "freemem_after"], "name": "VRAM_Debug", "display_name": "VRAM Debug", "description": "\nReturns the inputs unchanged, they are only used as triggers, \nand performs comfy model management functions and garbage collection, \nreports free VRAM before and after the operations.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/misc", "output_node": false}, "EmptyLatentImagePresets": {"input": {"required": {"dimensions": [["512 x 512 (1:1)", "768 x 512 (1.5:1)", "960 x 512 (1.875:1)", "1024 x 512 (2:1)", "1024 x 576 (1.778:1)", "1536 x 640 (2.4:1)", "1344 x 768 (1.75:1)", "1216 x 832 (1.46:1)", "1152 x 896 (1.286:1)", "1024 x 1024 (1:1)"], {"default": "512 x 512 (1:1)"}], "invert": ["BOOLEAN", {"default": false}], "batch_size": ["INT", {"default": 1, "min": 1, "max": 4096}]}}, "input_order": {"required": ["dimensions", "invert", "batch_size"]}, "output": ["LATENT", "INT", "INT"], "output_is_list": [false, false, false], "output_name": ["Latent", "Width", "Height"], "name": "EmptyLatentImagePresets", "display_name": "Empty Latent Image Presets", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes", "output_node": false}, "EmptyLatentImageCustomPresets": {"input": {"required": {"dimensions": [["SD - 512x512", "HD - 768x768", "Full HD - 1024x1024", "4k - 2048x2048", "SVD - 1024x576"]], "invert": ["BOOLEAN", {"default": false}], "batch_size": ["INT", {"default": 1, "min": 1, "max": 4096}]}}, "input_order": {"required": ["dimensions", "invert", "batch_size"]}, "output": ["LATENT", "INT", "INT"], "output_is_list": [false, false, false], "output_name": ["Latent", "Width", "Height"], "name": "EmptyLatentImageCustomPresets", "display_name": "Empty Latent Image Custom Presets", "description": "\nGenerates an empty latent image with the specified dimensions. \nThe choices are loaded from 'custom_dimensions.json' in the nodes folder.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes", "output_node": false}, "ModelPassThrough": {"input": {"required": {}, "optional": {"model": ["MODEL"]}}, "input_order": {"required": [], "optional": ["model"]}, "output": ["MODEL"], "output_is_list": [false], "output_name": ["model"], "name": "ModelPassThrough", "display_name": "ModelPass", "description": "\n Simply passes through the model,\n workaround for Set node not allowing bypassed inputs.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/misc", "output_node": false}, "SetShakkerLabsUnionControlNetType": {"input": {"required": {"control_net": ["CONTROL_NET"], "type": [["auto", "canny", "tile", "depth", "blur", "pose", "gray", "low quality"]]}}, "input_order": {"required": ["control_net", "type"]}, "output": ["CONTROL_NET"], "output_is_list": [false], "output_name": ["CONTROL_NET"], "name": "SetShakkerLabsUnionControlNetType", "display_name": "Set Shakker Labs Union ControlNet Type", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "conditioning/controlnet", "output_node": false}, "NormalizedAmplitudeToMask": {"input": {"required": {"normalized_amp": ["NORMALIZED_AMPLITUDE"], "width": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "height": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "frame_offset": ["INT", {"default": 0, "min": -255, "max": 255, "step": 1}], "location_x": ["INT", {"default": 256, "min": 0, "max": 4096, "step": 1}], "location_y": ["INT", {"default": 256, "min": 0, "max": 4096, "step": 1}], "size": ["INT", {"default": 128, "min": 8, "max": 4096, "step": 1}], "shape": [["none", "circle", "square", "triangle"], {"default": "none"}], "color": [["white", "amplitude"], {"default": "amplitude"}]}}, "input_order": {"required": ["normalized_amp", "width", "height", "frame_offset", "location_x", "location_y", "size", "shape", "color"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["MASK"], "name": "NormalizedAmplitudeToMask", "display_name": "NormalizedAmplitudeToMask", "description": "\nWorks as a bridge to the AudioScheduler -nodes: \nhttps://github.com/a1lazydog/ComfyUI-AudioScheduler \nCreates masks based on the normalized amplitude.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/audio", "output_node": false}, "NormalizedAmplitudeToFloatList": {"input": {"required": {"normalized_amp": ["NORMALIZED_AMPLITUDE"]}}, "input_order": {"required": ["normalized_amp"]}, "output": ["FLOAT"], "output_is_list": [false], "output_name": ["FLOAT"], "name": "NormalizedAmplitudeToFloatList", "display_name": "NormalizedAmplitudeToFloatList", "description": "\nWorks as a bridge to the AudioScheduler -nodes: \nhttps://github.com/a1lazydog/ComfyUI-AudioScheduler \nCreates a list of floats from the normalized amplitude.