How do I pass an OpenCV Mat into a C++ Tensorflow graph?

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In Tensorflow C++ I can load an image file into the graph using

tensorflow::Node* file_reader =  tensorflow::ops::ReadFile(tensorflow::ops::Const(IMAGE_FILE_NAME, b.opts()),b.opts().WithName(input_name));
tensorflow::Node* image_reader = tensorflow::ops::DecodePng(file_reader, b.opts().WithAttr("channels", 3).WithName("png_reader"));
tensorflow::Node* float_caster = tensorflow::ops::Cast(image_reader, tensorflow::DT_FLOAT, b.opts().WithName("float_caster"));
tensorflow::Node* dims_expander = tensorflow::ops::ExpandDims(float_caster, tensorflow::ops::Const(0, b.opts()), b.opts());
tensorflow::Node* resized = tensorflow::ops::ResizeBilinear(dims_expander, tensorflow::ops::Const({input_height, input_width},b.opts().WithName("size")),b.opts());

For an embedded application I would like to instead pass an OpenCV Mat into this graph.

How would I convert the Mat to a tensor that could be used as input to tensorflow::ops::Cast or tensorflow::ops::ExpandDims?

tensorflow opencv c++
4 Answers

Here is complete example to read and feed:

Mat image;
image = imread("flowers.jpg", CV_LOAD_IMAGE_COLOR);
cv::resize(image, image, cv::Size(input_height, input_width), 0, 0, CV_INTER_CUBIC);

int depth = 3;
tensorflow::Tensor input_tensor(tensorflow::DT_FLOAT,
                                tensorflow::TensorShape({1, image.rows, image.cols, depth}));

for (int y = 0; y < image.rows; y++) {
    for (int x = 0; x < image.cols; x++) {
        Vec3b pixel = image.at<Vec3b>(y, x);

        input_tensor_mapped(0, y, x, 0) = pixel.val[2]; //R
        input_tensor_mapped(0, y, x, 1) = pixel.val[1]; //G
        input_tensor_mapped(0, y, x, 2) = pixel.val[0]; //B
    }
}

auto result = Sub(root.WithOpName("subtract_mean"), input_tensor, {input_mean});
ClientSession session(root);
TF_CHECK_OK(session.Run({result}, out_tensors));
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Tensor convertMatToTensor(Mat &input)
{
    int height = input.rows;
    int width = input.cols;
    int depth = input.channels();

    Tensor imgTensor(tensorflow::DT_FLOAT, tensorflow::TensorShape({height, width, depth}));

    float* p = imgTensor.flat<float>().data();
    Mat outputImg(height, width, CV_32FC3, p);
    input.convertTo(outputImg, CV_32FC3);

    return imgTensor;
}
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