2D Eyewear Virtual Try-On
Budget: ₹37,500 – ₹75,000 INR
I want shoppers on the Laxmi Opticians site to slip on any frame from our catalogue without leaving the page. The idea is a lightweight, 2-D computer-vision overlay that precisely positions sunglasses and prescription glasses on a customer’s face, working fluidly on both desktop and mobile browsers. No full 3-D modelling, no manual prompt engineering—just an instant preview that feels as natural as looking in a mirror.
The experience must offer two entry points:
• Real-time overlay through the user’s webcam or phone camera.
• Photo upload for those who prefer to try glasses on a still image.
Accuracy is critical: pupils should align, temple angles should respect head pose, and scaling must stay consistent as users lean closer or farther from the camera. I’m open to the stack you choose—MediaPipe FaceMesh, OpenCV, TensorFlow.js, or a custom WebAssembly module—as long as the final JS/HTML/CSS bundle is small, loads quickly, and can be dropped into a React storefront with minimal wiring.
Deliverables
1. Embeddable front-end component (React preferred) with clear API hooks for product ID, frame PNG/SVG, and colour variants.
2. Back-end or edge function (if needed) for any image pre-processing.
3. Integration guide and commented source so my in-house devs can extend it.
4. Short test plan demonstrating alignment accuracy across common devices and lighting conditions.
Acceptance will be based on latency (<150 ms overlay update on mid-range mobile), alignment precision (≤3 px average pupil offset in sample tests), and straightforward plug-and-play integration into our existing checkout flow.
The experience must offer two entry points:
• Real-time overlay through the user’s webcam or phone camera.
• Photo upload for those who prefer to try glasses on a still image.
Accuracy is critical: pupils should align, temple angles should respect head pose, and scaling must stay consistent as users lean closer or farther from the camera. I’m open to the stack you choose—MediaPipe FaceMesh, OpenCV, TensorFlow.js, or a custom WebAssembly module—as long as the final JS/HTML/CSS bundle is small, loads quickly, and can be dropped into a React storefront with minimal wiring.
Deliverables
1. Embeddable front-end component (React preferred) with clear API hooks for product ID, frame PNG/SVG, and colour variants.
2. Back-end or edge function (if needed) for any image pre-processing.
3. Integration guide and commented source so my in-house devs can extend it.
4. Short test plan demonstrating alignment accuracy across common devices and lighting conditions.
Acceptance will be based on latency (<150 ms overlay update on mid-range mobile), alignment precision (≤3 px average pupil offset in sample tests), and straightforward plug-and-play integration into our existing checkout flow.