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/audio", "output_node": false}, "OffsetMaskByNormalizedAmplitude": {"input": {"required": {"normalized_amp": ["NORMALIZED_AMPLITUDE"], "mask": ["MASK"], "x": ["INT", {"default": 0, "min": -4096, "max": 16384, "step": 1, "display": "number"}], "y": ["INT", {"default": 0, "min": -4096, "max": 16384, "step": 1, "display": "number"}], "rotate": ["BOOLEAN", {"default": false}], "angle_multiplier": ["FLOAT", {"default": 0.0, "min": -1.0, "max": 1.0, "step": 0.001, "display": "number"}]}}, "input_order": {"required": ["normalized_amp", "mask", "x", "y", "rotate", "angle_multiplier"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["mask"], "name": "OffsetMaskByNormalizedAmplitude", "display_name": "OffsetMaskByNormalizedAmplitude", "description": "\nWorks as a bridge to the AudioScheduler -nodes: \nhttps://github.com/a1lazydog/ComfyUI-AudioScheduler \nOffsets masks based on the normalized amplitude.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/audio", "output_node": false}, "ImageTransformByNormalizedAmplitude": {"input": {"required": {"normalized_amp": ["NORMALIZED_AMPLITUDE"], "zoom_scale": ["FLOAT", {"default": 0.0, "min": -1.0, "max": 1.0, "step": 0.001, "display": "number"}], "x_offset": ["INT", {"default": 0, "min": -16383, "max": 16384, "step": 1, "display": "number"}], "y_offset": ["INT", {"default": 0, "min": -16383, "max": 16384, "step": 1, "display": "number"}], "cumulative": ["BOOLEAN", {"default": false}], "image": ["IMAGE"]}}, "input_order": {"required": ["normalized_amp", "zoom_scale", "x_offset", "y_offset", "cumulative", "image"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "ImageTransformByNormalizedAmplitude", "display_name": "ImageTransformByNormalizedAmplitude", "description": "\nWorks as a bridge to the AudioScheduler -nodes: \nhttps://github.com/a1lazydog/ComfyUI-AudioScheduler \nTransforms image based on the normalized amplitude.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/audio", "output_node": false}, "SplineEditor": {"input": {"required": {"points_store": ["STRING", {"multiline": false}], "coordinates": ["STRING", {"multiline": false}], "mask_width": ["INT", {"default": 512, "min": 8, "max": 4096, "step": 8}], "mask_height": ["INT", {"default": 512, "min": 8, "max": 4096, "step": 8}], "points_to_sample": ["INT", {"default": 16, "min": 2, "max": 1000, "step": 1}], "sampling_method": [["path", "time", "controlpoints"], {"default": "time"}], "interpolation": [["cardinal", "monotone", "basis", "linear", "step-before", "step-after", "polar", "polar-reverse"], {"default": "cardinal"}], "tension": ["FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}], "repeat_output": ["INT", {"default": 1, "min": 1, "max": 4096, "step": 1}], "float_output_type": [["list", "pandas series", "tensor"], {"default": "list"}]}, "optional": {"min_value": ["FLOAT", {"default": 0.0, "min": -10000.0, "max": 10000.0, "step": 0.01}], "max_value": ["FLOAT", {"default": 1.0, "min": -10000.0, "max": 10000.0, "step": 0.01}]}}, "input_order": {"required": ["points_store", "coordinates", "mask_width", "mask_height", "points_to_sample", "sampling_method", "interpolation", "tension", "repeat_output", "float_output_type"], "optional": ["min_value", "max_value"]}, "output": ["MASK", "STRING", "FLOAT", "INT", "STRING"], "output_is_list": [false, false, false, false, false], "output_name": ["mask", "coord_str", "float", "count", "normalized_str"], "name": "SplineEditor", "display_name": "Spline Editor", "description": "\n# WORK IN PROGRESS \nDo not count on this as part of your workflow yet, \nprobably contains lots of bugs and stability is not \nguaranteed!! \n \n## Graphical editor to create values for various \n## schedules and/or mask batches. \n\n**Shift + click** to add control point at end.\n**Ctrl + click** to add control point (subdivide) between two points. \n**Right click on a point** to delete it. \nNote that you can't delete from start/end. \n \nRight click on canvas for context menu: \nThese are purely visual options, doesn't affect the output: \n - Toggle handles visibility\n - Display sample points: display the points to be returned. \n\n**points_to_sample** value sets the number of samples \nreturned from the **drawn spline itself**, this is independent from the \nactual control points, so the interpolation type matters. \nsampling_method: \n - time: samples along the time axis, used for schedules \n - path: samples along the path itself, useful for coordinates \n\noutput types:\n - mask batch \n example compatible nodes: anything that takes masks \n - list of floats\n example compatible nodes: IPAdapter weights \n - pandas series\n example compatible nodes: anything that takes Fizz' \n nodes Batch Value Schedule \n - torch tensor \n example compatible nodes: unknown\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/weights", "output_node": false}, "CreateShapeImageOnPath": {"input": {"required": {"shape": [["circle", "square", "triangle"], {"default": "circle"}], "coordinates": ["STRING", {"forceInput": true}], "frame_width": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "frame_height": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "shape_width": ["INT", {"default": 128, "min": 8, "max": 4096, "step": 1}], "shape_height": ["INT", {"default": 128, "min": 8, "max": 4096, "step": 1}], "shape_color": ["STRING", {"default": "white"}], "bg_color": ["STRING", {"default": "black"}], "blur_radius": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 100, "step": 0.1}], "intensity": ["FLOAT", {"default": 1.0, "min": 0.01, "max": 100.0, "step": 0.01}]}, "optional": {"size_multiplier": ["FLOAT", {"default": [1.0], "forceInput": true}]}}, "input_order": {"required": ["shape", "coordinates", "frame_width", "frame_height", "shape_width", "shape_height", "shape_color", "bg_color", "blur_radius", "intensity"], "optional": ["size_multiplier"]}, "output": ["IMAGE", "MASK"], "output_is_list": [false, false], "output_name": ["image", "mask"], "name": "CreateShapeImageOnPath", "display_name": "Create Shape Image On Path", "description": "\nCreates an image or batch of images with the specified shape. \nLocations are center locations. