Recommended Alternatives

This node pack was created as a dependency-free library before the ComfyUI Manager made installing dependencies easy for end-users.

Unless you specifically need a library without dependencies, I recommend using Impact Pack instead. It's a more feature-rich and well-maintained alternative for dealing with masks and segmentation.

Masquerade Nodes

This is a node pack for ComfyUI, primarily dealing with masks. Some example workflows this pack enables are:

(Note that all examples use the default 1.5 and 1.5-inpainting models. Results are generally better with fine-tuned models.)

1. Fine control over composition via automatic photobashing (see examples/composition-by-photobashing.json)
2. Inpaint all faces at a higher resolution (see examples/inpaint-faces.json)
3. Inpaint all buildings with a particular LORA (see examples/inpaint-with-lora.json)
4. Filtering out images/change save location of images that contain certain objects/concepts without the side-effects caused by placing those concepts in a negative prompt (see examples/filter-by-season.json)

The lynchpin of these workflows is the Mask by Text node. This node makes use of ClipSeg to dynamically create masks from images via text prompts.

Node Descriptions

Mask By Text

Inputs

• image - The image to use to calculate the mask for.
• prompt - One or more prompts to select, separated by the | symbol.
• negative_prompt - Zero or more prompts to select, separated by the | symbol.
• precision - How sure to be about the mask created.
• normalize - Whether results should be normalized across the image.
  • Note - This can be useful if you know for certain that your prompt exists in the image, but the model inconsistently recognizes it. I would generally recommend trying with normalize turned off first.

Outputs

1. Thresholded Mask - The calculated mask after taking precision and normalization into account.
2. Raw ClipSeg Results - The raw results from ClipSeg. Values are between 0.0 and 1.0.

Tips

• Using multiple prompts/negative prompts within one node is an ease-of-use and runtime optimization feature. The same result can be achieved with multiple Mask by Text nodes by using Combine Masks -> Union and Combine Masks -> Difference.
• You can use the raw ClipSeg results for more complex operations (like comparing the relative likelihood of two concepts).

Mask Morphology

Inputs

• image - The mask to perform the operation on.
• distance - The distance across which to perform the operation.
• op - The operation to perform.
  • dilate - Expand the size of the mask.
  • erode - Contract the size of the mask.
  • open - Erode and then dilate. Useful to remove white specs in the mask.
  • close - Dilate and then erode. Useful to remove black specs in the mask.

Outputs

1. The resultant mask.

Tips

• Open is useful to remove white specs in a mask. You should generally use it before a Separate Mask Components node.
• Close is useful to remove black specs in a mask.

Combine Masks

Inputs

• image1 - The first mask to use.
• image2 - The second mask to use.
• op - The operation to perform.
  • union (max) - The maximum value between the two masks.
  • intersection (min) - The minimum, value between the two masks.
  • difference - The pixels that are white in the first mask but black in the second.
  • multiply - The result of multiplying the two masks together. Same as intersection for any thresholded masks.
  • multiply_alpha - An alpha channel is added to the first image if required and then the second image (treated as a mask) is multiplied on top.
  • add - The result of adding the two masks together. Same as union for any thresholded masks (if clamped).
  • greater_or_equal - image1 >= image1.
  • greater - image1 > image1. Same as difference for any thresholded masks.
• clamp_result - Whether results should be clamped between 0 and 1. Usually you want this.
• round_result - Whether results should be rounded to 0 or 1.

Outputs

1. The resultant mask or image.

Tips

• This node can also be used with RGB/RGBA images. This can be useful to alpha out part of an image based on a mask (via multiplication).

Unary Mask Op

Inputs

• image - The mask to operate on.
• op - The operation to perform.
  • invert - Inverts the mask.
  • average - Sets the value of all pixels in the mask to be equal to the value of the average pixel.
  • round - Rounds all pixels to the nearest integer (generally 0 or 1).
  • clamp - Clamps all values between 0 and 1.
  • abs - Takes the absolute value of all pixels.

