mmdeploy/csrc/apis/python/segmentor.cpp

65 lines
1.9 KiB
C++

// Copyright (c) OpenMMLab. All rights reserved.
#include "segmentor.h"
#include "common.h"
namespace mmdeploy {
class PySegmentor {
public:
PySegmentor(const char *model_path, const char *device_name, int device_id) {
auto status = mmdeploy_segmentor_create_by_path(model_path, device_name, device_id, &handle_);
if (status != MM_SUCCESS) {
throw std::runtime_error("failed to create segmentor");
}
}
~PySegmentor() {
mmdeploy_segmentor_destroy(handle_);
handle_ = {};
}
std::vector<py::array_t<int>> Apply(const std::vector<PyImage> &imgs) {
std::vector<mm_mat_t> mats;
mats.reserve(imgs.size());
for (const auto &img : imgs) {
auto mat = GetMat(img);
mats.push_back(mat);
}
mm_segment_t *segm{};
auto status = mmdeploy_segmentor_apply(handle_, mats.data(), (int)mats.size(), &segm);
if (status != MM_SUCCESS) {
throw std::runtime_error("failed to apply segmentor, code: " + std::to_string(status));
}
auto output = std::vector<py::array_t<int>>{};
output.reserve(mats.size());
for (int i = 0; i < mats.size(); ++i) {
auto mask = py::array_t<int>({segm[i].height, segm[i].width});
memcpy(mask.mutable_data(), segm[i].mask, mask.nbytes());
output.push_back(std::move(mask));
}
mmdeploy_segmentor_release_result(segm, (int)mats.size());
return output;
}
private:
mm_handle_t handle_{};
};
static void register_python_segmentor(py::module &m) {
py::class_<PySegmentor>(m, "Segmentor")
.def(py::init([](const char *model_path, const char *device_name, int device_id) {
return std::make_unique<PySegmentor>(model_path, device_name, device_id);
}))
.def("__call__", &PySegmentor::Apply);
}
class PythonSegmentorRegisterer {
public:
PythonSegmentorRegisterer() { gPythonBindings().emplace("segmentor", register_python_segmentor); }
};
static PythonSegmentorRegisterer python_segmentor_registerer;
} // namespace mmdeploy