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "CreateShapeMaskOnPath": {"input": {"required": {"shape": [["circle", "square", "triangle"], {"default": "circle"}], "coordinates": ["STRING", {"forceInput": true}], "frame_width": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "frame_height": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "shape_width": ["INT", {"default": 128, "min": 8, "max": 4096, "step": 1}], "shape_height": ["INT", {"default": 128, "min": 8, "max": 4096, "step": 1}]}, "optional": {"size_multiplier": ["FLOAT", {"default": [1.0], "forceInput": true}]}}, "input_order": {"required": ["shape", "coordinates", "frame_width", "frame_height", "shape_width", "shape_height"], "optional": ["size_multiplier"]}, "output": ["MASK", "MASK"], "output_is_list": [false, false], "output_name": ["mask", "mask_inverted"], "name": "CreateShapeMaskOnPath", "display_name": "Create Shape Mask On Path", "description": "\nCreates a mask or batch of masks with the specified shape. \nLocations are center locations. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/generate", "output_node": false}, "CreateTextOnPath": {"input": {"required": {"coordinates": ["STRING", {"forceInput": true}], "text": ["STRING", {"default": "text", "multiline": true}], "frame_width": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "frame_height": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "font": [["FreeMono.ttf", "FreeMonoBoldOblique.otf", "TTNorms-Black.otf"]], "font_size": ["INT", {"default": 42}], "alignment": [["left", "center", "right"], {"default": "center"}], "text_color": ["STRING", {"default": "white"}]}, "optional": {"size_multiplier": ["FLOAT", {"default": [1.0], "forceInput": true}]}}, "input_order": {"required": ["coordinates", "text", "frame_width", "frame_height", "font", "font_size", "alignment", "text_color"], "optional": ["size_multiplier"]}, "output": ["IMAGE", "MASK", "MASK"], "output_is_list": [false, false, false], "output_name": ["image", "mask", "mask_inverted"], "name": "CreateTextOnPath", "display_name": "Create Text On Path", "description": "\nCreates a mask or batch of masks with the specified text. \nLocations are center locations. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/generate", "output_node": false}, "CreateGradientFromCoords": {"input": {"required": {"coordinates": ["STRING", {"forceInput": true}], "frame_width": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "frame_height": ["INT", {"default": 512, "min": 16, "max": 4096, "step": 1}], "start_color": ["STRING", {"default": "white"}], "end_color": ["STRING", {"default": "black"}], "multiplier": ["FLOAT", {"default": 1.0, "min": 0.01, "max": 100.0, "step": 0.01}]}}, "input_order": {"required": ["coordinates", "frame_width", "frame_height", "start_color", "end_color", "multiplier"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["image"], "name": "CreateGradientFromCoords", "display_name": "Create Gradient From Coords", "description": "\nCreates a gradient image from coordinates. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "GradientToFloat": {"input": {"required": {"image": ["IMAGE"], "steps": ["INT", {"default": 10, "min": 2, "max": 10000, "step": 1}]}}, "input_order": {"required": ["image", "steps"]}, "output": ["FLOAT", "FLOAT"], "output_is_list": [false, false], "output_name": ["float_x", "float_y"], "name": "GradientToFloat", "display_name": "Gradient To Float", "description": "\nCalculates list of floats from image. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/image", "output_node": false}, "WeightScheduleExtend": {"input": {"required": {"input_values_1": ["FLOAT", {"default": 0.0, "forceInput": true}], "input_values_2": ["FLOAT", {"default": 0.0, "forceInput": true}], "output_type": [["match_input", "list", "pandas series", "tensor"], {"default": "match_input"}]}}, "input_order": {"required": ["input_values_1", "input_values_2", "output_type"]}, "output": ["FLOAT"], "output_is_list": [false], "output_name": ["FLOAT"], "name": "WeightScheduleExtend", "display_name": "Weight Schedule Extend", "description": "\nExtends, and converts if needed, different value lists/series \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/weights", "output_node": false}, "MaskOrImageToWeight": {"input": {"required": {"output_type": [["list", "pandas series", "tensor", "string"], {"default": "list"}]}, "optional": {"images": ["IMAGE"], "masks": ["MASK"]}}, "input_order": {"required": ["output_type"], "optional": ["images", "masks"]}, "output": ["FLOAT", "STRING"], "output_is_list": [false, false], "output_name": ["FLOAT", "STRING"], "name": "MaskOrImageToWeight", "display_name": "Mask Or Image To Weight", "description": "\nGets the mean values from mask or image batch \nand returns that as the selected output type. