From Pixels to Perfect Fit: The AI Stack Behind Our Virtual Fitting Tech

Hey dev community!

We are incredibly excited to announce the launch of our brand new website, https://www.visboom.com/ This isn't just another website launch for us; it's the culmination of months of hard work, countless lines of code, and a whole lot of AI model training.

Our mission is simple: to solve the "will it fit?" problem in online shopping.

We've all been there. You see a perfect shirt online, you hesitate between M and L, and when it finally arrives... it's not quite right. The hassle of returns is not only annoying for you but also a huge environmental problem for the planet.

So, we asked ourselves: What if we could use technology to bridge the gap between the 2D screen and the 3D reality of our bodies? What if you could actually see how clothes look on you before you click "buy"?

That's why we built Visboom, and today, we want to give you a peek under the hood at the AI that makes our virtual fitting feature possible.

The Magic: How Our AI Works
At its core, our virtual try-on isn't magic—it's a sophisticated pipeline of machine learning models working in harmony. Here's a simplified breakdown of the process:

Step 1: Understanding You (Human Pose Estimation)
When you upload a photo of yourself, the first thing our system does is analyze your posture and body shape. We use a deep learning model for Human Pose Estimation.

• It identifies key points on your body (shoulders, elbows, waist, hips, etc.).
• It creates a skeletal representation or a "pose map."
• This allows the AI to understand your body's specific orientation and dimensions, which is crucial for a realistic fit.

Think of it like creating a personalized digital mannequin from a single 2D image.

Step 2: Understanding the Garment (Garment Warping)
Next, we need to make the flat image of a t-shirt, dress, or jacket conform to your unique pose. This is where the real challenge lies. We employ a type of Generative AI, specifically a model inspired by Generative Adversarial Networks (GANs) or Diffusion Models.

1. Garment Parsing: The AI first identifies the clothing item from its product photo, separating it from the background.
2. Texture and Shape Warping: The model then "drapes" this 2D garment onto the 3D pose map we created in Step 1. It intelligently stretches, bends, and warps the clothing's texture and shape to match your body's contours. It has to learn the physics of how different fabrics fold and hang.

Step 3: Putting It All Together (Image Synthesis & Blending)
The final step is to create the final, seamless image. The AI model takes:

• Your original photo.
• Your estimated pose.
• The warped garment.

It then synthesizes a new image where the garment is realistically placed on you. This involves handling complex details like:

• Occlusion: If your hair falls over the collar, the AI needs to render the hair on top of the shirt.
• Lighting and Shadows: It adjusts the lighting on the clothing to match the lighting in your original photo, adding subtle shadows to create a sense of depth.

The result? A photorealistic image of you wearing the new item!

Challenges We Overcame
This journey wasn't without its bumps. Some of our biggest challenges included:

• Diverse Body Types: Ensuring the model works accurately for all body shapes, sizes, and heights.
• Complex Poses: Handling non-standard poses (e.g., hands on hips, slight turning).
• Performance: These AI models are computationally expensive. We spent a lot of time optimizing our backend to deliver the try-on result in seconds, not minutes.

What's Next for Visboom?
This is just the beginning! We're already working on:

• Expanding our clothing catalog.
• Improving the realism of fabric textures and folds.
• Potentially exploring video-based try-on in the future.
• Developing an API for e-commerce stores to integrate our technology. (If you're a developer in the e-commerce space, we'd love to chat!)

We Want Your Feedback!
We built Visboom for you, and we'd be thrilled if you gave it a spin.

Check out the live site and try it for yourself: https://visboom.com

Let us know what you think! Does it work well? What features would you like to see next? Drop a comment below. We're here to learn and build with the community.

Happy coding, and happy shopping!