#include <iostream>
#include <string>
#include <vector>
#include <opencv2/opencv.hpp>
#include <openvino/openvino.hpp>

const std::string labels_path = "inception_v3_2016_08_28_frozen.labels";
const std::string model_path = "inception_v3_2016_08_28_frozen.xml";
const std::string input_path = "car_1.bmp";
const std::string device_name = "CPU";

int main(int argc, char* argv[]) {

	// ラベルリストを読込み。
	std::vector<std::string> labels;
	FILE* fp = fopen(labels_path.c_str(), "r");
	if (fp == NULL) {
		std::cout << "labels is not exist" << std::endl;
		return -1;
	}
	char buf[256];

	while (fgets(buf, 256, fp) != NULL) {
		if (buf[strlen(buf) - 1] == '\n') {
			buf[strlen(buf) - 1] = '\0';
		}
		labels.push_back(buf);
	}

	//画像ファイルの読み込み
	cv::Mat image = cv::imread(input_path);
	if (image.empty()) {
		std::cout << "cv::imread() failed\n" << std::endl;
		return -1;
	}

	//Coreオブジェクト生成
	ov::Core ie;

	//IRモデル読み込み
	std::shared_ptr<ov::Model> network;
	try{
		network = ie.read_model(model_path);
	}
	catch(...){
		std::cout << "ie.read_model() failed\n" << std::endl;
		return -1;
	}

	//前処理をモデルに組み込み
	ov::preprocess::PrePostProcessor ppp(network);
	ppp.input().preprocess().resize(ov::preprocess::ResizeAlgorithm::RESIZE_LINEAR);
	ppp.input().tensor().set_shape({ 1, (unsigned long long)image.rows, (unsigned long long)image.cols, (unsigned long long)image.channels() });
	ppp.input().tensor().set_layout("NHWC");
	ppp.input().tensor().set_element_type(ov::element::u8);
	network = ppp.build();

	//モデルをデバイスに送信してコンパイル
	ov::CompiledModel compiled_model = ie.compile_model(network, device_name);

	//推論要求を送るため infer_requestオブジェクトの生成
	ov::InferRequest infer_request = compiled_model.create_infer_request();

	//推論データをモデルの入力にセット
	ov::Tensor input_tensor = ov::Tensor(ov::element::u8, { 1, (unsigned long long)image.rows, (unsigned long long)image.cols, (unsigned long long)image.channels() }, image.data);
	infer_request.set_input_tensor(input_tensor);

	//推論実行
	infer_request.infer();
	
	//推論結果の取り出し
	const ov::Tensor& output_tensor = infer_request.get_output_tensor();
	float* output = reinterpret_cast<float*>(output_tensor.data());
	ov::Shape output_shappe = output_tensor.get_shape();

	//推論結果の表示
	std::cout << "classid probability label\n------ ------ ------" << std::endl;
	std::vector<int> idx;	
	for (int i = 0; i < output_shappe[1]; i++) {
		idx.push_back(i);
	}

	std::sort(idx.begin(), idx.end(), [output](const int& left, const int& right) { return output[left] > output[right]; });

	for (size_t id = 0; id < 5; ++id) {
		std::cout << idx[id] << ": " << output[idx[id]] * 100 << "% " << ": " << labels[idx[id]] <<  std::endl;
	}
	return 0;
}

CC		=	g++
CFLAGS	=	-std=c++11 
CXFLAGS	=
LDFLAGS	=       -L/opt/intel/openvino/extras/opencv/lib \
                -lopencv_core -lopencv_imgcodecs -lopencv_highgui -lopencv_imgproc -lopencv_videoio -lopencv_video \
		-L/opt/intel/openvino/runtime/lib/intel64 \
		-lopenvino

LIBS	=
INCLUDE	=	-I /opt/intel/openvino/extras/opencv/include \
		-I /opt/intel/openvino/runtime/include/ie \
		-I /opt/intel/openvino/runtime/include

SRC_DIR	=	./
OBJ_DIR	=	./build
SOURCES	=	$(shell ls $(SRC_DIR)/*.cpp)
OBJS	=	$(subst $(SRC_DIR),$(OBJ_DIR), $(SOURCES:.cpp=.o))
TARGET	=	sample
DEPENDS	=	$(OBJS:.o=.d)

all: $(TARGET)

$(TARGET): $(OBJS) $(LIBS)
		$(CC) -o $@ $(OBJS) $(LIBS) $(LDFLAGS)

$(OBJ_DIR)/%.o: $(SRC_DIR)/%.cpp
		@if [ ! -d $(OBJ_DIR) ]; \
			then echo "mkdir -p $(OBJ_DIR)"; mkdir -p $(OBJ_DIR); \
		fi
		$(CC) $(CFLAGS) $(INCLUDE) -O2 -o $@ -c $<

clean:
		$(RM) $(OBJS) $(TARGET) $(DEPENDS)

-include $(DEPENDS)

.PHONY: all clean