title: Run inference with an openCV image
body: <p>I have an Android Project with OpenCV4.0.1 and TFLite installed.
  And I want to make an inference with a pretrained MobileNetV2 of an cv::Mat which I extracted and cropped from a CameraBridgeViewBase (Android style).
  But it's kinda difficult.</p>
  
  <p>I followed <a href="https://github.com/tensorflow/examples/tree/master/lite/examples/image_classification/android" rel="nofollow noreferrer">this</a> example.</p>
  
  <p>That does the inference about a ByteBuffer variable called "imgData" (line 71, class: org.tensorflow.lite.examples.classification.tflite.Classifier)</p>
  
  <p>That imgData looks been filled on the method called "convertBitmapToByteBuffer" from the same class (line 185), adding pixel by pixel form a bitmap that looks to be cropped little before.</p>
  
  <pre class="lang-java prettyprint-override"><code>private int[] intValues = new int[224 * 224];
  Mat _croppedFace = new Mat() // Cropped image from CvCameraViewFrame.rgba() method.
  
  float[][] outputVal = new float[1][1]; // Output value from my MobileNetV2 // trained model (i've changed the output on training, tested on python)
  
  // Following: https://stackoverflow.com/questions/13134682/convert-mat-to-bitmap-opencv-for-android
  Bitmap bitmap = Bitmap.createBitmap(_croppedFace.cols(), _croppedFace.rows(), Bitmap.Config.ARGB_8888);
  Utils.matToBitmap(_croppedFace, bitmap);
  
  convertBitmapToByteBuffer(bitmap); // This call should be used as the example one.
  // runInference();
  _tflite.run(imgData, outputVal);
  </code></pre>
  
  <p>But, it looks that the input_shape of my NN is not correct, but I'm following the MobileNet example because my NN it's a MobileNetV2.</p>