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.

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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.

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How it works

1. Form Trigger: The workflow starts with a public form where a user submits a URL of an image. 2. 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 requestid. 3. 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 requestid 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. 4. 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. ---