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| #include <MNN/Interpreter.hpp>
#include <MNN/Matrix.h>
#include <MNN/ImageProcess.hpp>
#include <iostream>
#include <opencv2/opencv.hpp>
#include <opencv2/dnn/dnn.hpp>
#include <sys/time.h>
cv::Mat ShowMat(const cv::Mat& src) {
double min;
double max;
cv::minMaxIdx(src, &min, &max);
cv::Mat adjMap;
float scale = 255 / (max - min);
src.convertTo(adjMap, CV_8UC1, scale, -min * scale);
cv::Mat falseColorsMap;
cv::applyColorMap(adjMap, falseColorsMap, cv::COLORMAP_PINK);
return falseColorsMap;
}
int main(int argc, char* argv[]) {
std::string img_file = "/Users/luohanjie/Workspace/Vision/depth_estimation/MiDaS/input/squirrel_iphone_sample3.png";
std::string model_file = "/Users/luohanjie/Workspace/Vision/my_slam/data/models/dpt_swin2_tiny_256/dpt_swin2_tiny_256.mnn";
cv::Mat img = cv::imread(img_file);
if (img.empty()) {
std::cout << "Can not load image: " << img_file << std::endl;
return 0;
}
int width_ori = img.cols;
int height_ori = img.rows;
std::shared_ptr<MNN::Interpreter> net(MNN::Interpreter::createFromFile(model_file.c_str()), MNN::Interpreter::destroy);
if (net == NULL) {
std::cout << "Can not load model: " << model_file << std::endl;
return 0;
}
MNN::ScheduleConfig session_config;
session_config.type = MNN_FORWARD_AUTO;
MNN::Session* session = net->createSession(session_config);
MNN::Tensor* input = net->getSessionInput(session, "input.1");
MNN::Tensor* output = net->getSessionOutput(session, "3335");
std::vector<int> input_dims = input->shape();
int input_n = input_dims[0];
int input_c = input_dims[1];
int input_h = input_dims[2];
int input_w = input_dims[3];
std::cout << "Model input_n: "<<input_n<<", input_c: " << input_c<<", input_h: " << input_h << ", input_w: " << input_w << std::endl;
std::vector<int> output_dims = output->shape();
int output_c = output_dims[0];
int output_h = output_dims[1];
int output_w = output_dims[2];
std::cout << "Model output_c: "<<output_c<<", output_h: " << output_h << ", output_w: " << output_w << std::endl;
float mean = 0.5f;
float std = 0.5f;
cv::Mat img_nchw;
cv::dnn::blobFromImage(img, img_nchw, 1 / (255 * std), cv::Size(input_w, input_h), - mean / std, true);
MNN::Tensor* tensor_nchw = new MNN::Tensor(input, MNN::Tensor::CAFFE);
MNN::Tensor* tensor_depth = new MNN::Tensor(output, MNN::Tensor::CAFFE);
memcpy(tensor_nchw->host<float>(), img_nchw.data, tensor_nchw->size());
input->copyFromHostTensor(tensor_nchw);
net->runSession(session);
output->copyToHostTensor(tensor_depth);
cv::Mat img_depth(output_h, output_w, CV_32FC1);
memcpy(img_depth.data, tensor_depth->host<float>(), tensor_depth->size());
cv::resize(img_depth, img_depth, cv::Size(width_ori, height_ori));
cv::Mat img_show = ShowMat(img_depth);
cv::imshow("img_depth", img_show);
cv::waitKey(0);
delete tensor_nchw;
delete tensor_depth;
return 1;
}
|