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+// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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+//
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+// Licensed under the Apache License, Version 2.0 (the "License");
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+// you may not use this file except in compliance with the License.
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+// You may obtain a copy of the License at
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+//
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+// http://www.apache.org/licenses/LICENSE-2.0
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+//
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+// Unless required by applicable law or agreed to in writing, software
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+// distributed under the License is distributed on an "AS IS" BASIS,
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+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+// See the License for the specific language governing permissions and
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+// limitations under the License.
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+
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+#include <gflags/gflags.h>
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+#include <string>
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+#include <vector>
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+
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+#include "model_deploy/common/include/paddle_deploy.h"
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+
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+PaddleDeploy::Model* model;
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+
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+extern "C" __declspec(dllexport) void InitModel(const char* model_type, const char* model_filename, const char* params_filename, const char* cfg_file)
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+{
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+ bool use_gpu = false;
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+ int gpu_id = 0;
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+
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+ // create model
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+ model = PaddleDeploy::CreateModel(model_type); //FLAGS_model_type
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+
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+ // model init
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+ model->Init(cfg_file);
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+
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+ // inference engine init
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+ PaddleDeploy::PaddleEngineConfig engine_config;
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+ engine_config.model_filename = model_filename;
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+ engine_config.params_filename = params_filename;
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+ engine_config.use_gpu = use_gpu;
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+ engine_config.gpu_id = gpu_id;
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+ bool init = model->PaddleEngineInit(engine_config);
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+ if (init)
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+ {
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+ std::cout << "init model success" << std::endl;
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+ }
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+}
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+/*
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+* img: input for predicting.
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+*
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+* nWidth: width of img.
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+*
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+* nHeight: height of img.
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+*
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+* nChannel: channel of img.
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+*
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+* output: result of pridict ,include category_id£¬score£¬coordinate¡£
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+*
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+* nBoxesNum£º number of box
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+*
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+* LabelList: label list of result
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+*/
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+extern "C" __declspec(dllexport) void ModelPredict(const unsigned char* img, int nWidth, int nHeight,int nChannel, float* output, int* nBoxesNum, char* LabelList)
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+{
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+ // prepare data
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+ std::vector<cv::Mat> imgs;
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+
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+ int nType = 0;
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+ if (nChannel==1)
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+ {
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+ nType = CV_8UC1;
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+ }
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+ else if (nChannel == 2)
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+ {
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+ nType = CV_8UC2;
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+ }
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+ else if (nChannel == 3)
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+ {
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+ nType = CV_8UC3;
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+ }
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+ else if (nChannel == 4)
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+ {
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+ nType = CV_8UC4;
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+ }
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+
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+ cv::Mat input = cv::Mat::zeros(cv::Size(nWidth, nHeight), nType);
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+ memcpy(input.data, img, nHeight * nWidth * nChannel * sizeof(uchar));
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+ //cv::imwrite("./1.png", input);
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+ imgs.push_back(std::move(input));
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+
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+ // predict
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+ std::vector<PaddleDeploy::Result> results;
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+ bool pre = model->Predict(imgs, &results, 1);
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+ if (pre)
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+ {
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+ std::cout << "model predict success" << std::endl;
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+ }
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+ nBoxesNum[0] = results.size();
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+ std::string label ="";
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+ for (int num = 0; num < results.size(); num++)
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+ {
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+ //std::cout << "res: " << results[num] << std::endl;
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+ for (int i = 0; i < results[num].det_result->boxes.size(); i++)
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+ {
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+ //std::cout << "category: " << results[num].det_result->boxes[i].category << std::endl;
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+ label = label + results[num].det_result->boxes[i].category+ " ";
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+ // labelindex
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+ output[num * 6 + 0] = results[num].det_result->boxes[i].category_id;
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+ // score
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+ output[num * 6 + 1] = results[num].det_result->boxes[i].score;
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+ //// box
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+ output[num * 6 + 2] = results[num].det_result->boxes[i].coordinate[0];
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+ output[num * 6 + 3] = results[num].det_result->boxes[i].coordinate[1];
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+ output[num * 6 + 4] = results[num].det_result->boxes[i].coordinate[2];
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+ output[num * 6 + 5] = results[num].det_result->boxes[i].coordinate[3];
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+ }
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+ }
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+ memcpy(LabelList, label.c_str(), strlen(label.c_str()));
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+}
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+
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+extern "C" __declspec(dllexport) void DestructModel()
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+{
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+ delete model;
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+ std::cout << "destruct model success" << std::endl;
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+
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+}
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+
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+//DEFINE_string(model_filename, "", "Path of det inference model");
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+//DEFINE_string(params_filename, "", "Path of det inference params");
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+//DEFINE_string(cfg_file, "", "Path of yaml file");
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+//DEFINE_string(model_type, "", "model type");
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+//DEFINE_string(image, "", "Path of test image file");
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+//DEFINE_bool(use_gpu, false, "Infering with GPU or CPU");
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+//DEFINE_int32(gpu_id, 0, "GPU card id");
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+//
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+//int main(int argc, char** argv) {
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+// // Parsing command-line
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+// google::ParseCommandLineFlags(&argc, &argv, true);
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+//
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+// // create model
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+// PaddleDeploy::Model* model = PaddleDeploy::CreateModel(FLAGS_model_type);
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+//
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+// // model init
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+// model->Init(FLAGS_cfg_file);
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+//
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+// // inference engine init
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+// PaddleDeploy::PaddleEngineConfig engine_config;
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+// engine_config.model_filename = FLAGS_model_filename;
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+// engine_config.params_filename = FLAGS_params_filename;
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+// engine_config.use_gpu = FLAGS_use_gpu;
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+// engine_config.gpu_id = FLAGS_gpu_id;
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+// model->PaddleEngineInit(engine_config);
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+//
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+// // prepare data
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+// std::vector<cv::Mat> imgs;
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+// imgs.push_back(std::move(cv::imread(FLAGS_image)));
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+//
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+// // predict
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+// std::vector<PaddleDeploy::Result> results;
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+// model->Predict(imgs, &results, 1);
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+//
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+// std::cout << results[0] << std::endl;
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+// delete model;
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+// return 0;
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+//}
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yzl19940819
