ImageRecognition/DoubleTemperatureGuageALGO.cpp

#include "DoubleTemperatureGuageALGO.h"
#define _CRT_SECURE_NO_WARNINGS


using namespace cv;
using namespace std;
using namespace Ort;
void DoubleTemperatureGuageALGO::Init(bool IsCuda)
{
	string model_path = "models/double_temperature_guage.onnx";
	std::wstring widestr = std::wstring(model_path.begin(), model_path.end());
	sessionOptions.SetGraphOptimizationLevel(ORT_ENABLE_BASIC);
	ort_session = new Session(env, widestr.c_str(), sessionOptions);
	size_t numInputNodes = ort_session->GetInputCount();
	size_t numOutputNodes = ort_session->GetOutputCount();
	AllocatorWithDefaultOptions allocator;
	for (int i = 0; i < numInputNodes; i++)
	{
		input_names.push_back(ort_session->GetInputName(i, allocator));
		Ort::TypeInfo input_type_info = ort_session->GetInputTypeInfo(i);
		auto input_tensor_info = input_type_info.GetTensorTypeAndShapeInfo();
		auto input_dims = input_tensor_info.GetShape();
		input_node_dims.push_back(input_dims);
	}
	for (int i = 0; i < numOutputNodes; i++)
	{
		output_names.push_back(ort_session->GetOutputName(i, allocator));
		Ort::TypeInfo output_type_info = ort_session->GetOutputTypeInfo(i);
		auto output_tensor_info = output_type_info.GetTensorTypeAndShapeInfo();
		auto output_dims = output_tensor_info.GetShape();
		output_node_dims.push_back(output_dims);
	}
	this->inpHeight = input_node_dims[0][2];
	this->inpWidth = input_node_dims[0][3];
	this->outHeight = output_node_dims[0][2];
	this->outWidth = output_node_dims[0][3];
}

pair<float, float> DoubleTemperatureGuageALGO::detect(Mat& srcimg,int MaxRange)
{
    METER_RANGE = MaxRange;
	vector<float> input_image_ = { 1, 3, 512, 512 };
	Mat dstimg;
	Size resize_size(input_image_[2], input_image_[3]);
	resize(srcimg, dstimg, resize_size, 0, 0, cv::INTER_LINEAR);
	int channels = dstimg.channels();
	input_image_.resize((this->inpWidth * this->inpHeight * dstimg.channels()));

	for (int c = 0; c < channels; c++)
	{
		for (int i = 0; i < this->inpHeight; i++)
		{
			for (int j = 0; j < this->inpWidth; j++)
			{
				float pix = dstimg.ptr<uchar>(i)[j * 3 + 2 - c];
				input_image_[(c * this->inpHeight * this->inpWidth + i * this->inpWidth + j)] = (pix / 255.0 - mean[c]) / stds[c];
			}
		}
	}

	array<int64_t, 4> input_shape_{ 1, 3, this->inpHeight, this->inpWidth };
	auto allocator_info = MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeCPU);
	Value input_tensor_ = Value::CreateTensor<float>(allocator_info, input_image_.data(), input_image_.size(), input_shape_.data(), input_shape_.size());

	// 开始推理
	vector<Value> ort_outputs = ort_session->Run(RunOptions{ nullptr }, &input_names[0], &input_tensor_, 1, output_names.data(), output_names.size());
	float* pred = ort_outputs[0].GetTensorMutableData<float>();
	Mat result(outHeight, outWidth, CV_32FC1, pred);
	result = 5 - result;
	result *= 255;
	result.convertTo(result, CV_8UC1);
	return get_meter_reader(creat_line_image(result, 230, 160));
}