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/weights", "output_node": false}, "WeightScheduleConvert": {"input": {"required": {"input_values": ["FLOAT", {"default": 0.0, "forceInput": true}], "output_type": [["match_input", "list", "pandas series", "tensor"], {"default": "list"}], "invert": ["BOOLEAN", {"default": false}], "repeat": ["INT", {"default": 1, "min": 1, "max": 255, "step": 1}]}, "optional": {"remap_to_frames": ["INT", {"default": 0}], "interpolation_curve": ["FLOAT", {"forceInput": true}], "remap_values": ["BOOLEAN", {"default": false}], "remap_min": ["FLOAT", {"default": 0.0, "min": -100000, "max": 100000.0, "step": 0.01}], "remap_max": ["FLOAT", {"default": 1.0, "min": -100000, "max": 100000.0, "step": 0.01}]}}, "input_order": {"required": ["input_values", "output_type", "invert", "repeat"], "optional": ["remap_to_frames", "interpolation_curve", "remap_values", "remap_min", "remap_max"]}, "output": ["FLOAT", "STRING", "INT"], "output_is_list": [false, false, false], "output_name": ["FLOAT", "STRING", "INT"], "name": "WeightScheduleConvert", "display_name": "Weight Schedule Convert", "description": "\nConverts different value lists/series to another type. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/weights", "output_node": false}, "FloatToMask": {"input": {"required": {"input_values": ["FLOAT", {"forceInput": true, "default": 0}], "width": ["INT", {"default": 100, "min": 1}], "height": ["INT", {"default": 100, "min": 1}]}}, "input_order": {"required": ["input_values", "width", "height"]}, "output": ["MASK"], "output_is_list": [false], "output_name": ["MASK"], "name": "FloatToMask", "display_name": "Float To Mask", "description": "\nGenerates a batch of masks based on the input float values.\nThe batch size is determined by the length of the input float values.\nEach mask is generated with the specified width and height.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/masking/generate", "output_node": false}, "FloatToSigmas": {"input": {"required": {"float_list": ["FLOAT", {"default": 0.0, "forceInput": true}]}}, "input_order": {"required": ["float_list"]}, "output": ["SIGMAS"], "output_is_list": [false], "output_name": ["SIGMAS"], "name": "FloatToSigmas", "display_name": "Float To Sigmas", "description": "\nCreates a sigmas tensor from list of float values. \n\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/noise", "output_node": false}, "PlotCoordinates": {"input": {"required": {"coordinates": ["STRING", {"forceInput": true}], "text": ["STRING", {"default": "title", "multiline": false}], "width": ["INT", {"default": 512, "min": 8, "max": 4096, "step": 8}], "height": ["INT", {"default": 512, "min": 8, "max": 4096, "step": 8}], "bbox_width": ["INT", {"default": 128, "min": 8, "max": 4096, "step": 8}], "bbox_height": ["INT", {"default": 128, "min": 8, "max": 4096, "step": 8}]}, "optional": {"size_multiplier": ["FLOAT", {"default": [1.0], "forceInput": true}]}}, "input_order": {"required": ["coordinates", "text", "width", "height", "bbox_width", "bbox_height"], "optional": ["size_multiplier"]}, "output": ["IMAGE", "INT", "INT", "INT", "INT"], "output_is_list": [false, false, false, false, false], "output_name": ["images", "width", "height", "bbox_width", "bbox_height"], "name": "PlotCoordinates", "display_name": "Plot Coordinates", "description": "\nPlots coordinates to sequence of images using Matplotlib. \n\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": false}, "InterpolateCoords": {"input": {"required": {"coordinates": ["STRING", {"forceInput": true}], "interpolation_curve": ["FLOAT", {"forceInput": true}]}}, "input_order": {"required": ["coordinates", "interpolation_curve"]}, "output": ["STRING"], "output_is_list": [false], "output_name": ["coordinates"], "name": "InterpolateCoords", "display_name": "Interpolate Coords", "description": "\nInterpolates coordinates based on a curve. \n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": false}, "PointsEditor": {"input": {"required": {"points_store": ["STRING", {"multiline": false}], "coordinates": ["STRING", {"multiline": false}], "neg_coordinates": ["STRING", {"multiline": false}], "bbox_store": ["STRING", {"multiline": false}], "bboxes": ["STRING", {"multiline": false}], "bbox_format": [["xyxy", "xywh"]], "width": ["INT", {"default": 512, "min": 8, "max": 4096, "step": 8}], "height": ["INT", {"default": 512, "min": 8, "max": 4096, "step": 8}], "normalize": ["BOOLEAN", {"default": false}]}, "optional": {"bg_image": ["IMAGE"]}}, "input_order": {"required": ["points_store", "coordinates", "neg_coordinates", "bbox_store", "bboxes", "bbox_format", "width", "height", "normalize"], "optional": ["bg_image"]}, "output": ["STRING", "STRING", "BBOX", "MASK", "IMAGE"], "output_is_list": [false, false, false, false, false], "output_name": ["positive_coords", "negative_coords", "bbox", "bbox_mask", "cropped_image"], "name": "PointsEditor", "display_name": "Points Editor", "description": "\n# WORK IN PROGRESS \nDo not count on this as part of your workflow yet, \nprobably contains lots of bugs and stability is not \nguaranteed!! \n \n## Graphical editor to create coordinates\n\n**Shift + click** to add a positive (green) point.