nodes/da2el-ai-D2-nodes-ComfyUI
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Node

🍅 Sampler Nodes

D2 KSampler / D2 KSampler(Advanced)

Differences from standard KSampler

  • Directly outputs images (VAE Decoder not required)
  • Can input prompts in STRING format
  • Supports A1111-style LoRA loading prompts
    • Example: <lora:foo.safetensors:1>
    • For format, refer to D2 Load Lora
    • Note: When inputting positive_cond / negative_cond to D2 KSampler Advanced, LoRA will not be applied to CLIP. It will only be applied to MODEL.
  • Has dedicated Controlnet input for simple application
  • Supports d2_pipe which consolidates generation parameters
    • Can easily receive from D2 XY Plot, D2 XY Plot Easy, D2 XY Plot Easy Mini
    • Can easily pass parameters to D2 Send Eagle
  • Can change prompt weight algorithm (weight_interpretation)

Notes

  • When d2_pipe is connected, d2_pipe parameters take priority
  • For example, if you specify steps:20 in D2 KSampler and steps:15 in D2 XYPlot Easy, with d2_pipe connected, steps:15 from D2 XYPlot Easy will be used.

Input

  • Same as standard KSampler
    • model / clip / latent_image / seed / steps / cfg / sampler_name / scheduler / denoise
  • Added in D2 KSampler
    • vae
    • cnet_stack: For connecting to D2 Controlnet Loader
    • d2_pipe: Consolidated generation parameters. Received from nodes like D2 XY Plot
    • preview_method: Preview display method during generation
    • positive / negative: Prompts in STRING format
  • Added in D2 KSampler Advanced
    • token_normalization / weight_interpretation

Output

  • Same as standard KSampler
    • LATENT
  • Added in D2 KSampler
    • IMAGE: Generated image
    • MODEL / CLIP: With LoRA applied
    • positive / negative: Input passthrough
    • formatted_positive: Positive prompt with A1111-style LoRA format removed
    • positive_cond / negative_cond: CONDITIONING with Controlnet applied
    • d2_pipe: Consolidated generation parameters

D2 Pipe

  • A node for modifying and extracting the contents of d2_pipe
  • d2_pipe is used to pass parameters collectively in nodes such as D2 XY Plot Easy, D2 KSampler, and D2 Send Eagle

🍅 Loader Node

D2 Checkpoint Loader

  • A Checkpoint Loader that outputs the full path of model files
  • Can automatically apply v_prediction settings when the filename contains "vpred"

Input

  • ckpt_name
    • Checkpoint name
  • auto_vpred
    • true: Automatically applies v_prediction settings if the filename contains "vpred"
  • sampling / zsnr
    • Same settings as ModelSamplingDiscrete (details unknown)
  • multiplier
    • Same settings as RescaleCFG (details unknown)

Output

  • model / clip / vae
    • Same as the conventional CheckpointLoader.
  • ckpt_name / ckpt_hash / ckpt_fullpath
    • Checkpoint name, hash, and full path.

D2 Controlnet Loader

  • Controlnet Loader that creates simple workflows when connected to D2 KSampler

Input

  • cnet_stack
    • For connecting to D2 Controlnet Loader

Output

  • cnet_stack
    • For connecting to D2 KSampler or D2 Controlnet Loader

D2 Load Lora

  • A Lora loader that allows specifying Lora through text
  • model_weight / clip_weight can also be specified
  • There are two modes: one that uses the same format as StableDiffusion webui A1111 (a1111), and one that simply lists LoRA names (simple)
  • For specific usage, refer to the sample workflow

Input

  • mode
    • a1111: Mode that allows using the same format as StableDiffusion webui A1111
    • simple: Simple mode that just lists LoRA names. In this mode, the STRING output is not used

Output

  • MODEL / CLIP: MODEL and CLIP with LoRA applied
  • prompt: Outputs the input text as is
  • formatted_prompt: Text with LoRA specification parts removed

Format differences based on mode

mode: a1111 Expressed as <lora:~>.

<lora:lora_name:1>

mode: simple No decorations needed before or after

lora_name:1

How to specify Weight

Write in the format {lora_name}:{model_weight}:{clip_weight}.

foo:0.8:1

If clip_weight is not specified, the same value as model_weight is applied. The following have the same meaning.

foo:0.8
foo:0.8:0.8

If weight is not specified, "1" is applied The following have the same meaning.

foo
foo:1:1

How to specify multiple LoRAs in simple mode

Separate with line breaks

foo:0.5
bar

When writing two types in one line, separate with ","

foo:0.5,bar

Comments

Lines that start with "//" or "#" are ignored.

//foo:0.5
#bar

🍅 Size Node

D2 Get Image Size

  • Both outputs and displays size

D2 Size Selector

  • Node for selecting image size from presets
  • Can also get size from images
  • Rounding method can be selected from Ceil / Float / None

Input

  • images
    • Used when getting size from images
    • preset must be set to custom
  • preset
    • Size presets
    • Must be set to custom when using width height below or image sizes
    • Edit /custom_nodes/D2-nodes-ComfyUI/config/sizeselector_config.yaml to modify presets
  • width / height
    • Width/height dimensions
    • preset must be set to custom
  • swap_dimensions
    • Swap width/height
  • upscale_factor
    • Value passed to other resize nodes. Does nothing in this node
  • prescale_factor
    • Output width/height after resizing by this factor
  • round_method
    • Round: Round to nearest
    • Floor: Round down
    • None: No rounding
  • batch_size
    • Batch size to set for empty_latent

Output

  • width / height
    • Input width, height multiplied by prescale_factor
  • upscale_factor / prescale_factor
    • Passthrough of input
  • batch_size
    • Passthrough of input
  • empty_latent
    • Outputs latent created with specified size and batch size

D2 Image Resize

  • Image and mask resizing and rotation
  • Precision up to 3 decimal places for scaling
  • Can select rounding, floor, or ceiling for decimal handling
  • Capable of upscaling using upscale models
  • Latent output is also possible (requires VAE)
  • Rotation options: 90 / 180 / 270 degrees

D2 Resize Calculator

  • Can select rounding, floor, or ceiling

🍅 Refiner Node

D2 Refiner Steps

  • Node for outputting steps for Refiner

Input

  • steps
    • Total step count
  • start
    • Starting steps for first KSampler
  • end
    • Ending steps for first KSampler

Output

  • steps / start / end
    • Input passthrough
  • refiner_start
    • Starting steps for second KSampler

D2 Refiner Steps A1111

  • Node that can specify denoise for Refiner in img2img

Input

  • steps
    • Total step count
  • denoise
    • Specify denoise for img2img
  • switch_at
    • What percentage of total steps to switch to next KSampler

Output

  • steps
    • Input passthrough
  • start
    • Starting steps for first KSampler
  • end
    • Ending steps for first KSampler
  • refiner_start
    • Starting steps for second KSampler

D2 Refiner Steps Tester

  • Node for checking steps

🍅 Merge Node

D2 Model and CLIP Merge SDXL

  • A node that combines ModelMergeSDXL and CLIPMergeSimple
  • Allows comma-separated weight specifications for easier use with XYPlot
  • In this figure, 0.85,0.85,1,1,0.4,0.4,1,0.4,0.4,0.4,1,0.4,0.4,0.4,0,0.55,0.85,0.85,0.85,0.85,0.85,0.85,1,1,0.65 is specified
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