Problem with Android Image classification app start

[Julia2505]

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.

 

[B. Diddy]

I moved this to the Software Development forum for more specific traffic.