Wildcard Divide

ComfyUI custom node that specifies wildcard prompts for multiple regions

The above workflow is docs/example.json.

Wildcard Divide Node

This node incorporates the syntax of Impact Pack Wildcards while introducing additional syntactical features.

Weighted Child Selection

You can assign selection weights to options by prefixing them with a numerical value. This number determines the likelihood of that particular option being chosen.

hair:
  - 4, blonde
  - 5, black
  - 1, red

In this example, invoking __hair__ will result in "blonde" being selected with a probability of 4/(4+5+1) = 4/10 = 0.4. When a numerical prefix is omitted, a default weight of 1 is assumed.

This weighted selection mechanism is functionally equivalent to the following syntax in Impact Pack Wildcards:

hair:
  - {4::blonde|5::black|1::red}

Pattern-based Child Selection

Lines beginning with / are selected when the pattern matches the prompt up to that point. For example:

outfit:
  - blouse, skirt, __legs__
  - shirt, pants, __legs__
  - swimsuit, __legs__
legs:
  - /skirt/ stockings
  - /pants/ socks
  - bare feet

If __outfit__ expands to blouse, skirt (with a 1/3 probability), __legs__ will subsequently expand to stockings because the /skirt/ pattern matches. In cases where no pattern matches (e.g., when swimsuit is selected), the default option bare feet would be chosen.

Lines starting with /! are selected when the pattern does not match the prompt. For instance:

outfit:
  - blouse, skirt
  - dress
  - swimsuit
legs:
  - /!swimsuit/ stockings
  - bare feet

Here, stockings would be selected for any outfit that doesn't include swimsuit (i.e., blouse, skirt or dress).

Lines starting with +/ (or +/!) add the corresponding option to the list of candidates when the pattern matches (or doesn't match) the prompt, rather than replacing the existing options. For example:

outfit:
  - blouse, skirt
  - dress
  - swimsuit
legs:
  - +/skirt/ stockings
  - bare feet

In this scenario, if __outfit__ expands to blouse, skirt (with a 1/3 probability), the /skirt/ pattern will match. Consequently, stockings will be added to the list of candidates for __legs__, resulting in two options: stockings and bare feet. The final selection will then be made randomly from these two options, each with an equal probability.

Split region

You can use [SEP] to divide an image into different regions. Each [SEP] divides the image into n equal parts.

scene: 2girls [SEP] blonde hair [SEP] black hair

For example, if written as above, 2girls would be applied to the entire image, blonde hair to the left half of the image, and black hair to the right half.

Split Direction

You can specify the orientation of the split using the opt:horizontal and opt:vertical options.

scene:
  - opt:horizontal 2girls [SEP] blonde hair [SEP] black hair
  - opt:vertical sky [SEP] blue sky [SEP] red sky

This syntax allows for precise control over image segmentation:

1. Horizontal Split (Left to Right): If the first option is selected, the image is divided horizontally. In this case:

   • 2girls applies to the entire image
   • blonde hair is applied to the left half
   • black hair is applied to the right half

2. Vertical Split (Top to Bottom): If the second option is chosen, the image is segmented vertically:

   • sky is applied across the entire image
   • blue sky affects the top half
   • red sky influences the bottom half

Image Size Specification

You can define the dimensions of the output image using the opt:widthxheight syntax. This feature allows for dynamic image size adjustment based on the selected option.

scene:
  - opt:1216x832 2girls [SEP] blonde hair [SEP] black hair
  - opt:832x1216 sky [SEP] blue sky [SEP] red sky

In this example, selecting the second option would result in an image with dimensions of 832x1216 pixels.

To implement this functionality, ensure that you connect the width and height outputs to the empty latent image node in your workflow. This connection enables the dynamic resizing of the output based on the specified dimensions.