\n**Shift + right click** to add a negative (red) point.\n**Ctrl + click** to draw a box. \n**Right click on a point** to delete it. \nNote that you can't delete from start/end of the points array. \n \nTo add an image select the node and copy/paste or drag in the image. \nOr from the bg_image input on queue (first frame of the batch). \n\n**THE IMAGE IS SAVED TO THE NODE AND WORKFLOW METADATA** \nyou can clear the image from the context menu by right clicking on the canvas \n\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": false}, "StabilityAPI_SD3": {"input": {"required": {"prompt": ["STRING", {"multiline": true}], "n_prompt": ["STRING", {"multiline": true}], "seed": ["INT", {"default": 123, "min": 0, "max": 4294967294, "step": 1}], "model": [["sd3", "sd3-turbo"], {"default": "sd3"}], "aspect_ratio": [["1:1", "16:9", "21:9", "2:3", "3:2", "4:5", "5:4", "9:16", "9:21"], {"default": "1:1"}], "output_format": [["png", "jpeg"], {"default": "jpeg"}]}, "optional": {"api_key": ["STRING", {"multiline": true}], "image": ["IMAGE"], "img2img_strength": ["FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}], "disable_metadata": ["BOOLEAN", {"default": true}]}}, "input_order": {"required": ["prompt", "n_prompt", "seed", "model", "aspect_ratio", "output_format"], "optional": ["api_key", "image", "img2img_strength", "disable_metadata"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["IMAGE"], "name": "StabilityAPI_SD3", "display_name": "Stability API SD3", "description": "\n## Calls StabilityAI API\n \nAlthough you may have multiple keys in your account, \nyou should use the same key for all requests to this API. \n\nGet your API key here: https://platform.stability.ai/account/keys \nRecommended to set the key in the config.json -file under this \nnode packs folder. \n# WARNING: \nOtherwise the API key may get saved in the image metadata even \nwith \"disable_metadata\" on if the workflow includes save nodes \nseparate from this node. \n \nsd3 requires 6.5 credits per generation \nsd3-turbo requires 4 credits per generation \n\nIf no image is provided, mode is set to text-to-image \n\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": false}, "SoundReactive": {"input": {"required": {"sound_level": ["FLOAT", {"default": 1.0, "min": 0.0, "max": 99999, "step": 0.01}], "start_range_hz": ["INT", {"default": 150, "min": 0, "max": 9999, "step": 1}], "end_range_hz": ["INT", {"default": 2000, "min": 0, "max": 9999, "step": 1}], "multiplier": ["FLOAT", {"default": 1.0, "min": 0.01, "max": 99999, "step": 0.01}], "smoothing_factor": ["FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}], "normalize": ["BOOLEAN", {"default": false}]}}, "input_order": {"required": ["sound_level", "start_range_hz", "end_range_hz", "multiplier", "smoothing_factor", "normalize"]}, "output": ["FLOAT", "INT"], "output_is_list": [false, false], "output_name": ["sound_level", "sound_level_int"], "name": "SoundReactive", "display_name": "Sound Reactive", "description": "\nReacts to the sound level of the input. \nUses your browsers sound input options and requires. \nMeant to be used with realtime diffusion with autoqueue.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/audio", "output_node": false}, "StableZero123_BatchSchedule": {"input": {"required": {"clip_vision": ["CLIP_VISION"], "init_image": ["IMAGE"], "vae": ["VAE"], "width": ["INT", {"default": 256, "min": 16, "max": 16384, "step": 8}], "height": ["INT", {"default": 256, "min": 16, "max": 16384, "step": 8}], "batch_size": ["INT", {"default": 1, "min": 1, "max": 4096}], "interpolation": [["linear", "ease_in", "ease_out", "ease_in_out"]], "azimuth_points_string": ["STRING", {"default": "0:(0.0),\n7:(1.0),\n15:(0.0)\n", "multiline": true}], "elevation_points_string": ["STRING", {"default": "0:(0.0),\n7:(0.0),\n15:(0.0)\n", "multiline": true}]}}, "input_order": {"required": ["clip_vision", "init_image", "vae", "width", "height", "batch_size", "interpolation", "azimuth_points_string", "elevation_points_string"]}, "output": ["CONDITIONING", "CONDITIONING", "LATENT"], "output_is_list": [false, false, false], "output_name": ["positive", "negative", "latent"], "name": "StableZero123_BatchSchedule", "display_name": "Stable Zero123 Batch Schedule", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": false}, "SV3D_BatchSchedule": {"input": {"required": {"clip_vision": ["CLIP_VISION"], "init_image": ["IMAGE"], "vae": ["VAE"], "width": ["INT", {"default": 576, "min": 