Skip to content

googlesamples/arcore-ml-sample

Repository files navigation

ARCore ML sample

An ARCore sample demonstrating how to use camera images as an input for machine learning algorithms, and how to use the results of the inference model to create anchors in the AR scene.

This sample uses ML Kit's Object Detection and (optionally) Google's Cloud Vision API to infer object labels from camera images.

Getting Started

To try this app, you'll need the following:

Configure ML Kit's classification model

By default, this sample uses ML Kit's built-in coarse classifier, which is only built for five categories and provides limited information about the detected objects.

For better classification results:

  1. Read Label images with a custom model on Android on ML Kit's documentation website.
  2. Modify MLKitObjectAnalyzer.kt in app/src/main/java/com/google/ar/core/examples/java/ml/classification/ to specify a custom model.

[Optional] Configure Google Cloud Vision API

This sample also supports results from the Google Cloud Vision API for even more information on detected objects.

To configure Google Cloud Vision APIs:

  1. Follow steps for configuring a Google Cloud project, enabling billing, enabling the API, and enabling a service account on Set up the Vision API documentation.
  2. Save the resulting service account key file to app/src/main/res/raw/credentials.json.

License

Copyright 2021 Google LLC

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published