Image Analyzer

The r/comfyui thread "N8N to ComfyUI seems like a nightmare" (103 upvotes, 2025) sums up the state of the art: getting n8n and ComfyUI to talk over raw HTTP is where automation dreams go to die. Image Analyzer is StudioDeep's attempt to make one specific version of that conversation painless - shove an image out to your n8n workflow, and read the structured JSON that comes back.

The idea: your n8n workflow already has the vision model, the database, the business logic - whatever turns a picture into data. This node is the outbound side. It takes an IMAGE and an N8N Backend, converts the image's first frame to a PNG data URL, POSTs it to your webhook as {"image_url": "data:image/png;base64,..."}, and returns whatever JSON your workflow answers with.

How it works

The key design choice is how tolerant it is on the way back. It tries the response as JSON, then digs through output, data, or json_output keys in that order before falling back to the raw body; if the value it finds is a dict or list, it reformats it with indentation; if it's a JSON string, it re-parses and pretty-prints it. So your n8n workflow can return almost anything and you'll still get a readable json_output - the node's single output, a STRING.

That leniency is both the strength and the warning. Strong side: you don't need a strict contract to see something. Weak side: "anything goes" means the shape is on you, and the node won't tell you when the workflow returned something meaningless.

Inputs

• n8n_backend - an AI_BACKEND from N8N Backend (the webhook + optional basic auth). It needs a webhook, so don't wire an LLM Backend here - same KeyError trap as Image Prompt by Seed Idea.
• image - any IMAGE; only image[0] is sent.

Output: json_output (STRING).

Installing

ComfyUI Manager → "StudioDeep", or:

cd ComfyUI/custom_nodes
git clone https://github.com/studiodeep-ai/comfyui-studiodeep StudioDeep
pip install -r StudioDeep/requirements.txt

Restart. No local models - the vision brain lives in your n8n workflow (or whatever service it calls), so the only real setup is the webhook.

Troubleshooting

• Non-JSON or empty output - your webhook returned text that isn't JSON. The node will hand you the raw text, which at least tells you it got a response. Fix the workflow, not the node.
• KeyError: 'webhook_url' - wrong backend type again. Use the N8N Backend, not LLM Backend.
• Timeouts - 120 seconds is generous but not infinite. If your n8n chain runs a big vision model on a huge image, consider downscaling before it leaves ComfyUI.
• Auth issues - credentials only go out if a username is set on the backend. No username, no auth header, and a 401 from n8n is the usual symptom.

Worth knowing: this node pairs cleanly with the Describer prompt kit - your workflow can use the same disciplined "describe only the camera angle" prompts to turn frames into structured data you can sort, filter, and feed back into a queue. That's the actual point of the N8N path: the analysis isn't trapped inside ComfyUI.