轻量级PP-HumanSeg lite人像分割模型NCNN C++部署代码和模型

#include "HumanSeg.h" HumanSeg::HumanSeg(const std::string param_path, const std::string bin_path, std::vector<int> input_shape) :param_path(param_path), bin_path(bin_path), input_shape(input_shape) { net.load_param(param_path.c_str()); net.load_model(bin_path.c_str()); } HumanSeg::~HumanSeg() { net.clear(); } cv::Mat HumanSeg::normalize(cv::Mat& image) { std::vector<cv::Mat> channels, normalized_image; cv::split(image, channels); cv::Mat r, g, b; b = channels.at(0); g = channels.at(1); r = channels.at(2); b = (b / 255. - 0.5) / 0.5; g = (g / 255. - 0.5) / 0.5; r = (r / 255. - 0.5) / 0.5; normalized_image.push_back(r); normalized_image.push_back(g); normalized_image.push_back(b); cv::Mat out = cv::Mat(image.rows, image.cols, CV_32F); cv::merge(normalized_image, out); return out; } cv::Mat HumanSeg::predict_image(cv::Mat& image) { cv::Mat rgbImage; cv::cvtColor(image, rgbImage, cv::COLOR_BGR2RGB); ncnn::Mat in = ncnn::Mat::from_pixels_resize(rgbImage.data, ncnn::Mat::PIXEL_RGB, image.cols, image.rows, input_shape[3], input_shape[2]); in.substract_mean_normalize(mean_vals, norm_vals); ncnn::Extractor ex = net.create_extractor(); ex.input("x", in); ncnn::Mat out; ex.extract("bilinear_interp_v2_13.tmp_0", out); cv::Mat mask(out.h, out.w, CV_8UC1); const float* maskmap0 = out.channel(0); const float* maskmap1 = out.channel(1); for (int i{ 0 }; i < out.h; i++) { for (int j{ 0 }; j < out.w; ++j) { mask.at<uchar>(i, j) = maskmap1[i * out.w + j] > maskmap0[i * out.w + j] ? 255 : 0; } } cv::resize(mask, mask, cv::Size(image.cols, image.rows), 0, 0); cv::Mat segFrame; cv::bitwise_and(image, image, segFrame, mask = mask); return segFrame; } void HumanSeg::predict_image(const std::string& src_image_path, const std::string& dst_path) { cv::Mat image = cv::imread(src_image_path); cv::Mat segFrame = predict_image(image); cv::imwrite(dst_path, segFrame); } void HumanSeg::predict_camera() { cv::Mat frame; cv::VideoCapture cap; int deviceID{ 0 }; int apiID{ cv::CAP_ANY }; cap.open(deviceID, apiID); if (!cap.isOpened()) { std::cout << "Error, cannot open camera!" << std::endl; return; } //--- GRAB AND WRITE LOOP std::cout << "Start grabbing" << std::endl << "Press any key to terminate" << std::endl; int count{ 0 }; clock_t start{ clock() }, end{0}; double fps{ 0 }; for (;;) { // wait for a new frame from camera and store it into 'frame' cap.read(frame); // check if we succeeded if (frame.empty()) { std::cout << "ERROR! blank frame grabbed" << std::endl; break; } cv::Mat segFrame = predict_image(frame); // fps ++count; end = clock(); fps = count / (float(end - start) / CLOCKS_PER_SEC); if (count >= 50) { count = 0; //防止计数溢出 start = clock(); } std::cout << "FPS: " << fps << " Seg Image Number: " << count << " time consume:" << (float(end - start) / CLOCKS_PER_SEC) << std::endl; //设置绘制文本的相关参数 std::string text{ std::to_string(fps) }; int font_face = cv::FONT_HERSHEY_COMPLEX; double font_scale = 1; int thickness = 2; int baseline; cv::Size text_size = cv::getTextSize(text, font_face, font_scale, thickness, &baseline); //将文本框居中绘制 cv::Point origin; origin.x = 20; origin.y = 20; cv::putText(segFrame, text, origin, font_face, font_scale, cv::Scalar(0, 255, 255), thickness, 8, 0); // show live and wait for a key with timeout long enough to show images imshow("Live", segFrame); if (cv::waitKey(5) >= 0) break; } cap.release(); cv::destroyWindow("Live"); return; }