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Thank you for pointing this out. I overlooked this. I presume that on top of that what also could be relevant is the movements of arms, facial expressions and maybe also general body posture. Please correct me if I'm wrong as I'm not too familiar with sign language.

Thank you for sharing this creative idea. "so that the fingers can touch (or almost touch) the screen" I think this is a big advantage of this approach since you can only achieve this with the back facing camera. On the flip side, with a back facing camera you either have to place the camera in between yourself and the screen which might be awkward or you have to ensure a placement of the camera behind you that isn't prone to occlusions (e.g. your head or chair might occlude your hands from the cameras point of view). The latter might also make calibration more difficult or impact precision since you might have to mount the camera with some elevation causing a less optimal camera angle.

Thank you for the feedback.

Thank you for the feedback.

Thank you for the feedback. You are right, the home page should probably be enriched with more information and maybe I can make the information you were looking for stand out better. As a side note: There is a link to GitHub in the footer. The language ("TypeScript API") is also mentioned in the body of the page. But I see that these two can quickly go unnoticed.

Thank you for your feedback.

Thank you for this inspiring question. For interpreting sign language you need multi-hand support which YoHa is currently lacking. Apart from that you likely also need to account for the temporal dimension which YoHa also does not do right now. If those things were implemented I'm confident that it would produce meaningful results.

Thank you for the feedback. Indeed such a functionality would be nice. One could solve this via another hand pose or in some way also with the existing hand poses. E.g. make a fist for say 2 seconds to clear the whole screen. Anything shorter will just issue an "undo".

YoHa uses tfjs.js which provides several backends for computation. One indeed uses WASM, the other one is WebGL based. The latter one is usually the more powerful one.

Thank you for the feedback. You are right that the project is not open source right now. It's "only" MIT licensed. That's why I also don't advertise it as open source (if you see the word open source somewhere it would be a mistake on my end, feel free to tell me if you see it somewhere). I wanted to start out from just an API contract so that it is easier to manage and get started. In general I have no problem open sourcing the JS part. But first there is some refactoring to do so it is easier to maintain upon open sourcing. Stay tuned!

As a side note: The wasm files are actually from the inference engine (tfjs).

Please let me know if you have any more questions in that regard.

That's an interesting idea. I have not tried to build something similar but a humble word of caution that I want to put out is that no matter what kind of ML you use the mechanical version of the instrument will always be more precise (you likely are aware of it, just want to make sure). However, you might be able to approximate precision of the mechanical version.

Two hand support would be nice and I would love to add it in the future.

The engine should work well with different skin tones as the training data was collected from a set of many and diverse individuals. The training data will also grow further over time making it more and more robust.