16, "max": 16384, "step": 8}], "height": ["INT", {"default": 576, "min": 16, "max": 16384, "step": 8}], "batch_size": ["INT", {"default": 21, "min": 1, "max": 4096}], "interpolation": [["linear", "ease_in", "ease_out", "ease_in_out"]], "azimuth_points_string": ["STRING", {"default": "0:(0.0),\n9:(180.0),\n20:(360.0)\n", "multiline": true}], "elevation_points_string": ["STRING", {"default": "0:(0.0),\n9:(0.0),\n20:(0.0)\n", "multiline": true}]}}, "input_order": {"required": ["clip_vision", "init_image", "vae", "width", "height", "batch_size", "interpolation", "azimuth_points_string", "elevation_points_string"]}, "output": ["CONDITIONING", "CONDITIONING", "LATENT"], "output_is_list": [false, false, false], "output_name": ["positive", "negative", "latent"], "name": "SV3D_BatchSchedule", "display_name": "SV3D Batch Schedule", "description": "\nAllow scheduling of the azimuth and elevation conditions for SV3D. \nNote that SV3D is still a video model and the schedule needs to always go forward \nhttps://huggingface.co/stabilityai/sv3d\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": false}, "LoadResAdapterNormalization": {"input": {"required": {"model": ["MODEL"], "resadapter_path": [["juggernautXL_juggXIByRundiffusion.safetensors", "realvisxlV50_v50Bakedvae.safetensors"]]}}, "input_order": {"required": ["model", "resadapter_path"]}, "output": ["MODEL"], "output_is_list": [false], "output_name": ["MODEL"], "name": "LoadResAdapterNormalization", "display_name": "LoadResAdapterNormalization", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": false}, "Superprompt": {"input": {"required": {"instruction_prompt": ["STRING", {"default": "Expand the following prompt to add more detail", "multiline": true}], "prompt": ["STRING", {"default": "", "multiline": true, "forceInput": true}], "max_new_tokens": ["INT", {"default": 128, "min": 1, "max": 4096, "step": 1}]}}, "input_order": {"required": ["instruction_prompt", "prompt", "max_new_tokens"]}, "output": ["STRING"], "output_is_list": [false], "output_name": ["STRING"], "name": "Superprompt", "display_name": "Superprompt", "description": "\n# SuperPrompt\nA T5 model fine-tuned on the SuperPrompt dataset for \nupsampling text prompts to more detailed descriptions. \nMeant to be used as a pre-generation step for text-to-image \nmodels that benefit from more detailed prompts. \nhttps://huggingface.co/roborovski/superprompt-v1\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/text", "output_node": false}, "GLIGENTextBoxApplyBatchCoords": {"input": {"required": {"conditioning_to": ["CONDITIONING"], "latents": ["LATENT"], "clip": ["CLIP"], "gligen_textbox_model": ["GLIGEN"], "coordinates": ["STRING", {"forceInput": true}], "text": ["STRING", {"multiline": true}], "width": ["INT", {"default": 128, "min": 8, "max": 4096, "step": 8}], "height": ["INT", {"default": 128, "min": 8, "max": 4096, "step": 8}]}, "optional": {"size_multiplier": ["FLOAT", {"default": [1.0], "forceInput": true}]}}, "input_order": {"required": ["conditioning_to", "latents", "clip", "gligen_textbox_model", "coordinates", "text", "width", "height"], "optional": ["size_multiplier"]}, "output": ["CONDITIONING", "IMAGE"], "output_is_list": [false, false], "output_name": ["conditioning", "coord_preview"], "name": "GLIGENTextBoxApplyBatchCoords", "display_name": "GLIGENTextBoxApplyBatchCoords", "description": "\nThis node allows scheduling GLIGEN text box positions in a batch, \nto be used with AnimateDiff-Evolved. Intended to pair with the \nSpline Editor -node. \n\nGLIGEN model can be downloaded through the Manage's \"Install Models\" menu. \nOr directly from here: \nhttps://huggingface.co/comfyanonymous/GLIGEN_pruned_safetensors/tree/main \n \nInputs: \n- **latents** input is used to calculate batch size \n- **clip** is your standard text encoder, use same as for the main prompt \n- **gligen_textbox_model** connects to GLIGEN Loader \n- **coordinates** takes a json string of points, directly compatible \nwith the spline editor node.\n- **text** is the part of the prompt to set position for \n- **width** and **height** are the size of the GLIGEN bounding box \n \nOutputs:\n- **conditioning** goes between to clip text encode and the sampler \n- **coord_preview** is an optional preview of the coordinates and \nbounding boxes.\n\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": false}, "Intrinsic_lora_sampling": {"input": {"required": {"model": ["MODEL"], "lora_name": [["intrinsic_lora_sd15_albedo.safetensors", "intrinsic_lora_sd15_depth.safetensors", "intrinsic_lora_sd15_normal.safetensors", "intrinsic_lora_sd15_shading.safetensors", "intrinsic_loras.txt"]], "task": [["depth map", "surface normals", "albedo", "shading"], {"default": "depth map"}], "text": ["STRING", {"multiline": true, "default": ""}], "clip": ["CLIP"], "vae": ["VAE"], "per_batch": ["INT", {"default": 16, "min": 1, "max": 4096, "step": 1}]}, "optional": {"image": ["IMAGE"], "optional_latent": ["LATENT"]}}, "input_order": {"required": ["model", "lora_name", "task", "text", "clip", "vae", "per_batch"], "optional": ["image", "optional_latent"]}, "output": ["IMAGE", "LATENT"], "output_is_list": [false, false], "output_name": ["IMAGE", "LATENT"], "name": "Intrinsic_lora_sampling", "display_name": "Intrinsic Lora Sampling", "description": "\nSampler to use the intrinsic loras: \nhttps://github.com/duxiaodan/intrinsic-lora \nThese LoRAs are tiny and thus included \nwith this node pack.