Downscale a SeedVR (or other upscaler) result back to your target training size — the upscaler adds fine detail, Smart Resize brings it to the right dimensions for LoRA training
Any workflow step that needs a clean resize before the next node
Normalize mixed-resolution batches to a consistent size

Input	Type	Default	Description
image	IMAGE	—	Single image or batch
max_pixels	INT	1536	Target size for longest side
multiple_of	INT	8	Snap dimensions to this multiple (8 = SD/Flux compatible)
interpolation	ENUM	lanczos	lanczos / bicubic / bilinear / nearest
upscale_if_smaller	BOOLEAN	false	Also upscale images already smaller than max_pixels

Outputs: image, width, height

📁 Smart Batch Resize

Load all images from a folder, resize each one by longest side, and save with the original filename + a suffix into a subfolder. Original filenames are always preserved.

Use this for bulk preprocessing — e.g. preparing a LoRA dataset from a folder of high-res images.

Input	Type	Default	Description
input_folder	STRING	D:/images/input	Source folder path
max_pixels	INT	1536	Target size for longest side
filename_suffix	STRING	_Small	Appended to each output filename before the extension
output_subfolder	STRING	resized	Subfolder created inside input_folder
multiple_of	INT	8	Snap dimensions to this multiple
interpolation	ENUM	lanczos	lanczos / bicubic / bilinear / nearest
skip_if_exists	BOOLEAN	false	Skip files that already exist in output

Outputs: images (list), filenames (list), output_paths (list), count

📏 Smart Size Multiplier

Multiply image dimensions by a factor and output the results as integers.

SeedVR takes a single resolution INT (the longest side) — not a width and height separately. Standard math nodes give you a FLOAT or require multiple steps to get there. This node does it cleanly in one step: give it your image and a multiplier, and it outputs width, height, and resolution (longest side) ready to connect directly to SeedVR's max_resolution input.

Also useful for LoRA dataset prep — using mixed resolutions in your training set generally produces better results than training on a single fixed size. Smart Size Multiplier makes it easy to dynamically calculate the right target size per image rather than hardcoding a value.

Input	Type	Default	Description
image	IMAGE	—	Source image
multiplier	FLOAT	2.0	Multiply width and height by this factor
multiple_of	INT	8	Snap dimensions to this multiple

Outputs: width, height, resolution (longest side as INT → directly into SeedVR)

Why these nodes?

ComfyUI's built-in Resize Images by Longer Edge [BETA] has no Lanczos and no multiple_of snapping
JWImageResizeByLongerSide (comfyui-various) has no Lanczos in the official release
No existing node combines batch folder loading + longest-side resize + original filename preservation
No existing node outputs a ready-to-use resolution INT for SeedVR

Installation

ComfyUI Manager: search for ComfyUI-SmartResize and install.

Manual:

cd ComfyUI/custom_nodes
git clone https://github.com/CraftopiaStudio/ComfyUI-SmartResize

Restart ComfyUI. All nodes appear under Craftopia in the node menu:

Craftopia → Smart Resize 📐
Craftopia → Smart Batch Resize 📁
Craftopia → Smart Size Multiplier 📏

Requirements

Pillow, NumPy, PyTorch — all included with ComfyUI. No extra dependencies.