Quick tip if you use the AI Hairstyle Virtual Try-On API in Customize mode, where users upload a reference photo of the style they want.

Preset Style already let users keep their own hair color, but Customize didn’t. Before V2.1, it always copied the reference photo’s hair color along with the cut. A user with dark brown hair trying on a blonde reference look came out blonde, whether they wanted that or not.

V2.1 gives Customize the same choice with one optional parameter:

• hair_color: "src" → keeps the user’s own hair color from their uploaded photo
• hair_color: "ref" → applies the reference image’s hair color (the old Customize behavior)

A few details worth knowing:

• It sits under the hairTransfer effect (API v1.16+) and applies to Customize mode (style: customize).
• If you leave hair_color out, it defaults to ref. Existing integrations keep working as-is.
• The output format is the same, so your Get Result handling doesn’t change.

⚠️ One gotcha: the API Playground defaults to User’s Hair Color, but the API defaults to ref. If your Playground result doesn’t match your first API call, that’s probably why.

To try it without writing code, open the Hairstyle API Playground, set Version to V2.1, go to the Customize tab, and switch between User’s Hair Color and Reference Hair Color. The full parameter reference is in the Hairstyle API docs. For more details, check the V2.1 release post on our blog.

If you’re building hairstyle try-on, which default would your users expect: keeping their own color, or matching the reference? 👇

Most people hear “AI skin analysis” and think of beauty apps: selfie in, skin report out, product recommendations. That’s the obvious use case, but it’s probably not the only one.

So this week’s question: where else could an AI skin analysis API make sense? 🤔

A few directions to get things started:

• Wellness and lifestyle apps. Let users track how their skin looks over time alongside sleep, hydration or routine changes.
• Sun care and outdoor brands. Pair a skin check with education about sun protection habits.
• Retail kiosks or in-store mirrors. Offer a quick skin check at the shelf instead of only in an app.
• Content and creator tools. Build personalized skincare content or routines around an analysis result.

Curious what this community would build:

1. What industry or product would you plug skin analysis into?
2. What would make you trust (or not trust) the results as a user?
3. Anything you’d need from the API before you’d ship it?

If you want to see what the output looks like before brainstorming, you can try the AI Skin Analysis API in the API Playground with your own photo.

Drop your ideas in the comments, even half-baked ones 👇

Weekly API Tip 🧪 AI Skin Analysis

If your AI Skin Analysis results look off, check the input photo before you start debugging your code. Here’s what the API expects:

Size and format

• JPEG or PNG, under 10 MB
• SD: short side at least 480 px
• HD: short side at least 1080 px
• If the long side is over 2560 px, the API resizes it for you

Framing

• The face should take up more than 60% of the image width. Otherwise you’ll get error_src_face_too_small.
• Face the camera directly and keep the face centered, with a neutral expression, mouth closed and eyes open
• Portrait orientation is strongly recommended over landscape

Conditions

• Use bright, even light and avoid blown-out highlights. A photo that’s too dark returns error_lighting_dark.
• Keep the forehead visible: brush bangs back or tie hair up
• Take glasses off (recommended, not required) and remove makeup for more accurate results
• Avoid motion blur and anything covering the face

An easy way to see the difference is to run the same face in the API Playground twice, once in good light and once in a dim room, and compare the results.

👉 Try AI Skin Analysis in the API Playground

Question for you: if you’ve built skin analysis into an app, how do you get users to take a usable selfie? Overlay guides, a checklist, auto-capture, something else? 👇

We’ve added AI Watermark Removal API to the Image category of YouCam API.

The new standalone effect, wmkRemoval, detects and removes watermarks from images you have the rights to use and returns a cleaned result image.

The workflow follows three steps:

1. Create a file using an image URL, File ID, or supported sample image
2. Run the Watermark Removal task
3. Check the task status and retrieve the result URL when processing is complete

A few integration details:

• Available on API 2.0
• Runs as an asynchronous task
• Effect name: wmkRemoval

If you’re already building on API 2.0, the feature can be added alongside other YouCam Image APIs.

