// Copyright (c) OpenMMLab. All rights reserved. #include "detector.h" #include #include "archive/value_archive.h" #include "codebase/mmdet/mmdet.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", "mmdetection"}, {"type", "Inference"}, {"params", {{"model", "TBD"}}}, {"input", {"image"}}, {"output", {"det"}} } } } } } }; // clang-format on return v; } template int mmdeploy_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(m); auto detector = std::make_unique(device_name, device_id, std::move(value)); *handle = detector.release(); return MM_SUCCESS; } catch (const std::exception& e) { ERROR("exception caught: {}", e.what()); } catch (...) { ERROR("unknown exception caught"); } return MM_E_FAIL; } } // namespace MM_SDK_API int mmdeploy_detector_create(mm_model_t model, const char* device_name, int device_id, mm_handle_t* handle) { return mmdeploy_detector_create_impl(*static_cast(model), device_name, device_id, handle); } MM_SDK_API int mmdeploy_detector_create_by_path(const char* model_path, const char* device_name, int device_id, mm_handle_t* handle) { return mmdeploy_detector_create_impl(model_path, device_name, device_id, handle); } MM_SDK_API int mmdeploy_detector_apply(mm_handle_t handle, const mm_mat_t* mats, int mat_count, mm_detect_t** results, int** result_count) { if (handle == nullptr || mats == nullptr || mat_count == 0) { return MM_E_INVALID_ARG; } try { auto detector = static_cast(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->type), mats[i].data, Device{"cpu"}}; input.front().push_back({{"ori_img", _mat}}); } auto output = detector->Run(std::move(input)).value().front(); ERROR("output: {}", output); auto detector_outputs = from_value>(output); vector _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 result_count_data(new int[_result_count.size()]{}); std::copy(_result_count.begin(), _result_count.end(), result_count_data.get()); std::unique_ptr result_data(new mm_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& bbox = detection.bbox; result_ptr->bbox = {(int)bbox[0], (int)bbox[1], (int)bbox[2], (int)bbox[3]}; ++result_ptr; } } *result_count = result_count_data.release(); *results = result_data.release(); return MM_SUCCESS; } catch (const std::exception& e) { ERROR("exception caught: {}", e.what()); } catch (...) { ERROR("unknown exception caught"); } return MM_E_FAIL; } MM_SDK_API void mmdeploy_detector_release_result(mm_detect_t* results, const int* result_count, int count) { delete[] results; delete[] result_count; } MM_SDK_API void mmdeploy_detector_destroy(mm_handle_t handle) { if (handle != nullptr) { auto detector = static_cast(handle); delete detector; } }