Add example file

src/videostab.cpp

@@ -0,0 +1,258 @@
+#include <opencv2/opencv.hpp>
+#include <iostream>
+#include <cassert>
+#include <cmath>
+#include <fstream>
+
+using namespace std;
+using namespace cv;
+
+// This video stablisation smooths the global trajectory using a sliding average window
+
+const int SMOOTHING_RADIUS = 30; // In frames. The larger the more stable the video, but less reactive to sudden panning
+const int HORIZONTAL_BORDER_CROP = 20; // In pixels. Crops the border to reduce the black borders from stabilisation being too noticeable.
+
+// 1. Get previous to current frame transformation (dx, dy, da) for all frames
+// 2. Accumulate the transformations to get the image trajectory
+// 3. Smooth out the trajectory using an averaging window
+// 4. Generate new set of previous to current transform, such that the trajectory ends up being the same as the smoothed trajectory
+// 5. Apply the new transformation to the video
+
+struct TransformParam
+{
+    TransformParam() {}
+    TransformParam(double _dx, double _dy, double _da) {
+        dx = _dx;
+        dy = _dy;
+        da = _da;
+    }
+
+    double dx;
+    double dy;
+    double da; // angle
+};
+
+struct Trajectory
+{
+    Trajectory() {}
+    Trajectory(double _x, double _y, double _a) {
+        x = _x;
+        y = _y;
+        a = _a;
+    }
+
+    double x;
+    double y;
+    double a; // angle
+};
+
+int main(int argc, char **argv)
+{
+    if(argc < 2) {
+        cout << "./VideoStab [video.avi]" << endl;
+        return 0;
+    }
+
+    // For further analysis
+    ofstream out_transform("prev_to_cur_transformation.txt");
+    ofstream out_trajectory("trajectory.txt");
+    ofstream out_smoothed_trajectory("smoothed_trajectory.txt");
+    ofstream out_new_transform("new_prev_to_cur_transformation.txt");
+
+    VideoCapture cap(argv[1]);
+    assert(cap.isOpened());
+
+    Mat cur, cur_grey;
+    Mat prev, prev_grey;
+
+    cap >> prev;
+    cvtColor(prev, prev_grey, COLOR_BGR2GRAY);
+
+    // Step 1 - Get previous to current frame transformation (dx, dy, da) for all frames
+    vector <TransformParam> prev_to_cur_transform; // previous to current
+
+    int k=1;
+    int max_frames = cap.get(CV_CAP_PROP_FRAME_COUNT);
+    Mat last_T;
+
+    while(true) {
+        cap >> cur;
+
+        if(cur.data == NULL) {
+            break;
+        }
+
+        cvtColor(cur, cur_grey, COLOR_BGR2GRAY);
+
+        // vector from prev to cur
+        vector <Point2f> prev_corner, cur_corner;
+        vector <Point2f> prev_corner2, cur_corner2;
+        vector <uchar> status;
+        vector <float> err;
+
+        goodFeaturesToTrack(prev_grey, prev_corner, 200, 0.01, 30);
+        calcOpticalFlowPyrLK(prev_grey, cur_grey, prev_corner, cur_corner, status, err);
+
+        // weed out bad matches
+        for(size_t i=0; i < status.size(); i++) {
+            if(status[i]) {
+                prev_corner2.push_back(prev_corner[i]);
+                cur_corner2.push_back(cur_corner[i]);
+            }
+        }
+
+        // translation + rotation only
+        Mat T = estimateRigidTransform(prev_corner2, cur_corner2, false); // false = rigid transform, no scaling/shearing
+
+        // in rare cases no transform is found. We'll just use the last known good transform.
