Automate 3D body model generation from images using SAM-3D & Google Sheets

This workflow automates the process of generating 3D human body models (in .glb format) from single image using SAM-3D model. It operates by connecting a Google Sheet as a data source with the external AI processing API.

Start	Result

---

Use Cases

1. ✅ Sports Analysis & Motion Optimization

3D models allow precise analysis of posture, angles, and technique. Possible applications:

• Golf swing analysis Identify stance, rotation, shoulder/hip alignment, and follow-through.
• Tennis serve biomechanics Optimize shoulder rotation, racket angle, leg push-off.
• Running gait analysis Evaluate stride symmetry, foot strike, and body tilt.
• Cycling posture optimization Reduce drag by analyzing torso angle and hand position.
• Swimming technique evaluations Compare ideal vs. actual joint angles.

2. ✅ Fitness, Health & Physiotherapy

3D models can visually highlight imbalances or incorrect positions.

• Posture correction assessments Identify spinal misalignment or uneven weight distribution.
• Physical therapy progress tracking Compare poses over time to assess recovery.
• Ergonomics and workplace safety Evaluate whether a worker’s posture is safe during lifting or repetitive tasks.
• Home fitness coaching Automated feedback for yoga, pilates, stretching exercises.

3. ✅ Fashion, Apparel & Virtual Try-On

Photorealistic body reconstruction helps generate tailored outfits or evaluate fit.

• Virtual try-on for clothing brands Produce accurate 3D avatars to test garments digitally.
• Custom-made fashion Use 3D measurements for bespoke tailoring patterns.
• Model pose simulation Test clothing fit in dynamic or unusual positions (e.g., dance, athletic poses).

4. ✅ Gaming, Animation & Digital Content Creation

Quick 3D reconstruction reduces production time for digital humans.

• Character rigging from real people Generate 3D avatars ready for animation.
• Motion capture alternatives Recreate specific poses without expensive mocap systems.
• VR/AR content creation Deploy 3D characters into immersive environments.
• Comics, illustration, and concept art Use 3D poses as reference models to speed up drawing.

5. ✅ Medical, Research & Educational Applications

Human-body 3D models provide insights in scientific or practical contexts.

• Anthropometric measurements Estimate height, limb length, body proportions from images.
• Posture and musculoskeletal studies Analyze joint angle distribution in different poses.
• Rehabilitation robotics or exoskeleton design Fit devices to a patient’s real body shape.
• Training materials for anatomy or movement science Generate accurate pose examples for students.

6.✅ Security, Forensics & Reconstruction

When allowed ethically and legally, 3D models can support investigations.

• Reconstruction of accident scenes Understand how a person fell, collided, or moved.
• Analysis of body posture in video frames Useful for determining gesture patterns or mobility constraints.

7. ✅ Art, Photography & Creative Industries

Artists often need unusual or complex human poses.

• Pose reference creation For painting, 3D sculpting, illustration, or storyboarding.
• Recreating dynamic action scenes Parkour, martial arts, ballet, expressive dance.
• Virtual studio lighting tests Apply simulated lighting to a 3D model before shooting.

---

How It Works

This workflow automates the process of generating 3D human body models (in .glb format) from single images using the FAL.AI SAM-3D service. It operates by connecting a Google Sheet as a data source with the external AI processing API. Here is the operational flow:

1. Trigger & Data Fetch: The workflow begins either manually (via "Test workflow") or on a schedule. It queries a designated Google Sheet to find rows where the "3D RESULT" column is empty, indicating a new image needs processing.
2. API Request & Queuing: For each new image, it sends the image URL to the FAL.AI SAM-3D API endpoint (/fal-ai/sam-3/3d-body), which queues the job and returns a unique request_id.
3. Status Polling & Waiting: The workflow enters a polling loop. It waits 60 seconds, then checks the job's status using the request_id. If the status is not "COMPLETED", it waits another 60 seconds and checks again.
4. Result Retrieval & Storage: Once the status is "COMPLETED", the workflow fetches the final result, which contains the URL of the generated 3D model file (.glb). This file is then downloaded via an HTTP request.
5. Sheet Update: Finally, the workflow updates the original Google Sheet row. It writes the URL of the generated 3D model into the "IMAGE RESULT" column for the corresponding row_number, thus marking the task as complete.

---

Set Up Steps

To configure this workflow in your n8n environment, follow these steps:

1. Prepare the Google Sheet:

   • Clone the provided Google Sheet template.
   • Insert the URLs of the model images you want to convert into the "IMAGE MODEL" column.
   • Leave the "IMAGE RESULT" column empty; it will be populated automatically.
   • In n8n, set up a "Google Sheets OAuth2 API" credential and connect it to the Get new image and Update result nodes. Ensure the documentId points to your cloned sheet.

2. Configure the FAL.AI API Connection:

   • Create an account at fal.ai and obtain your API key.
   • In n8n, create an "HTTP Header Auth" credential. Set the Header Name to Authorization and the Header Value to Key YOUR_API_KEY_HERE (replace with your actual key).
   • Apply this credential to the following nodes: Create 3D Image, Get status, and Get Url 3D image.

3. Verify Workflow Logic (Key Nodes):

   • Get new image: Confirm the filtersUI is set to look for empty rows in the correct column (e.g., "3D RESULT" or "IMAGE RESULT").
   • Create 3D Image: Verify the JSON body correctly references the image URL from the previous node ({{ $json.image }}).
   • Completed? (If node): Ensure the condition checks for the string COMPLETED from {{ $json.status }}.
   • Update result: Double-check that the column mapping correctly uses row_number to match the row and updates the "IMAGE RESULT" column with the GLB URL

4. Activate & Test:

   • Save the workflow.
   • Use the When clicking ‘Test workflow’ node for an initial manual test with one image URL in your sheet.
   • Once confirmed working, you can enable the Schedule Trigger node for automatic, periodic execution.

---

👉 Subscribe to my new YouTube channel. Here I’ll share videos and Shorts with practical tutorials and FREE templates for n8n.

---

Need help customizing?

Contact me for consulting and support or add me on Linkedin.