AI-Powered Body Measurement & Clothing Size Estimator from Image with Fal.ai

This workflow automates the process of estimating a person’s fashion size from an uploaded image using an AI model.

This workflow is an automated pipeline that uses an AI model to estimate a person's body measurements and clothing size from an image URL.

Key Features

🔁 Full Automation** – From image submission to result display, the process requires no manual steps. ⚙️ Easy Integration** – Uses n8n’s native nodes and simple HTTP requests to connect with Fal.ai’s API. 🕒 Real-Time Processing** – Automatically waits and checks for the AI result, ensuring the user receives the output as soon as it’s ready. 🧩 Modular Design** – Each step (submit → process → check → result) is clearly separated, making it easy to modify or extend (e.g., adding notifications or storing results in a database). 💡 User-Friendly Interface** – The initial form and final result form make it accessible even for non-technical users. 🔐 Secure** – Authentication to the Fal.ai API is handled through HTTP header authorization, keeping API keys protected.

How it works

Form Trigger: The workflow starts with a public form where a user submits a URL of an image. AI Processing Request: The submitted image URL is sent to the fal.run AI service (specifically, the "fashion-size-estimator" model) via a POST request. This initial request places the job in a queue and returns a unique request_id. Polling for Completion: The AI processing is asynchronous and takes some time. The workflow enters a loop where it: Waits: Pauses for 10 seconds to give the AI model time to process the request. Checks Status: Uses the request_id to check the status of the job. Conditional Check: An IF node checks if the status is "COMPLETED". If NO (not completed), the loop repeats (wait, then check again). If YES, the workflow exits the loop. Fetching and Displaying Results: Once processing is complete, the workflow retrieves the final result (containing the size, height, bust, waist, and hip measurements) and automatically displays it to the user on a "thank you" page. Set up steps

To make this workflow operational, you need to configure the API authentication.

Obtain an API Key: Create an account at fal.ai Navigate to your account settings to generate an API key.

Configure Credentials in n8n: In your n8n instance, create a new HTTP Header Auth credential (you can name it "Fal.run API"). Set the Name field to Authorization. Set the Value field to Key YOURAPIKEY, replacing "YOURAPIKEY" with the actual key you obtained from fal.ai. Ensure this credential is correctly selected in the three HTTP Request nodes: "Send image to estimator", "Get status", and "Get result".

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