Outputs

1. The resultant mask.

Tips

• Average is deceptively useful. For example, you can use two Mask to Text nodes with different concepts (like 'New York' and 'Chicago') and average the raw ClipSeg result to see which city the image is more likely to depict.

Unary Image Op

This node is the same as Unary Mask Op, but will operate across all channels of an image individually. This can be particularly useful after converting to HSV colorspace.

Inputs

• image - The image to operate on.
• op - The operation to perform.
  • invert - Inverts all channels of the image.
  • average - Sets the value of all pixels in the image to be equal to the value of the average pixel in that channel.
  • round - Rounds all pixels to the nearest integer (generally 0 or 1).
  • clamp - Clamps all values between 0 and 1.
  • abs - Takes the absolute value of all pixels.

Outputs

1. The resultant image.

Blur

Inputs

• image - The image to blur.
• radius - How much to blur the image.
• sigma_factor - Control the falloff speed of the blur.

Outputs

1. The resultant mask or image.

Tips

• This node can be used on both masks and images.
• You can usually leave the sigma factor at 1.

Image To Mask

Inputs

• image - The image to convert.
• method - The method to use for conversion.
  • intensity - Uses the grayscale color of the image.
  • alpha - Uses the alpha mask of the image.

Outputs

1. The resultant mask in a form usable by inpainting.

Mix Images By Mask

Inputs

• image1 - The first image.
• image2 - The second image.
• mask - The mask to use to interpolate between the two images.

Outputs

1. The resultant image.

Mix Color By Mask

Inputs

• image - The first image.
• r, g, b - The red, green and blue components to use for the color.
• mask - The mask to use to interpolate between the image and the color.

Outputs

1. The resultant image.

Mask To Region

Inputs

• mask - The mask to use to calculate the region for.
• padding - How much padding to add around the mask.
• constraints - Once we determine a minimum size, the mask will be grown until it meets the specified constraint.
  • keep_ratio - The region's ratio will be the same as the ratio between constraint_x and constraint_y.
  • keep_ratio_divisible - The region's ratio will be the same as the ratio between constraint_x and constraint_y. Additionally, the region's width will divide evenly into constraint_x and the region's height will divide evenly into constraint_y.
  • multiple_of - The region's width will be a multiple of constraint_x and the region's height will be a multiple of constraint_y.
  • ignore - No special constraints (constraint_x and constraint_y are meaningless).
• constraint_x - See constraints.
• constraint_y - See constraints.
• min_width - The minimum width of the region.
• min_height - The minimum height of the region.
• batch_behavior - How to handle batches of multiple images/masks.
  • match_ratio - The region will have the same ratio for all masks. Additionally, all masks will be scaled to the size of the largest mask with bicubic filtering applied.
  • match_size - All regions will grow to the size of the largest mask.

Outputs

1. A mask of the resultant region.

Tips

• This node is particularly useful for an inpainting at full resolution. You can use it to select a reasonable area around the masked area you want to inpaint.

Cut By Mask

Inputs

• image - The image or mask to cut the masked area out of.
• mask - The mask specifying the area to cut.
• force_resize_width - If non-zero, the image will be resized to this width.
• force_resize_height - If non-zero, the image will be resized to this height.
• mask_mapping_optional - If there are a variable number of masks for each image (due to use of Separate Mask Components), use the mask mapping output of that node to cut the masks out of the correct image. Leave this unused otherwise.

Outputs

1. The resultant image or mask.

Notes

• If there are multiple masks/images and force_resize_width and force_resize_height are zero, all images will be resized to the size of the largest.
• If the mask is not rectangular, alpha will be applied to areas outside of the mask. If you paste the image back with Paste By Mask, areas with 0 alpha will not be pasted.

Tips

• You will frequently want to use Mask To Region to generate the mask to cut out. You can then cut out both the image and the original mask to get your inpainting target.
• If you are using a batc