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| #include "net.h"
#include "mat.h"
#include "cpu.h"
#include <opencv2/opencv.hpp>
#include <sys/time.h>
int main(int argc, char* argv[]) {
std::string img_file = "/Users/luohanjie/Workspace/Vision/depth_estimation/MiDaS/input/squirrel_iphone_sample3.png";
std::string param_file = "/Users/luohanjie/Workspace/Vision/my_slam/data/models/midas_v21_small-int8.param";
std::string model_file = "/Users/luohanjie/Workspace/Vision/my_slam/data/models/midas_v21_small-int8.bin";
int target_size = 256;
float scale = 0.33333f;
cv::Mat img = cv::imread(img_file);
cv::resize(img, img, cv::Size(), scale, scale);
int img_width = img.cols;
int img_height = img.rows;
ncnn::Net net;
ncnn::set_cpu_powersave(0);
ncnn::set_omp_num_threads(ncnn::get_cpu_count());
net.opt = ncnn::Option();
net.opt.use_vulkan_compute = false;
net.opt.num_threads = ncnn::get_cpu_count();
net.load_param(param_file.c_str());
net.load_model(model_file.c_str());
ncnn::Mat img_in = ncnn::Mat::from_pixels_resize(img.data, ncnn::Mat::PIXEL_BGR2RGB, img_width, img_height, target_size, target_size);
const float mean_vals[3] = {123.675f, 116.28f, 103.53f};
const float norm_vals[3] = {0.01712475383f, 0.0175070028f, 0.01742919389f};
img_in.substract_mean_normalize(mean_vals, norm_vals);
ncnn::Extractor ex = net.create_extractor();
ex.set_light_mode(true);
ncnn::Mat img_out;
ex.input("input.1", img_in);
ex.extract("649", img_out);
ncnn::resize_bilinear(img_out, img_out, img_width, img_height);
cv::Mat cv_out(img_out.h, img_out.w, CV_8UC1);
img_out.to_pixels(cv_out.data, ncnn::Mat::PIXEL_GRAY);
cv::imshow("cv_out", cv_out);
cv::waitKey(0);
return 0;
}
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