lohasearch.blogg.se - Accompanist android

ACCOMPANIST ANDROID ANDROID
ACCOMPANIST ANDROID CODE

The analyzer has two listeners you can subscribe to, one is the successful listener to return the detected gesture category list, it may or may not has any gesture detected.

ACCOMPANIST ANDROID ANDROID

But you need to add UnsafeExperimentalUsageError annotation as this method is still under experimental and may return null if the ImageProxy can’t wrap the Android Image. In this demo, the Android image is used to construct the MLFrame as ImageProxy already wrap it. There are several ways to create MLFrame from images, such as bitmap, byte buffer or Android Image. Using the ML analyzer is really straightforward, create the instance and call the analysis method to analyze the MLFrame. I will start the gesture detection for the camera frame first.

ACCOMPANIST ANDROID CODE

You can also check out the code from this repo if you want to follow it alone. If you want to review the changes you can check out the repo here. You may find more details here and the dependencies set up here. Setup the Huawei ML library is very simple as the training model is already included in the library, you just need to add the maven centre address and ML gesture library dependencies.

In order to display the captured image, an image view composable is created and notify the MediaScannerConnection to add the newly captured image to the media content provider.

To use the image capture use case, I created a ViewModle to handle the image capture use case setup and gesture recognition call back.

First I added a gesture analyzer that uses the gesture recognition API to detect the thumbs-up hand gesture.

Here is a quick review of the changes I made since the last article. I will use the Huawei ML kit in this demo since it has the gesture model already integrated into the hand gesture library, but the code and idea can be easily adapted to other ML libraries. There are several ML libraries you can use on Android for hand gesture recognition, such as Tensor flow lite, Huawei ML Kit or Pytorch Mobile. In this article, I will add this feature by using hand gesture recognition. One of the key features of CameraX we didn’t check is image capture. In the previous article, I used Jetpack Compose and CameraX, implemented a camera preview in the app, and added an image analyzer with the Palette library to track the colour pattern of the incoming camera frame.