mmdeploy/csrc/apis/c/rotated_detector.cpp

143 lines
4.4 KiB
C++

// Copyright (c) OpenMMLab. All rights reserved.
#include "rotated_detector.h"
#include <numeric>
#include "codebase/mmrotate/mmrotate.h"
#include "core/device.h"
#include "core/graph.h"
#include "core/mat.h"
#include "core/utils/formatter.h"
#include "handle.h"
using namespace std;
using namespace mmdeploy;
namespace {
Value& config_template() {
// clang-format off
static Value v{
{
"pipeline", {
{"input", {"image"}},
{"output", {"det"}},
{
"tasks",{
{
{"name", "mmrotate"},
{"type", "Inference"},
{"params", {{"model", "TBD"}}},
{"input", {"image"}},
{"output", {"det"}}
}
}
}
}
}
};
// clang-format on
return v;
}
template <class ModelType>
int mmdeploy_rotated_detector_create_impl(ModelType&& m, const char* device_name, int device_id,
mm_handle_t* handle) {
try {
auto value = config_template();
value["pipeline"]["tasks"][0]["params"]["model"] = std::forward<ModelType>(m);
auto pose_estimator = std::make_unique<Handle>(device_name, device_id, std::move(value));
*handle = pose_estimator.release();
return MM_SUCCESS;
} catch (const std::exception& e) {
MMDEPLOY_ERROR("exception caught: {}", e.what());
} catch (...) {
MMDEPLOY_ERROR("unknown exception caught");
}
return MM_E_FAIL;
}
} // namespace
int mmdeploy_rotated_detector_create(mm_model_t model, const char* device_name, int device_id,
mm_handle_t* handle) {
return mmdeploy_rotated_detector_create_impl(*static_cast<Model*>(model), device_name, device_id,
handle);
}
int mmdeploy_rotated_detector_create_by_path(const char* model_path, const char* device_name,
int device_id, mm_handle_t* handle) {
return mmdeploy_rotated_detector_create_impl(model_path, device_name, device_id, handle);
}
int mmdeploy_rotated_detector_apply(mm_handle_t handle, const mm_mat_t* mats, int mat_count,
mm_rotated_detect_t** results, int** result_count) {
if (handle == nullptr || mats == nullptr || mat_count == 0 || results == nullptr ||
result_count == nullptr) {
return MM_E_INVALID_ARG;
}
try {
auto detector = static_cast<Handle*>(handle);
Value input{Value::kArray};
for (int i = 0; i < mat_count; ++i) {
mmdeploy::Mat _mat{mats[i].height, mats[i].width, PixelFormat(mats[i].format),
DataType(mats[i].type), mats[i].data, Device{"cpu"}};
input.front().push_back({{"ori_img", _mat}});
}
auto output = detector->Run(std::move(input)).value().front();
auto detector_outputs = from_value<vector<mmrotate::RotatedDetectorOutput>>(output);
vector<int> _result_count;
_result_count.reserve(mat_count);
for (const auto& det_output : detector_outputs) {
_result_count.push_back((int)det_output.detections.size());
}
auto total = std::accumulate(_result_count.begin(), _result_count.end(), 0);
std::unique_ptr<int[]> result_count_data(new int[_result_count.size()]{});
std::copy(_result_count.begin(), _result_count.end(), result_count_data.get());
std::unique_ptr<mm_rotated_detect_t[]> result_data(new mm_rotated_detect_t[total]{});
auto result_ptr = result_data.get();
for (const auto& det_output : detector_outputs) {
for (const auto& detection : det_output.detections) {
result_ptr->label_id = detection.label_id;
result_ptr->score = detection.score;
const auto& rbbox = detection.rbbox;
for (int i = 0; i < 5; i++) {
result_ptr->rbbox[i] = rbbox[i];
}
++result_ptr;
}
}
*result_count = result_count_data.release();
*results = result_data.release();
return MM_SUCCESS;
} catch (const std::exception& e) {
MMDEPLOY_ERROR("exception caught: {}", e.what());
} catch (...) {
MMDEPLOY_ERROR("unknown exception caught");
}
return MM_E_FAIL;
}
void mmdeploy_rotated_detector_release_result(mm_rotated_detect_t* results,
const int* result_count) {
delete[] results;
delete[] result_count;
}
void mmdeploy_rotated_detector_destroy(mm_handle_t handle) { delete static_cast<Handle*>(handle); }