Flutter 使用TFLITE插件将TFLITE自定义模型与颤振集成时遇到问题

我使用Keras构建了一个自定义模型，并将其转换为TFLITE模型。CNN模型的输入形状是60*60*3，因此当数据类型是int时，所需的缓冲区将是60*60*3*4=43200。现在，在使用功能将模型与颤振集成时-

    recognitions = await Tflite.runModelOnImage(
          path: widget.imagePath,
          imageMean: 127.5,
          imageStd: 127.5,
          numResults: 2,
          threshold: 0.1,
          asynch: true);
      print(recognitions);
    } 

我收到这个错误-

    E/AndroidRuntime(21412): Caused by: java.lang.IllegalArgumentException: Cannot convert between a TensorFlowLite buffer with 21600 bytes and a Java Buffer with 43200 bytes.
E/AndroidRuntime(21412):    at org.tensorflow.lite.Tensor.throwIfShapeIsIncompatible(Tensor.java:332)
E/AndroidRuntime(21412):    at org.tensorflow.lite.Tensor.throwIfDataIsIncompatible(Tensor.java:305)
E/AndroidRuntime(21412):    at org.tensorflow.lite.Tensor.setTo(Tensor.java:123)
E/AndroidRuntime(21412):    at org.tensorflow.lite.NativeInterpreterWrapper.run(NativeInterpreterWrapper.java:150)
E/AndroidRuntime(21412):    at org.tensorflow.lite.Interpreter.runForMultipleInputsOutputs(Interpreter.java:311)
E/AndroidRuntime(21412):    at org.tensorflow.lite.Interpreter.run(Interpreter.java:272)
E/AndroidRuntime(21412):    at sq.flutter.tflite.TflitePlugin$RunModelOnImage.runTflite(TflitePlugin.java:452)
E/AndroidRuntime(21412):    at sq.flutter.tflite.TflitePlugin$TfliteTask.doInBackground(TflitePlugin.java:419)
E/AndroidRuntime(21412):    at sq.flutter.tflite.TflitePlugin$TfliteTask.doInBackground(TflitePlugin.java:393)
E/AndroidRuntime(21412):    at android.os.AsyncTask$2.call(AsyncTask.java:333)
E/AndroidRuntime(21412):    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
E/AndroidRuntime(21412):    ... 4 more

关于如何解决这个错误有什么建议吗