Hello.

I've been exploring Chrome's Shape Detection API and its potential, even creating a QR code detector with a JS polyfill. While I appreciate the API, I'm more impressed by libraries like Jeeliz, which offer faster face detection and broader cross-platform compatibility via WebGL and WASM. This tech allows for augmented reality experiences without large app downloads and data harvesting. There are numerous practical applications for this technology, from text selection and translation to product search and accessibility features. I believe the web is ideal for such experiences, and although I appreciate the native Shape Detection API, its inconsistencies across platforms raise questions about the need for native implementations when web-based solutions using WebGL and WASM can offer better consistency and reach.

I'm excited about the new experimental Shape Detection API in Chrome Canary! It provides a simple JavaScript API for face and barcode detection, leveraging underlying hardware for performance. This opens up new possibilities for web apps, from faster face detection and profile picture cropping to real-time tagging and optimized facial recognition. While currently only available in Chrome for Android (desktop support coming soon), I've shared a demo on JSBin. I also discuss strategies for progressive enhancement to ensure broader compatibility, including server-side detection, client-side JavaScript libraries, and the potential of Web Assembly. This API has the potential to revolutionize object detection performance on the web, and I'm particularly keen to see its impact on barcode scanning apps like my own QR Snapper.