// Copyright (c) OpenMMLab. All rights reserved. #include "text_detector.h" #include "common.h" namespace mmdeploy { class PyTextDetector { public: PyTextDetector(const char *model_path, const char *device_name, int device_id) { auto status = mmdeploy_text_detector_create_by_path(model_path, device_name, device_id, &handle_); if (status != MM_SUCCESS) { throw std::runtime_error("failed to create text_detector"); } } std::vector> Apply(const std::vector &imgs) { std::vector mats; mats.reserve(imgs.size()); for (const auto &img : imgs) { auto mat = GetMat(img); mats.push_back(mat); } mm_text_detect_t *detection{}; int *result_count{}; auto status = mmdeploy_text_detector_apply(handle_, mats.data(), (int)mats.size(), &detection, &result_count); if (status != MM_SUCCESS) { throw std::runtime_error("failed to apply text_detector, code: " + std::to_string(status)); } auto output = std::vector>{}; auto result = detection; for (int i = 0; i < mats.size(); ++i) { auto bboxes = py::array_t({result_count[i], 9}); for (int j = 0; j < result_count[i]; ++j, ++result) { auto data = bboxes.mutable_data(j); for (const auto &p : result->bbox) { *data++ = p.x; *data++ = p.y; } *data++ = result->score; } output.push_back(std::move(bboxes)); } mmdeploy_text_detector_release_result(detection, result_count, (int)mats.size()); return output; } ~PyTextDetector() { mmdeploy_text_detector_destroy(handle_); handle_ = {}; } private: mm_handle_t handle_{}; }; static void register_python_text_detector(py::module &m) { py::class_(m, "TextDetector") .def(py::init([](const char *model_path, const char *device_name, int device_id) { return std::make_unique(model_path, device_name, device_id); })) .def("__call__", &PyTextDetector::Apply); } class PythonTextDetectorRegisterer { public: PythonTextDetectorRegisterer() { gPythonBindings().emplace("text_detector", register_python_text_detector); } }; static PythonTextDetectorRegisterer python_text_detector_registerer; } // namespace mmdeploy