Use this as a pipeline node — IMAGE in, IMAGE out. Perfect for downscaling SeedVR upscales before LoRA training, or any workflow step where you need a clean downscale without saving to disk.

Inputs:

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

📁 Batch Resize & Save

Load all images from a folder, resize each one (longest side), and save them with the original filename + a suffix into a subfolder.

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

Inputs:

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

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

Why these nodes?

Existing nodes like JWImageResizeByLongerSide lack Lanczos interpolation (the best choice for downscaling). Other batch nodes don't preserve original filenames or offer multiple_of snapping.

These nodes fill that gap with a minimal, focused feature set.

Installation

Option A — ComfyUI Manager: Search for ComfyUI-SmartResize and install.

Option B — Manual:

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

Restart ComfyUI. Nodes appear under:

image/transform → Smart Resize 📐
image/batch → Batch Resize & Save 📁

Requirements

ComfyUI
Pillow (included with ComfyUI)
PyTorch (included with ComfyUI)