Sample Code

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// Create an on-device image classification analyzer that uses the default configuration.
MLImageClassificationAnalyzer analyzer = MLAnalyzerFactory.getInstance().getLocalImageClassificationAnalyzer();
// You can also create an on-cloud classification analyzer in a similar way.
// MLImageClassificationAnalyzer analyzer = MLAnalyzerFactory.getInstance().getRemoteImageClassificationAnalyzer();
// Create an MLFramMLFrameing the bitmap.It is recommended that the image size be greater than or equal to 224 x 224.
MLFrame frame = MLFrame.fromBitmap(bitmap);
Task<List<MLImageClassification>> task = analyzer.asyncAnalyseFrame(frame);
task.addOnSuccessListener(new OnSuccessListener<List<MLImageClassification>>() {
   public void onSuccess(List<MLImageClassification>classifications) {
      // Process the classification result.
   }
}).addOnFailureListener(new OnFailureListener() {
   public void onFailure(Exception e) {
      // Processing failure.
   }
});

Constant Summary

Public Method Summary

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Throws