Switch to DNN face detection
Haar Cascades can still be used by passing the "--haar-cascade" option.
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cvdata/deploy.prototxt
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1790
cvdata/deploy.prototxt
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cvdata/res10_300x300_ssd_iter_140000_fp16.caffemodel
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cvdata/res10_300x300_ssd_iter_140000_fp16.caffemodel
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56
src/cv.cpp
56
src/cv.cpp
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@ -7,13 +7,19 @@
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#include <paths.hpp>
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#include <paths.hpp>
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cv::Ptr<cv::face::Facemark> facemark;
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cv::Ptr<cv::face::Facemark> facemark;
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cv::CascadeClassifier faceDetector;
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cv::CascadeClassifier haarFaceDetector;
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cv::dnn::Net dnnFaceDetector;
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cv::VideoCapture vid;
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cv::VideoCapture vid;
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cv::Mat frame, gray, small;
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cv::Mat frame, gray, small;
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bool useHaar;
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void initCV() {
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void initCV(bool haar) {
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//TODO: switch to DNN face detection
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useHaar = haar;
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faceDetector = cv::CascadeClassifier (resolvePath("cvdata/haarcascade_frontalface_alt2.xml"));
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haarFaceDetector = cv::CascadeClassifier (resolvePath("cvdata/haarcascade_frontalface_alt2.xml"));
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dnnFaceDetector = cv::dnn::readNetFromCaffe(
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resolvePath("cvdata/deploy.prototxt"),
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resolvePath("cvdata/res10_300x300_ssd_iter_140000_fp16.caffemodel") );
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facemark = cv::face::FacemarkLBF::create();
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facemark = cv::face::FacemarkLBF::create();
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facemark->loadModel (resolvePath("cvdata/lbfmodel.yaml"));
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facemark->loadModel (resolvePath("cvdata/lbfmodel.yaml"));
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@ -21,24 +27,56 @@ void initCV() {
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vid = cv::VideoCapture (0);
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vid = cv::VideoCapture (0);
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}
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}
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void dnnFaceDetect(cv::Mat inFrame, std::vector<cv::Rect>* faces) {
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cv::Mat inputBlob = cv::dnn::blobFromImage(inFrame, 1.0f, cv::Size(300, 300), cv::Scalar(104, 177, 123, 0), false, false);
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dnnFaceDetector.setInput(inputBlob, "data");
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cv::Mat output = dnnFaceDetector.forward("detection_out");
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cv::Mat detection(output.size[2], output.size[3], CV_32F, output.ptr<float>());
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for (int i = 0; i < detection.rows; i++) {
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float confidence = detection.at<float>(i, 2);
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if (confidence > 0.75f) {
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int x1 = detection.at<float>(i, 3) * inFrame.cols;
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int y1 = detection.at<float>(i, 4) * inFrame.rows;
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int x2 = detection.at<float>(i, 5) * inFrame.cols;
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int y2 = detection.at<float>(i, 6) * inFrame.rows;
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cv::Point2f pt1(x1, y1);
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cv::Point2f pt2(x2, y2);
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faces->push_back(cv::Rect(pt1, pt2));
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}
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}
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}
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//process image and send controls to graphics
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//process image and send controls to graphics
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void cvFrame() {
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void cvFrame() {
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vid.read(frame);
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vid.read(frame);
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cv::cvtColor (frame, gray, cv::COLOR_BGR2GRAY);
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cv::cvtColor (frame, gray, cv::COLOR_BGR2GRAY);
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//downsample image for face detection, works too slow on full res
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cv::pyrDown (gray, small);
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cv::pyrDown (small, small);
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std::vector<cv::Rect> faces;
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std::vector<cv::Rect> faces;
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faceDetector.detectMultiScale(small, faces);
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if (useHaar) {
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//downsample image for face detection, works too slow on full res
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cv::pyrDown (gray, small);
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cv::pyrDown (small, small);
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haarFaceDetector.detectMultiScale(small, faces);
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} else {
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dnnFaceDetect(frame, &faces);
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}
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//get biggest face
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//get biggest face
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int biggestFace = 0;
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int biggestFace = 0;
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int biggestArea = 0;
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int biggestArea = 0;
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for (int i = 0; i < faces.size(); i++) {
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for (int i = 0; i < faces.size(); i++) {
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//convert face region to full res, because we perform facemark on full res
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//convert face region to full res, because we perform facemark on full res
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faces[i] = cv::Rect (faces[i].x * 4, faces[i].y * 4, faces[i].width * 4, faces[i].height * 4);
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if (useHaar) {
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faces[i] = cv::Rect (faces[i].x * 4, faces[i].y * 4, faces[i].width * 4, faces[i].height * 4);
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}
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int iArea = faces[i].area();
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int iArea = faces[i].area();
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if (iArea > biggestArea) {
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if (iArea > biggestArea) {
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@ -1,7 +1,7 @@
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#ifndef CV_HPP
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#ifndef CV_HPP
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#define CV_HPP
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#define CV_HPP
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void initCV();
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void initCV(bool haar);
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void cvFrame();
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void cvFrame();
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@ -3,8 +3,9 @@
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#include <paths.hpp>
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#include <paths.hpp>
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#include <iostream>
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#include <iostream>
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#include <cstring>
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int main () {
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int main (int argc, char** argv) {
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std::cout << "Facecam2D is starting..." << std::endl;
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std::cout << "Facecam2D is starting..." << std::endl;
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initPrefixes();
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initPrefixes();
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@ -12,7 +13,8 @@ int main () {
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std::cout << "Default asset prefix: " << prefixDefault << std::endl;
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std::cout << "Default asset prefix: " << prefixDefault << std::endl;
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initGraphics();
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initGraphics();
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initCV();
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//TODO: real argument parsing
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initCV(argc > 1 && strcmp(argv[1], "--haar-cascade") == 0);
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while (true) {
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while (true) {
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cvFrame();
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cvFrame();
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