1、onnx turn ncnn

onnx2ncnn.exe BiSeNetV2_sim.onnx BSNs.param NSNs.bin

2、ncnn Reasoning

#include<iostream>
#include<opencv2/opencv.hpp>
#include<net.h>
#include <stdio.h>

int main()
{
	cv::Mat img = cv::imread("../asserts/4.png");
	cv::cvtColor(img,img,cv::COLOR_BGR2RGB);

	ncnn::Net net;
	// Load parameters before loading models 
	net.load_param("../asserts/BSNs.param");
	net.load_model("../asserts/BSNs.bin");
	


	ncnn::Mat input = ncnn::Mat::from_pixels_resize(img.data, ncnn::Mat::PIXEL_RGB, img.cols,img.rows,512,512);

	const float mean_vals[3] = { 0.485f * 255.f, 0.456f * 255.f, 0.406f * 255.f };//123,117,104
	const float norm_vals[3] = { 1 / 0.229f / 255.f, 1 / 0.224f / 255.f, 1 / 0.225f / 255.f };//0.017,0.017,0.017
	input.substract_mean_normalize(mean_vals, norm_vals);

	//std::cout << "data_shape:" << data.d << "," << data.c << "," <&l