#include "opaque_types.h" #include <dlib/python.h> #include "dlib/pixel.h" #include <dlib/image_transforms.h> #include <dlib/image_io.h> #include <pybind11/numpy.h> using namespace dlib; using namespace std; namespace py = pybind11; // -------------------------------- Basic Image IO ---------------------------------------- numpy_image<rgb_pixel> load_rgb_image (const std::string &path) { numpy_image<rgb_pixel> img; load_image(img, path); return img; } bool has_ending (std::string const full_string, std::string const &ending) { if(full_string.length() >= ending.length()) { return (0 == full_string.compare(full_string.length() - ending.length(), ending.length(), ending)); } else { return false; } } // ---------------------------------------------------------------------------------------- template <typename T> void save_image(numpy_image<T> img, const std::string &path) { std::string lowered_path = path; std::transform(lowered_path.begin(), lowered_path.end(), lowered_path.begin(), ::tolower); if(has_ending(lowered_path, ".bmp")) { save_bmp(img, path); } else if(has_ending(lowered_path, ".dng")) { save_dng(img, path); } else if(has_ending(lowered_path, ".png")) { save_png(img, path); } else if(has_ending(lowered_path, ".jpg") || has_ending(lowered_path, ".jpeg")) { save_jpeg(img, path); } else { throw dlib::error("Unsupported image type, image path must end with one of [.bmp, .png, .dng, .jpg, .jpeg]"); } return; } // ---------------------------------------------------------------------------------------- py::list get_jitter_images(numpy_image<rgb_pixel> img, size_t num_jitters = 1, bool disturb_colors = false) { static dlib::rand rnd_jitter; // The top level list (containing 1 or more images) to return to python py::list jitter_list; for (int i = 0; i < num_jitters; ++i) { // Get a jittered crop numpy_image<rgb_pixel> crop = dlib::jitter_image(img, rnd_jitter); // If required disturb colors of the image if(disturb_colors) dlib::disturb_colors(crop, rnd_jitter); // Append image to jittered image list jitter_list.append(crop); } return jitter_list; } // ---------------------------------------------------------------------------------------- py::list get_face_chips ( numpy_image<rgb_pixel> img, const std::vector<full_object_detection>& faces, size_t size = 150, float padding = 0.25 ) { if (faces.size() < 1) { throw dlib::error("No face were specified in the faces array."); } py::list chips_list; std::vector<chip_details> dets; for (auto& f : faces) dets.push_back(get_face_chip_details(f, size, padding)); dlib::array<numpy_image<rgb_pixel>> face_chips; extract_image_chips(img, dets, face_chips); for (auto& chip : face_chips) { // Append image to chips list chips_list.append(chip); } return chips_list; } numpy_image<rgb_pixel> get_face_chip ( numpy_image<rgb_pixel> img, const full_object_detection& face, size_t size = 150, float padding = 0.25 ) { numpy_image<rgb_pixel> chip; extract_image_chip(img, get_face_chip_details(face, size, padding), chip); return chip; } // ---------------------------------------------------------------------------------------- void bind_numpy_returns(py::module &m) { m.def("load_rgb_image", &load_rgb_image, "Takes a path and returns a numpy array (RGB) containing the image", py::arg("path") ); m.def("save_image", &save_image<rgb_pixel>, "Saves the given image to the specified path. Determines the file type from the file extension specified in the path", py::arg("img"), py::arg("path") ); m.def("save_image", &save_image<unsigned char>, "Saves the given image to the specified path. Determines the file type from the file extension specified in the path", py::arg("img"), py::arg("path") ); m.def("jitter_image", &get_jitter_images, "Takes an image and returns a list of jittered images." "The returned list contains num_jitters images (default is 1)." "If disturb_colors is set to True, the colors of the image are disturbed (default is False)", py::arg("img"), py::arg("num_jitters")=1, py::arg("disturb_colors")=false ); m.def("get_face_chip", &get_face_chip, "Takes an image and a full_object_detection that references a face in that image and returns the face as a Numpy array representing the image. The face will be rotated upright and scaled to 150x150 pixels or with the optional specified size and padding.", py::arg("img"), py::arg("face"), py::arg("size")=150, py::arg("padding")=0.25 ); m.def("get_face_chips", &get_face_chips, "Takes an image and a full_object_detections object that reference faces in that image and returns the faces as a list of Numpy arrays representing the image. The faces will be rotated upright and scaled to 150x150 pixels or with the optional specified size and padding.", py::arg("img"), py::arg("faces"), py::arg("size")=150, py::arg("padding")=0.25 ); }