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

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 request_id.
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 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.
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.

Set up steps

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

1. Obtain an API Key:

   • Create an account at fal.ai
   • Navigate to your account settings to generate an API key.

2. 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".

Need help customizing?

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