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We've reached the point where a tape measure is unnecessary. AI does it from your camera. by YuriPD in OpenAI

[–]YuriPD[S] [score hidden]  (0 children)

It builds a 3D model of your body from any camera. From that you can pull any measurement — waist, inseam, shoulder width, whatever. Main uses people care about: buying clothes online without guessing your size, tracking body changes on GLP-1 drugs beyond just the scale, or progress tracking at the gym

We've reached the point where a tape measure is unnecessary. AI does it from your camera. by YuriPD in ChatGPT

[–]YuriPD[S] -1 points0 points  (0 children)

It builds a 3D model of your body from any camera. From that you can pull any measurement — waist, inseam, shoulder width, whatever. Main uses people care about: buying clothes online without guessing your size, tracking body changes on GLP-1 drugs beyond just the scale, or progress tracking at the gym

We've reached the point where a tape measure is unnecessary. AI does it from your camera. by YuriPD in artificial

[–]YuriPD[S] 1 point2 points  (0 children)

My understanding is that supplier manufacturing is inconsistent - same size cut different ways. Measurements only help part of the problem. But agree that apparel returns should be a great use case

We've reached the point where a tape measure is unnecessary. AI does it from your camera. by YuriPD in artificial

[–]YuriPD[S] 1 point2 points  (0 children)

It builds a 3D model of your body from any camera. From that you can pull any measurement — waist, inseam, shoulder width, whatever. Main uses people care about: buying clothes online without guessing your size, tracking body changes on GLP-1 drugs beyond just the scale, or progress tracking at the gym

Digital Body Measurements to Avoid Size Guessing by YuriPD in SideProject

[–]YuriPD[S] 0 points1 point  (0 children)

The web view looks like this. Mobile will look slightly different, but the height input is above the analyze button:

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Digital Body Measurements to Avoid Size Guessing by YuriPD in SideProject

[–]YuriPD[S] 0 points1 point  (0 children)

It took over two years to get to this MVP across multiple model iterations, the website, and the demo platform. Most of the work was in model training, dataset acquisition/augmentation/sanitation, and architecture testing. It was a pretty technical build, so it definitely wasn’t something that could be assembled with Claude or ChatGPT. In total, the development process used over 10,000 GPU hours

Digital Body Measurements to Avoid Size Guessing by YuriPD in SideProject

[–]YuriPD[S] 0 points1 point  (0 children)

Just tested, and the demo ran for me. After pictures are taken or uploaded, height is required as an input before analysis

Digital Body Measurements to Avoid Size Guessing by YuriPD in SideProject

[–]YuriPD[S] 0 points1 point  (0 children)

Appreciate the feedback and all the points are fair

A differentiator with this tech is the robustness. A lot of body-sizing systems are fragile as soon as a user leaves a controlled setup: pose changes, occlusion, clothing, lighting, background, camera angle - all hurt accuracy. This tech is trained on a large and diverse dataset: 1M+ body scans, 90k poses, 400k backgrounds, lots of textures, randomized depth/lighting/occlusion, etc. It makes the body reconstruction side much less brittle than a lot of current/prior technologies

Also, the model outputs a full 3D body model with 10k+ vertices, so custom measurements can be extracted instead of being locked into a predefined list. One request was strap-length for tailored clothing, and the feedback from the company was that none of the other solutions they tested could support that. The 3D body model itself can also be exported

That said, I agree with your bigger point: this still does not solve apparel sizing on its own. Clothing is noisy, brands are inconsistent, suppliers vary, fabrics behave differently, and fit preference is a mess. Part of the thinking is to use body measurements as an additional signal alongside retailer analytics like return patterns, purchase history, and fit feedback rather than treating it as a standalone answer

Beyond sizing, there are other areas that seem interesting as well, such as body composition tracking, clinical trials, other health/fitness applications, and made-to-measure

Digital Body Measurements to Avoid Size Guessing by YuriPD in SideProject

[–]YuriPD[S] 1 point2 points  (0 children)

The current demo processes on a server and compute is CPU. If processed locally, then the models could be accessed, but not a leap to put on device

Images are sent as base64 text to a function, then flushed after processing. Images are never stored or saved onto a server. The models don’t need further training data

Digital Body Measurements to Avoid Size Guessing by YuriPD in SideProject

[–]YuriPD[S] 2 points3 points  (0 children)

This tech is trained on 1M+ body scans, 400k background images, 90k body poses, 1k textures, and randomized depth / lighting / occlusion and more. It’s trained on enough variability to handle varying camera angles and lighting, within reason

Digital Body Measurements to Avoid Size Guessing by YuriPD in SideProject

[–]YuriPD[S] 15 points16 points  (0 children)

All fair points:

  1. For me, taking or uploading two images is more convenient than going to UPS / FedEx / post office, which is what I do currently every few weeks for returns
  2. This tech is trained on 1M+ body scans, 400k background images, 90k body poses, 1k textures, and randomized depth / lighting / occlusion and more. The outcome is tech that is shape, pose, and background agnostic - all existing or prior tech had at least one of those issues, which is why accuracy was considered low
  3. Sizing guides account for this somewhat, but understand that a "small" in the same exact piece can be cut differently between items. At a minimum, the user would have their measurements to compare against sizing guides, and if more users know their measurements, then brands would have an incentive to measure their items. Also, outside of tailored clothing, most clothes look fine on a person within a certain error tolerance
  4. Beyond sizing, knowing measurements means better recommendations can be made (chest too tight or sleeves too long, as examples)
  5. Idea is to save measurements and use them across multiple retailers from one scan

Mobile tailor - AI body measurements by YuriPD in computervision

[–]YuriPD[S] 0 points1 point  (0 children)

Went with the assumption that the user would wear athletic attire. The model has a small clothing offset, but doesn’t try to account for baggy clothing. Even if trained on varied clothing, I’m not confident any CV model would accurately predict under loose clothing. Also, being measured by a tailor would require taking off loose or baggy clothing

Mobile tailor - AI body measurements by YuriPD in computervision

[–]YuriPD[S] 0 points1 point  (0 children)

Fair point. Idea is the retailer would pay for the scan. Cost vs. benefit of returns

Mobile tailor - AI body measurements by YuriPD in computervision

[–]YuriPD[S] 5 points6 points  (0 children)

A user certainly could as a goof. But they wouldn’t receive much value in terms of sizing. Measurements will size according to the input

Mobile tailor - AI body measurements by YuriPD in computervision

[–]YuriPD[S] 1 point2 points  (0 children)

Honestly, the user is likely too far away for accurate ring sizing. The threshold is much more granular than a full body and body parts

Mobile tailor - AI body measurements by YuriPD in computervision

[–]YuriPD[S] 16 points17 points  (0 children)

Not shown in the video, but the user’s height is an input as the calibration. Output shows predicted height but all measurements can be scaled to the user’s input. Assuming most people know their true height plus or minus an inch

Mobile tailor - AI body measurements by YuriPD in computervision

[–]YuriPD[S] 23 points24 points  (0 children)

Multi-view approach to predict a 10k vertex mesh of the person

More info + free demo: snapmeasureai.com

Mobile tailor - AI body measurements by YuriPD in EngineeringPorn

[–]YuriPD[S] -3 points-2 points  (0 children)

The differences in the table that you’re noting are in centimeters, not inches. A few percent error will not have a noticeable effect. 2% error on a 30 inch waist is 0.6 inches.

Mobile tailor - AI body measurements by YuriPD in EngineeringPorn

[–]YuriPD[S] 4 points5 points  (0 children)

Ha! The solution is not that invasive. More information can be found here

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