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MaskDetailer (pipe)

ImpactPack/Detailer
MaskDetailerPipe

Example

JSON Example
{
  "class_type": "MaskDetailerPipe",
  "inputs": {
    "image": [
      "node_id",
      0
    ],
    "mask": [
      "node_id",
      0
    ],
    "basic_pipe": [
      "node_id",
      0
    ],
    "guide_size": 512,
    "guide_size_for": true,
    "max_size": 1024,
    "mask_mode": true,
    "seed": 0,
    "steps": 20,
    "cfg": 8,
    "sampler_name": "euler",
    "scheduler": "simple",
    "denoise": 0.5,
    "feather": 5,
    "crop_factor": 3,
    "drop_size": 10,
    "refiner_ratio": 0.2,
    "batch_size": 1,
    "cycle": 1
  }
}

This example shows required inputs only. Connection values like ["node_id", 0] should reference actual node IDs from your workflow.

Inputs

NameTypeStatusConstraintsDefault
imageIMAGErequired--
maskMASKrequired--
basic_pipeBASIC_PIPErequired--
guide_sizeFLOATrequiredmin: 64, max: 16384, step: 8512
guide_size_forBOOLEANrequired-true
max_sizeFLOATrequiredmin: 64, max: 16384, step: 81024
mask_modeBOOLEANrequired-true
seedINTrequiredmin: 0, max: 1.84e+190
stepsINTrequiredmin: 1, max: 1000020
cfgFLOATrequiredmin: 0, max: 1008
sampler_nameENUM
44 options
  • euler
  • euler_cfg_pp
  • euler_ancestral
  • euler_ancestral_cfg_pp
  • heun
  • heunpp2
  • exp_heun_2_x0
  • exp_heun_2_x0_sde
  • 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_cfg_pp
  • dpmpp_2m_sde
  • dpmpp_2m_sde_gpu
  • dpmpp_2m_sde_heun
  • dpmpp_2m_sde_heun_gpu
  • dpmpp_3m_sde
  • dpmpp_3m_sde_gpu
  • ddpm
  • lcm
  • ipndm
  • ipndm_v
  • deis
  • res_multistep
  • res_multistep_cfg_pp
  • res_multistep_ancestral
  • res_multistep_ancestral_cfg_pp
  • gradient_estimation
  • gradient_estimation_cfg_pp
  • er_sde
  • seeds_2
  • seeds_3
  • sa_solver
  • sa_solver_pece
  • ddim
  • uni_pc
  • uni_pc_bh2
required--
schedulerENUM
17 options
  • simple
  • sgm_uniform
  • karras
  • exponential
  • ddim_uniform
  • beta
  • normal
  • linear_quadratic
  • kl_optimal
  • AYS SDXL
  • AYS SD1
  • AYS SVD
  • GITS[coeff=1.2]
  • LTXV[default]
  • OSS FLUX
  • OSS Wan
  • OSS Chroma
required--
denoiseFLOATrequiredmin: 0.0001, max: 1, step: 0.010.5
featherINTrequiredmin: 0, max: 100, step: 15
crop_factorFLOATrequiredmin: 1, max: 10, step: 0.13
drop_sizeINTrequiredmin: 1, max: 16384, step: 110
refiner_ratioFLOATrequiredmin: 0, max: 10.2
batch_sizeINTrequiredmin: 1, max: 1001
cycleINTrequiredmin: 1, max: 10, step: 11
refiner_basic_pipe_optBASIC_PIPEoptional--
detailer_hookDETAILER_HOOKoptional--
inpaint_modelBOOLEANoptional-false
noise_mask_featherINToptionalmin: 0, max: 100, step: 120
bbox_fillBOOLEANoptional-false
contour_fillBOOLEANoptional-true
scheduler_func_optSCHEDULER_FUNCoptional--

Outputs

IndexNameTypeIs ListConnection Reference
0imageIMAGENo["{node_id}", 0]
1cropped_refinedIMAGEYes["{node_id}", 1]
2cropped_enhanced_alphaIMAGEYes["{node_id}", 2]
3basic_pipeBASIC_PIPENo["{node_id}", 3]
4refiner_basic_pipe_optBASIC_PIPENo["{node_id}", 4]
How to connect to these outputs

To connect another node's input to an output from this node, use the connection reference format:

["node_id", output_index]

Where node_id is the ID of this MaskDetailerPipe node in your workflow, and output_index is the index from the table above.

Example

If this node has ID "5" in your workflow:

  • image (IMAGE): ["5", 0]
  • cropped_refined (IMAGE): ["5", 1]
  • cropped_enhanced_alpha (IMAGE): ["5", 2]
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