What's next:
- WebRTC integration for video calls
- Built-in barcode/QR code scanning
- Face detection hooks
That sounds to me like final application usages that should be independent from this project, which is just a HAL for camera access. Conflating the two into the same code seems to raise the bar incredibly high for the scope of this one, so not sure how that will work out. WebRTC alone is a very complicated beast, for which the camera acquisition is just a very small part.That page says that "By using the OS’s native web renderer, the size of a Tauri app can be little as 600KB." sounds like an alternative for Electron basically
If need only mobile (iOS / Android) then react-native-vision-camera probably the best bet.
If need only simple camera access then opencv
I thought the "demo_crabcamera.py" was funny with respect to vibecoding: it's not a demo (I already found it odd for a Tauri app to be demo-ed via a python script); it produces the description text posted by OP.
On a more serious note, it all looks reasonably complete like most AI generated projects, but also almost a one shot generated project which hasn't seen much use for it to mature. This becomes even more true when you look a bit deeper at the code, where there are unfinished methods like:
pub fn get_device_caps(device_path: &str) -> Result<Vec<String>, CameraError> {
// This would typically query V4L2 capabilities
// For now, return common capabilities
Ok(vec![
"Video Capture".to_string(),
"Streaming".to_string(),
"Extended Controls".to_string(),
])
}
The project states it builds on nokhwa for the real camera capture capabilities, but then conditionally includes platform libraries, which seem to be only used for tests (which means they could have been dev-dependencies), at least in the case of v4l, based on the results of GitHub's search within the repo.Perhaps it all works, but it does feel a bit immature and it does come with the risks of AI generated code.