+        if(T.data == NULL) {
+            last_T.copyTo(T);
+        }
+
+        T.copyTo(last_T);
+
+        // decompose T
+        double dx = T.at<double>(0,2);
+        double dy = T.at<double>(1,2);
+        double da = atan2(T.at<double>(1,0), T.at<double>(0,0));
+
+        prev_to_cur_transform.push_back(TransformParam(dx, dy, da));
+
+        out_transform << k << " " << dx << " " << dy << " " << da << endl;
+
+        cur.copyTo(prev);
+        cur_grey.copyTo(prev_grey);
+
+        cout << "Frame: " << k << "/" << max_frames << " - good optical flow: " << prev_corner2.size() << endl;
+        k++;
+    }
+
+    // Step 2 - Accumulate the transformations to get the image trajectory
+
+    // Accumulated frame to frame transform
+    double a = 0;
+    double x = 0;
+    double y = 0;
+
+    vector <Trajectory> trajectory; // trajectory at all frames
+
+    for(size_t i=0; i < prev_to_cur_transform.size(); i++) {
+        x += prev_to_cur_transform[i].dx;
+        y += prev_to_cur_transform[i].dy;
+        a += prev_to_cur_transform[i].da;
+
+        trajectory.push_back(Trajectory(x,y,a));
+
+        out_trajectory << (i+1) << " " << x << " " << y << " " << a << endl;
+    }
+
+    // Step 3 - Smooth out the trajectory using an averaging window
+    vector <Trajectory> smoothed_trajectory; // trajectory at all frames
+
+    for(size_t i=0; i < trajectory.size(); i++) {
+        double sum_x = 0;
+        double sum_y = 0;
+        double sum_a = 0;
+        int count = 0;
+
+        for(int j=-SMOOTHING_RADIUS; j <= SMOOTHING_RADIUS; j++) {
+            if(i+j >= 0 && i+j < trajectory.size()) {
+                sum_x += trajectory[i+j].x;
+                sum_y += trajectory[i+j].y;
+                sum_a += trajectory[i+j].a;
+
+                count++;
+            }
+        }
+
+        double avg_a = sum_a / count;
+        double avg_x = sum_x / count;
+        double avg_y = sum_y / count;
+
+        smoothed_trajectory.push_back(Trajectory(avg_x, avg_y, avg_a));
+
+        out_smoothed_trajectory << (i+1) << " " << avg_x << " " << avg_y << " " << avg_a << endl;
+    }
+
+    // Step 4 - Generate new set of previous to current transform, such that the trajectory ends up being the same as the smoothed trajectory
+    vector <TransformParam> new_prev_to_cur_transform;
+
+    // Accumulated frame to frame transform
+    a = 0;
+    x = 0;
+    y = 0;
+
+    for(size_t i=0; i < prev_to_cur_transform.size(); i++) {
+        x += prev_to_cur_transform[i].dx;
+        y += prev_to_cur_transform[i].dy;
+        a += prev_to_cur_transform[i].da;
+
+        // target - current
+        double diff_x = smoothed_trajectory[i].x - x;
+        double diff_y = smoothed_trajectory[i].y - y;
+        double diff_a = smoothed_trajectory[i].a - a;
+
+        double dx = prev_to_cur_transform[i].dx + diff_x;
+        double dy = prev_to_cur_transform[i].dy + diff_y;
+        double da = prev_to_cur_transform[i].da + diff_a;
+
+        new_prev_to_cur_transform.push_back(TransformParam(dx, dy, da));
+
+        out_new_transform << (i+1) << " " << dx << " " << dy << " " << da << endl;
+    }
+
+    // Step 5 - Apply the new transformation to the video
+    cap.set(CV_CAP_PROP_POS_FRAMES, 0);
+    Mat T(2,3,CV_64F);
+
+    int vert_border = HORIZONTAL_BORDER_CROP * prev.rows / prev.cols; // get the aspect ratio correct
+
+    k=0;
+    while(k < max_frames-1) { // don't process the very last frame, no valid transform
+        cap >> cur;
+
+        if(cur.data == NULL) {
+            break;
+        }
+
+        T.at<double>(0,0) = cos(new_prev_to_cur_transform[k].da);
+        T.at<double>(0,1) = -sin(new_prev_to_cur_transform[k].da);
+        T.at<double>(1,0) = sin(new_prev_to_cur_transform[k].da);
+        T.at<double>(1,1) = cos(new_prev_to_cur_transform[k].da);
+
+        T.at<double>(0,2) = new_prev_to_cur_transform[k].dx;
+        T.at<double>(1,2) = new_prev_to_cur_transform[k].dy;
+
+        Mat cur2;
+
+        warpAffine(cur, cur2, T, cur.size());
+
+        cur2 = cur2(Range(vert_border, cur2.rows-vert_border), Range(HORIZONTAL_BORDER_CROP, cur2.cols-HORIZONTAL_BORDER_CROP));
+
+        // Resize cur2 back to cur size, for better side by side comparison
+        resize(cur2, cur2, cur.size());
+
+        // Now draw the original and stablised side by side for coolness
+        Mat canvas = Mat::zeros(cur.rows, cur.cols*2+10, cur.type());
+
+        cur.copyTo(canvas(Range::all(), Range(0, cur2.cols)));
+        cur2.copyTo(canvas(Range::all(), Range(cur2.cols+10, cur2.cols*2+10)));
+
+        // If too big to fit on the screen, then scale it down by 2, hopefully it'll fit :)
+        if(canvas.cols > 1920) {
+            resize(canvas, canvas, Size(canvas.cols/2, canvas.rows/2));
+        }
+
+        imshow("before and after", canvas);
+
+        //char str[256];
+        //sprintf(str, "images/%08d.jpg", k);
+        //imwrite(str, canvas);
+
+        waitKey(20);
+
+        k++;
+    }
+
+    return 0;
+}