Image Node

An Image Node is a block within a workflow — a chain of tasks connected in sequence — whose only job is to generate images. It's like a conveyor belt lined with workstations, where one station does nothing but painting. You feed this block a source image and an instruction, and the image-generation model wired into it produces a new image according to that instruction, then passes it on to the next block.

The value of an Image Node becomes clear when you need to repeat the same task many times. Say you need to translate a single thumbnail into several languages: instead of opening a design tool and redoing the work each time, you can duplicate the Image Node and just swap out the language. Keep the instruction inside the node the same, or tweak it slightly, and you can quickly produce multiple outputs that share the same structure.

An Image Node is rarely used on its own. To build a complete automation, it usually needs to be paired with a verification block that checks whether the output came out correctly, and an input block that feeds in variables like language or conditions.

The article explains that "after uploading the source thumbnail image once, it's connected to an Image Node that runs OpenAI's image-generation model GPT Image 2 at a 16:9 aspect ratio and 4K resolution." The easy point of confusion here is that an Image Node isn't the image file itself — it refers to the task unit placed in the workflow to run the image-generation model.

If you want to build an Image Node yourself in a workflow tool, try the following steps:

1. Create a starting block that uploads the source image.
2. Add an Image Node that connects to an image-generation model, and set your desired aspect ratio and resolution.
3. Give the Image Node an instruction like: "Translate only the headline text into (your chosen language), and keep the rest of the layout, logo, and design identical to the original."
4. Duplicate this node and swap out just the language value to generate multiple versions at once.
5. Attach a verification node afterward that reads the resulting image back and checks whether the translation is correct.