How to set input with image for tensorflow-lite in

I am trying to move our Tensoflow model from Python+Keras version to Tensorflow Lite with C++ on an embedded platform.

It looks like I don't know how set properly input for interpreter.

Input shape should be (1, 224, 224, 3).

As an input I am taking image with openCV, converting this to CV_BGR2RGB.


std::unique_ptr<tflite::FlatBufferModel> model_stage1 = 
tflite::FlatBufferModel::BuildFromFile("model1.tflite");
  TFLITE_MINIMAL_CHECK(model_stage1 != nullptr);

  // Build the interpreter
  tflite::ops::builtin::BuiltinOpResolver resolver_stage1;
  std::unique_ptr<Interpreter> interpreter_stage1;
  tflite::InterpreterBuilder(*model_stage1, resolver_stage1)(&interpreter_stage1);

TFLITE_MINIMAL_CHECK(interpreter_stage1 != nullptr);

  cv::Mat cvimg = cv::imread(imagefile);
  if(cvimg.data == NULL) {
    printf("=== IMAGE READ ERROR ===\n");
    return 0;
  }

  cv::cvtColor(cvimg, cvimg, CV_BGR2RGB);

  uchar* input_1 = interpreter_stage1->typed_input_tensor<uchar>(0);

 memcpy( ... );

I have issue with proper setup of memcpy for this uchar type.

When I am doing like this, I have seg fault during working:

memcpy(input_1, cvimg.data, cvimg.total() * cvimg.elemSize());

How should I properly fill input in this case?

To convert my comments into an answer: Memcpy might not be the right approach here. OpenCV saves images as 1-dimensional arrays of RGB-ordered (or BGR or yet another color combination) color values per pixel. It is possible to iterate over these RGB-chunks via:

for (const auto& rgb : cvimg) {
    // now rgb[0] is the red value, rgb[1] green and rgb[2] blue.
}

And writing values to a Tensorflow-Lite typed_input_tensor should be done like this; where i is the index (iterator) and x the assigned value:

interpreter->typed_input_tensor<uchar>(0)[i] = x;

So the loop could look like this:

for (size_t i = 0; size_t < cvimg.size(); ++i) {
    const auto& rgb = cvimg[i];
    interpreter->typed_input_tensor<uchar>(0)[3*i + 0] = rgb[0];
    interpreter->typed_input_tensor<uchar>(0)[3*i + 1] = rgb[1];
    interpreter->typed_input_tensor<uchar>(0)[3*i + 2] = rgb[2];
}