ML Kit for Firebase Quickstart
The ML Kit for Firebase Android Quickstart app demonstrates how to use the various features of ML Kit to add machine learning to your application.
- Add Firebase to your Android Project.
- Run the sample on an Android device.
- Choose LivePreviewActivity to see a demo of the following APIs:
- Face detection
- Text recognition (on-device)
- Barcode scanning
- Image labeling (on-device)
- Landmark recognition
- Custom model (Labeled "Classification"). The custom model used in this sample, MobileNet_v1, is already included as a local asset in the project. To use this sample with a hosted model, follow the directions under the "Hosting a Custom Model" section of this readme.
- Choose StillImageActivity to see a demo of the following:
- Image labeling (Cloud)
- Landmark recognition (Cloud)
- Text recognition (Cloud)
- Document text recognition (Cloud)
Hosting a Custom Model
- Download the TensorFlow Lite custom model we are using in this sample.
- Go to the Firebase console.
- Select your project.
- Select ML Kit under the DEVELOP section in the left hand navigation.
- Click on the CUSTOM tab.
- Click on Add another model and use "mobilenet_v1" as the name.
- Click BROWSE and upload the mobilenet_v1_1.0_224_quant.tflite file you downloaded earlier.
- Click PUBLISH.
Copyright 2018 Google, Inc.
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