1. Julia2505's Avatar
    Hello everyone! While I try to run my custom Image classification app, I am getting a mistake:
    java.lang.IllegalArgumentException: Cannot copy between a TensorFlowLite tensor with shape [1, 30] and a Java object with shape [1, 1].
     at org.tensorflow.lite.Tensor.throwIfShapeIsIncompatible(Tensor.java:282)
     at org.tensorflow.lite.Tensor.throwIfDataIsIncompatible(Tensor.java:249)
     at org.tensorflow.lite.Tensor.copyTo(Tensor.java:141)
     at org.tensorflow.lite.NativeInterpreterWrapper.run(NativeInterpreterWrapper.java:161)
     at org.tensorflow.lite.Interpreter.runForMultipleInputsOutputs(Interpreter.java:275)
     at org.tensorflow.lite.Interpreter.run(Interpreter.java:249)
     at com.example.android.tflitecamerademo.ImageClassifier.classifyFrame(ImageClassifier.java:117)
     at com.example.android.tflitecamerademo.Camera2BasicFragment.classifyFrame(Camera2BasicFragment.java:663)
     at com.example.android.tflitecamerademo.Camera2BasicFragment.access$900(Camera2BasicFragment.java:69)
     at com.example.android.tflitecamerademo.Camera2BasicFragment$5.run(Camera2BasicFragment.java:558)
     at android.os.Handler.handleCallback(Handler.java:873)
     at android.os.Handler.dispatchMessage(Handler.java:99)
     at android.os.Looper.loop(Looper.java:201)
     at android.os.HandlerThread.run(HandlerThread.java:65)
    My model parameters are:
    == Input details ==
    name: x shape: [  1 256 256   3]
    type: <class 'numpy.float32'>
     == Output details ==
    name: Identity shape: [ 1 30]
    type: <class 'numpy.float32'>
    I use .lite format with quantization.
    07-22-2019 07:23 AM
  2. B. Diddy's Avatar
    I moved this to the Software Development forum for more specific traffic.
    07-22-2019 01:12 PM

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