Function test_shape_predictor_with_images_py

tools/python/src/shape_predictor.cpp:112–153

inline double test_shape_predictor_with_images_py (
        const py::list& pyimages,
        const py::list& pydetections,
        const py::list& pyscales,
        const shape_predictor& predictor
)
{
    const unsigned long num_images = py::len(pyimages);
    const unsigned long num_scales = py::len(pyscales);
    if (num_images != py::len(pydetections))
        throw dlib::error("The length of the detections list must match the length of the images list.");

    if (num_scales > 0 && num_scales != num_images)
        throw dlib::error("The length of the scales list must match the length of the detections list.");

    std::vector<std::vector<full_object_detection> > detections(num_images);
    std::vector<std::vector<double> > scales;
    if (num_scales > 0)
        scales.resize(num_scales);
    dlib::array<numpy_image<unsigned char>> images(num_images);

    // Now copy the data into dlib based objects so we can call the testing routine.
    for (unsigned long i = 0; i < num_images; ++i)
    {
        const unsigned long num_boxes = py::len(pydetections[i]);
        for (py::iterator det_it = pydetections[i].begin();
             det_it != pydetections[i].end();
             ++det_it)
          detections[i].push_back(det_it->cast<full_object_detection>());

        assign_image(images[i], pyimages[i].cast<py::array>());
        if (num_scales > 0)
        {
            if (num_boxes != py::len(pyscales[i]))
                throw dlib::error("The length of the scales list must match the length of the detections list.");
            for (py::iterator scale_it = pyscales[i].begin(); scale_it != pyscales[i].end(); ++scale_it)
                scales[i].push_back(scale_it->cast<double>());
        }
    }

    return test_shape_predictor_with_images(images, detections, scales, predictor);
}

inline double test_shape_predictor_with_images_no_scales_py (
        const py::list& pyimages,