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes", "output_node": false}, "CheckpointPerturbWeights": {"input": {"required": {"model": ["MODEL"], "joint_blocks": ["FLOAT", {"default": 0.02, "min": 0.001, "max": 10.0, "step": 0.001}], "final_layer": ["FLOAT", {"default": 0.02, "min": 0.001, "max": 10.0, "step": 0.001}], "rest_of_the_blocks": ["FLOAT", {"default": 0.02, "min": 0.001, "max": 10.0, "step": 0.001}], "seed": ["INT", {"default": 123, "min": 0, "max": 18446744073709551615, "step": 1}]}}, "input_order": {"required": ["model", "joint_blocks", "final_layer", "rest_of_the_blocks", "seed"]}, "output": ["MODEL"], "output_is_list": [false], "output_name": ["MODEL"], "name": "CheckpointPerturbWeights", "display_name": "CheckpointPerturbWeights", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": true}, "Screencap_mss": {"input": {"required": {"x": ["INT", {"default": 0, "min": 0, "max": 4096, "step": 1}], "y": ["INT", {"default": 0, "min": 0, "max": 4096, "step": 1}], "width": ["INT", {"default": 512, "min": 0, "max": 4096, "step": 1}], "height": ["INT", {"default": 512, "min": 0, "max": 4096, "step": 1}], "num_frames": ["INT", {"default": 1, "min": 1, "max": 255, "step": 1}], "delay": ["FLOAT", {"default": 0.1, "min": 0.0, "max": 10.0, "step": 0.01}]}}, "input_order": {"required": ["x", "y", "width", "height", "num_frames", "delay"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["image"], "name": "Screencap_mss", "display_name": "Screencap mss", "description": "\nCaptures an area specified by screen coordinates. \nCan be used for realtime diffusion with autoqueue.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": false}, "WebcamCaptureCV2": {"input": {"required": {"x": ["INT", {"default": 0, "min": 0, "max": 4096, "step": 1}], "y": ["INT", {"default": 0, "min": 0, "max": 4096, "step": 1}], "width": ["INT", {"default": 512, "min": 0, "max": 4096, "step": 1}], "height": ["INT", {"default": 512, "min": 0, "max": 4096, "step": 1}], "cam_index": ["INT", {"default": 0, "min": 0, "max": 255, "step": 1}], "release": ["BOOLEAN", {"default": false}]}}, "input_order": {"required": ["x", "y", "width", "height", "cam_index", "release"]}, "output": ["IMAGE"], "output_is_list": [false], "output_name": ["image"], "name": "WebcamCaptureCV2", "display_name": "Webcam Capture CV2", "description": "\nCaptures a frame from a webcam using CV2. \nCan be used for realtime diffusion with autoqueue.\n", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": false}, "DifferentialDiffusionAdvanced": {"input": {"required": {"model": ["MODEL"], "samples": ["LATENT"], "mask": ["MASK"], "multiplier": ["FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.001}]}}, "input_order": {"required": ["model", "samples", "mask", "multiplier"]}, "output": ["MODEL", "LATENT"], "output_is_list": [false, false], "output_name": ["MODEL", "LATENT"], "name": "DifferentialDiffusionAdvanced", "display_name": "Differential Diffusion Advanced", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "_for_testing", "output_node": false}, "FluxBlockLoraLoader": {"input": {"required": {"model": ["MODEL", {"tooltip": "The diffusion model the LoRA will be applied to."}], "strength_model": ["FLOAT", {"default": 1.0, "min": -100.0, "max": 100.0, "step": 0.01, "tooltip": "How strongly to modify the diffusion model. This value can be negative."}]}, "optional": {"lora_name": [[], {"tooltip": "The name of the LoRA."}], "opt_lora_path": ["STRING", {"forceInput": true, "tooltip": "Absolute path of the LoRA."}], "blocks": ["SELECTEDBLOCKS"]}}, "input_order": {"required": ["model", "strength_model"], "optional": ["lora_name", "opt_lora_path", "blocks"]}, "output": ["MODEL", "STRING"], "output_is_list": [false, false], "output_name": ["model", "rank"], "name": "FluxBlockLoraLoader", "display_name": "Flux Block Lora Loader", "description": "", "python_module": "custom_nodes.ComfyUI-KJNodes", "category": "KJNodes/experimental", "output_node": false, "output_tooltips": ["The modified diffusion model.", "possible rank of the LoRA."]}, "FluxBlockLoraSelect": {"input": {"required": {"double_blocks.0.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.1.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.2.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.3.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.4.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.5.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.6.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.7.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.8.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.9.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.10.