👉 Read the release details on our blog

If you try it in a project, feel free to share your use case or results with the community. 🛠️

We’ve added a new option to YouCam Hair Style Virtual Try-On API for developers using Customize mode.

Previously, when a user provided a reference hairstyle, Customize automatically transferred the reference image’s hair color along with the style.

V2.1 introduces a new optional hair_color parameter under the hairTransfer effect:

• src → keep the user’s original hair color
• ref → use the reference image’s hair color

If hair_color is omitted, it defaults to ref, so existing integrations continue to behave the same way.

You can also test the feature directly in the API Playground by selecting Hair Style → V2.1 → Customize and choosing between User’s Hair Color and Reference Hair Color.

👉 Read the full announcement on our blog

If you try the new option, let us know how you’re using it in your project.

One of the winning teams from the YouCam API Skin AI & Apparel VTO Hackathon sent us a thank-you video after the results were announced, so we wanted to share it here with the community.

Their project, CASTING, takes an interesting B2B approach to virtual try-on: using YouCam Apparel Virtual Try-On API and Skin AI capabilities to help brands evaluate product representation across different skin tones.

🎥 Watch their message:
https://www.youtube.com/watch?v=US2gASXnCw4

🛠️ Explore CASTING on Devpost:
https://devpost.com/software/casting

Thanks again to everyone who participated in the hackathon. We’ve really enjoyed seeing the different ways developers approached the APIs.

BeautyMirror is my submission for the YouCam API Hackathon 2026.

I wanted to build something that goes beyond simply analyzing your skin or trying on clothes — a complete beauty and style experience that brings these capabilities together in one app.

BeautyMirror is a fully functional iOS application, combining AI skin analysis, skincare tracking, wardrobe management, and virtual try-on.

The idea is simple: understand your skin, make better use of the products and clothes you already own, and discover what works for you before making a decision.

Built with the YouCam Skin Analysis API and Apparel Virtual Try-On, the app connects these experiences into one seamless workflow.

🎥 Demo video above.

I’d love to hear what you think!

There are a lot of different directions you can take when adding AI-powered experiences to an app or website.

We’re curious what developers and product teams are most interested in right now:

• Skin analysis
• Virtual makeup try-on
• Hair color or hairstyle try-on
• Clothes virtual try-on
• Fashion and accessory try-on
• Face analysis
• AI image editing
• Something else entirely

What are you exploring, and what kind of product or experience would you use it for?

If you’re already experimenting with YouCam API, feel free to share what you’re working on too.

We also have an official Discord community for developers building with YouCam API :)

You can use it to:

• Ask questions and discuss API integrations
• Report bugs
• Request features
• Explore the API Playground
• Share what you’re building
• Keep up with product announcements

Join here: YouCam API Discord

We’re just getting this community started, and we want it to be genuinely useful for developers.

What kind of content would you like to see here?

A few ideas:

• API updates and new feature announcements
• Integration examples
• Short tutorials and getting-started guides
• Common questions and troubleshooting discussions
• API Playground examples
• Developer showcases
• Product and use case discussions

If there’s something else that would make this community more useful to you, let us know below.

Virtual try-on can be used across fashion, beauty, eyewear, accessories, and other shopping experiences — but the most interesting use cases usually depend on the product itself.

For developers and product teams working with VTO:

Where do you think virtual try-on adds the most value?

For example:

• E-commerce product pages
• Shopping apps
• Product recommendation flows
• In-store experiences
• Social or interactive campaigns
• AI shopping assistants

We’d be interested to hear what you’re building or where you think VTO works best.

If you’re exploring YouCam API for the first time, these are the main resources available to help you get familiar with the platform:

📚 API Documentation

🧪 API Console

💬 Discord Developer Community

You can use the documentation to explore available APIs and requirements, and the API Playground to test supported features before building them into your own product.

And of course, you can also post questions here in r/YouCamAPI

We’re curious to hear what kinds of projects developers are working on with AI APIs — whether it’s virtual try-on, image editing, beauty tech, e-commerce, content creation, or something completely different.

If you’re building with YouCam API, feel free to share what you’re working on, what stage you’re at, and what kind of API capabilities would make your project easier.

No need to share anything confidential — even a general description is welcome.