I’m looking for suggestions on AI tools or integrations that can process images and return structured data in n8n. Specifically, I want a tool that can take an image, perform OCR to extract text, detect and segment objects, understand layout/structure, measure elements (like dimensions or distances), and output the results as structured data (JSON, CSV, etc.) that I can use in workflows. Ideally something that’s accurate and works well within n8n — either via API, node, or custom integration.
I have tried just the basic Open AI Visions but it is not quite accurate enough for measuring.
Any recommendations or examples of how you’ve done something similar would be greatly appreciated!
I feel the image to be processed is complex. However, if I were to take on the challenge, I would consider the following structure:
First, I would try to convert the image to text using Gemini Node’s Analyze Document. At this time, I would attempt to improve OCR analysis accuracy by outputting in Markdown or HTML format. This would be more effective if the image being processed has a format.
Next, I would extract the desired information from step 1 using Information Extractor. This is also worth trying with a Basic LLM Chain.
Options to check OCR accuracy:
It would be good to try third-party OCR services as well.
You might find AIs and OCRs specifically specialized for accuracy.
If accuracy is the biggest challenge, I might have Gemini, OpenAI, and other third-party services analyze it separately, then have another AI evaluate them and select the best one, or select information that seems highly probable based on that data.
In my experience, the prompt in step 1 is the most crucial. I hope this is helpful.
1. OCR + structure extraction - Pretty straightforward. Most document APIs handle this well. Send image, get back text with layout preserved as JSON.
2. Object detection + segmentation - Different beast. You need computer vision models. Google Vision API or Azure Computer Vision do this. They’ll give you bounding boxes, labels, confidence scores.
3. Measuring dimensions - This is the hard part. You need reference points or known scale. Most vision APIs won’t do this accurately without calibration.
OpenAI Vision struggles with precision measurements because it’s designed for understanding, not measuring.
What I’d do:
If you mostly need text + structure: use a document extraction API via HTTP Request.
If you need object detection: Google Vision or Azure via HTTP Request.
For measurements: honestly might need custom Python code with OpenCV. Depends on your images - do you have a scale reference?
What kind of images are you working with? Construction plans? Product photos? That’ll determine which approach works.