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.11.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.12.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.13.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.14.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.15.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.16.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.17.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "double_blocks.18.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.0.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.1.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.2.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.3.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.4.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.5.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.6.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.7.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.8.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.9.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.10.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.11.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.12.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.13.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.14.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.15.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.16.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.17.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.18.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.19.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.20.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.21.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.22.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.23.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.24.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.25.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.26.": ["FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.01}], "single_blocks.27.": ["FLOAT", {"default": 0.0, "min": 0.0, 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1}]}}, "input_order": {"required": ["python_expression", "print_to_console"], "optional": ["a", "b", "c"]}, "output": ["INT", "FLOAT", "STRING"], "output_is_list": [false, false, false], "output_name": ["INT", "FLOAT", "STRING"], "name": "Evaluate Floats", "display_name": "Evaluate Floats", "description": "", "python_module": "custom_nodes.efficiency-nodes-comfyui", "category": "Efficiency Nodes/Simple Eval", "output_node": true}, "Evaluate Strings": {"input": {"required": {"python_expression": ["STRING", {"default": "a + b + c", "multiline": false}], "print_to_console": [["False", "True"]]}, "optional": {"a": ["STRING", {"default": "Hello", "multiline": false}], "b": ["STRING", {"default": " World", "multiline": false}], "c": ["STRING", {"default": "!", "multiline": false}]}}, "input_order": {"required": ["python_expression", "print_to_console"], "optional": ["a", "b", "c"]}, "output": ["STRING"], "output_is_list": [false], "output_name": ["STRING"], "name": "Evaluate Strings", "display_name": "Evaluate Strings", "description": "", "python_module": "custom_nodes.efficiency-nodes-comfyui", "category": "Efficiency Nodes/Simple Eval", "output_node": true}, "Simple Eval Examples": {"input": {"required": {"models_text": ["STRING", {"default": "The Evaluate Integers, Floats, and Strings nodes \nnow employ the SimpleEval library, enabling secure \ncreation and execution of custom Python expressions.\n\n(https://github.com/danthedeckie/simpleeval)\n\nBelow is a short list of what is possible.\n______________________________________________\n\n\"EVALUATE INTEGERS/FLOATS\" NODE EXPRESSION EXAMPLES:\n\nAddition: a + b + c\nSubtraction: a - b - c\nMultiplication: a * b * c\nDivision: a / b / c\nModulo: a % b % c\nExponentiation: a ** b ** c\nFloor Division: a // b // c\nAbsolute Value: abs(a) + abs(b) + abs(c)\nMaximum: max(a, b, c)\nMinimum: min(a, b, c)\nSum of Squares: a**2 + b**2 + c**2\nBitwise And: a & b & c\nBitwise Or: a | b | c\nBitwise Xor: a ^ b ^ c\nLeft 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Alphanumeric: a.isalnum() + b.isalnum() + c.isalnum()\nCheck Start: a.startswith('prefix') + b.startswith('prefix') + c.startswith('prefix')\nCheck End: a.endswith('suffix') + b.endswith('suffix') + c.endswith('suffix')\nSplit: a.split(' ') + b.split(' ') + c.split(' ')\nZero Fill: a.zfill(5) + b.zfill(5) + c.zfill(5)\nSlice: a[:5] + b[:5] + c[:5]\nReverse: a[::-1] + b[::-1] + c[::-1]\n______________________________________________", "multiline": true}]}}, "input_order": {"required": ["models_text"]}, "output": [], "output_is_list": [], "output_name": [], "name": "Simple Eval Examples", "display_name": "Simple Eval Examples", "description": "", "python_module": "custom_nodes.efficiency-nodes-comfyui", "category": "Efficiency Nodes/Simple Eval", "output_node": false}}

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