Mat DoubleTemperatureGuageALGO::creat_line_image(const Mat& circle, int Radius, int RingStride)
{
	Mat rectangle;
	float theta;
	int rho;

	rectangle = Mat::zeros(Size(Radius * pi * 2, RingStride), CV_8UC1);
	int nl = rectangle.rows;   // number of lines					
	int nc = rectangle.cols * rectangle.channels();   // total number of elements per line
	for (int j = 0; j < nl; j++) {
		// get the address of row j
		uchar* data = rectangle.ptr<uchar>(j);
		for (int i = 0; i < nc; i++) {
			theta = pi * 2.0 / LINE_WIDTH * float(i + 1);
			rho = (Radius - j - 1);
			int position_y = (float)circle_center[0] + rho * (float)std::cos(theta) + 0.5;
			int position_x = (float)circle_center[1] - rho * (float)std::sin(theta) + 0.5;
			data[i] = circle.at<uchar>(position_y, position_x);
		}
	}
	return rectangle;
}

//像素值提取及累加
pair<float,float> DoubleTemperatureGuageALGO::get_meter_reader(const Mat& image)
{
	Mat histogram = Mat::zeros(Size(256, 1), CV_8UC1);
	int rows = LINE_HEIGH;  	 //输入图像的行数
	int cols = LINE_WIDTH; 		 //输入图像的列数
	int first_scale_num = 0;
	int second_scale_num = 0;
	int first_pointer_num = 0;
	int second_pointer_num = 0;
	int sum_horsum = 0;

	vector<int>num1;
	vector<int>num2;
	vector<int>num3;
	for (int c = 0; c < 1445; c++)
	{
		int versum = 0;
		for (int r = 0; r < rows; r++)
		{
			int index = int(image.at<uchar>(r, c));	//获取每个点的像素值
			versum += index;
		}
		if (versum != 0)
		{
			sum_horsum += versum;
			num1.push_back(sum_horsum);
		}
		if (versum == 0)
		{
			int num2_maxValue = 0;
			for (auto v : num1)
			{
				if (num2_maxValue < v) num2_maxValue = v;
			}
			if (num2_maxValue != 0)
			{
				num2.push_back(num2_maxValue);
			}
			sum_horsum = 0;
			vector<int>().swap(num1);
		}
	}

	//计算表盘读数
	//first pointer
	int first_maxPosition = max_element(num2.begin(), num2.end()) - num2.begin();
	auto iter = num2.erase(num2.begin() + first_maxPosition);
	//second pointer
	num3 = num2;
	int num3_maxValue = 0;
	for (auto v : num3)
	{
		if (num3_maxValue < v)
		{
			num3_maxValue = v;
		}
	}

	//计算指针刻度值
	int second_maxPosition = max_element(num2.begin(), num2.end()) - num2.begin();
	float default_value = 0;  //red pointer
	float read_value = 0;
	first_scale_num = num2.size();
	second_scale_num = num2.size();
	first_pointer_num = first_maxPosition;
	second_pointer_num = second_maxPosition;
	float first_result_ratio = (1.0 * first_pointer_num / first_scale_num);
	float second_result_ratio = (1.0 * second_pointer_num / second_scale_num);
	float first_result_value = (first_result_ratio * METER_RANGE);
	float second_result_value = (second_result_ratio * METER_RANGE);

	//compare two pointers
	default_value = first_result_value > second_result_value ? first_result_value : second_result_value;
	read_value = second_result_value < first_result_value ? second_result_value : first_result_value;

	cout << "scale_num:" << first_scale_num << "  pointer_num:" << first_pointer_num << "  result_ratio:" << first_result_ratio << "  result_value:" << first_result_value << endl;
	cout << "scale_num:" << second_scale_num << "  pointer_num:" << second_pointer_num << "  result_ratio:" << second_result_ratio << "  result_value:" << second_result_value << endl;
	if (read_value>4)
	{
		read_value -= 4;

	}
	if (default_value != 0)
	{
		//default_value += 4;
	}
	cout << "读数：" << read_value << " 预设值：" << default_value << endl;
	return pair<float,float>( read_value, default_value);
}