Contact person: Business Client

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Location: Delhi, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I have an idea for an end-to-end face-analysis solution where true-to-life 3D try-on sits at the core. The workflow I picture is:

• A user points the camera, a backend service detects the face in real time, measures key landmarks to determine shape and dominant skin tone, then immediately streams a realistic 3D overlay (glasses, makeup, jewellery—think virtual fitting-room).
• The heavy lifting happens in an API you will build; the mobile front ends on both iOS and Android simply call it and render the result.

Accuracy matters, but the breakthrough experience hinges on smooth, believable 3D try-on, so every design choice should prioritise that. If you like working with OpenCV, MediaPipe, TensorFlow, ARKit/ARCore or your own blend of frameworks, I’m open—as long as the final deliverables include:

1. A documented REST/GraphQL API that receives a camera frame (or short clip) and returns:
– Face bounding box and landmarks
– Calculated face-shape classification
– Suggested dominant skin-tone values
– The 3D mesh / transformation data needed by the client app for live overlay

2. Sample iOS and Android projects demonstrating the API call and real-time rendering.
3. A short deployment guide so I can spin up the service on my own GPU instance or cloud provider.
4. Unit tests or a test harness that proves detection precision and run-time performance under typical mobile network conditions.

If this brief excites you, tell me a bit about the similar visual-AI or AR tasks you’ve shipped and the toolchain you prefer. I’m happy to iterate quickly, review milestones, and release payments against each verified feature." (client-provided description)