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dcdbc638af
@ -60,6 +60,9 @@ static void removeOcclusions(const Mat& flow,
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Mat& confidence) {
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Mat& confidence) {
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const int rows = flow.rows;
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const int rows = flow.rows;
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const int cols = flow.cols;
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const int cols = flow.cols;
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if (!confidence.data) {
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confidence = Mat::zeros(rows, cols, CV_32F);
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}
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for (int r = 0; r < rows; ++r) {
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for (int r = 0; r < rows; ++r) {
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for (int c = 0; c < cols; ++c) {
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for (int c = 0; c < cols; ++c) {
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if (dist(flow.at<Vec2f>(r, c), -flow_inv.at<Vec2f>(r, c)) > occ_thr) {
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if (dist(flow.at<Vec2f>(r, c), -flow_inv.at<Vec2f>(r, c)) > occ_thr) {
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@ -96,20 +99,12 @@ static void wc(const Mat& image, Mat& d, int r0, int c0,
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exp(d, d);
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exp(d, d);
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}
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}
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static void dist(const Mat& m1, const Mat& m2, Mat& result) {
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static void crossBilateralFilter(const Mat& image,
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const int rows = m1.rows;
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const Mat& edge_image,
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const int cols = m1.cols;
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const Mat confidence,
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for (int r = 0; r < rows; ++r) {
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Mat& dst, int d,
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const Vec3b *m1_row = m1.ptr<Vec3b>(r);
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float sigma_color, float sigma_space,
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const Vec3b *m2_row = m2.ptr<Vec3b>(r);
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bool flag=false) {
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float* row = result.ptr<float>(r);
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for (int c = 0; c < cols; ++c) {
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row[c] = dist(m1_row[c], m2_row[c]);
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}
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}
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}
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static void crossBilateralFilter(const Mat& image, const Mat& edge_image, const Mat confidence, Mat& dst, int d, float sigma_color, float sigma_space, bool flag=false) {
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const int rows = image.rows;
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const int rows = image.rows;
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const int cols = image.cols;
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const int cols = image.cols;
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Mat image_extended, edge_image_extended, confidence_extended;
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Mat image_extended, edge_image_extended, confidence_extended;
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@ -121,7 +116,6 @@ static void crossBilateralFilter(const Mat& image, const Mat& edge_image, const
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Mat weights(2*d+1, 2*d+1, CV_32F);
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Mat weights(2*d+1, 2*d+1, CV_32F);
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Mat weighted_sum(2*d+1, 2*d+1, CV_32F);
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Mat weighted_sum(2*d+1, 2*d+1, CV_32F);
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vector<Mat> image_extended_channels;
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vector<Mat> image_extended_channels;
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split(image_extended, image_extended_channels);
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split(image_extended, image_extended_channels);
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@ -148,31 +142,15 @@ static void crossBilateralFilter(const Mat& image, const Mat& edge_image, const
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}
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}
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}
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}
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static void calcOpticalFlowSingleScaleSF(const Mat& prev,
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static void calcConfidence(const Mat& prev,
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const Mat& next,
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const Mat& next,
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const Mat& mask,
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const Mat& flow,
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Mat& flow,
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Mat& confidence,
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Mat& confidence,
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int max_flow) {
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int averaging_radius,
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int max_flow,
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float sigma_dist,
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float sigma_color) {
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const int rows = prev.rows;
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const int rows = prev.rows;
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const int cols = prev.cols;
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const int cols = prev.cols;
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confidence = Mat::zeros(rows, cols, CV_32F);
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confidence = Mat::zeros(rows, cols, CV_32F);
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Mat diff_storage(averaging_radius*2 + 1, averaging_radius*2 + 1, CV_32F);
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Mat w_full_window(averaging_radius*2 + 1, averaging_radius*2 + 1, CV_32F);
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Mat wd_full_window(averaging_radius*2 + 1, averaging_radius*2 + 1, CV_32F);
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float w_full_window_sum = 1e-9f;
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Mat prev_extended;
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copyMakeBorder(prev, prev_extended,
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averaging_radius, averaging_radius, averaging_radius, averaging_radius,
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BORDER_DEFAULT);
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wd(wd_full_window, averaging_radius, averaging_radius, averaging_radius, averaging_radius, sigma_dist);
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for (int r0 = 0; r0 < rows; ++r0) {
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for (int r0 = 0; r0 < rows; ++r0) {
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for (int c0 = 0; c0 < cols; ++c0) {
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for (int c0 = 0; c0 < cols; ++c0) {
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Vec2f flow_at_point = flow.at<Vec2f>(r0, c0);
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Vec2f flow_at_point = flow.at<Vec2f>(r0, c0);
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@ -183,25 +161,16 @@ static void calcOpticalFlowSingleScaleSF(const Mat& prev,
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if (c0 + v0 < 0) { v0 = -c0; }
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if (c0 + v0 < 0) { v0 = -c0; }
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if (c0 + v0 >= cols) { v0 = cols - 1 - c0; }
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if (c0 + v0 >= cols) { v0 = cols - 1 - c0; }
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const int min_row_shift = -min(r0 + u0, max_flow);
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const int top_row_shift = -min(r0 + u0, max_flow);
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const int max_row_shift = min(rows - 1 - (r0 + u0), max_flow);
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const int bottom_row_shift = min(rows - 1 - (r0 + u0), max_flow);
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const int min_col_shift = -min(c0 + v0, max_flow);
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const int left_col_shift = -min(c0 + v0, max_flow);
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const int max_col_shift = min(cols - 1 - (c0 + v0), max_flow);
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const int right_col_shift = min(cols - 1 - (c0 + v0), max_flow);
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float min_cost = FLT_MAX, best_u = (float)u0, best_v = (float)v0;
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if (mask.at<uchar>(r0, c0)) {
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wc(prev_extended, w_full_window, r0 + averaging_radius, c0 + averaging_radius,
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averaging_radius, averaging_radius, averaging_radius, averaging_radius, sigma_color);
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multiply(w_full_window, wd_full_window, w_full_window);
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w_full_window_sum = (float)sum(w_full_window)[0];
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}
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bool first_flow_iteration = true;
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bool first_flow_iteration = true;
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float sum_e = 0, min_e = 0;
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float sum_e = 0, min_e = 0;
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for (int u = min_row_shift; u <= max_row_shift; ++u) {
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for (int u = top_row_shift; u <= bottom_row_shift; ++u) {
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for (int v = min_col_shift; v <= max_col_shift; ++v) {
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for (int v = left_col_shift; v <= right_col_shift; ++v) {
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float e = dist(prev.at<Vec3b>(r0, c0), next.at<Vec3b>(r0 + u0 + u, c0 + v0 + v));
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float e = dist(prev.at<Vec3b>(r0, c0), next.at<Vec3b>(r0 + u0 + u, c0 + v0 + v));
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if (first_flow_iteration) {
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if (first_flow_iteration) {
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sum_e = e;
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sum_e = e;
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@ -211,55 +180,83 @@ static void calcOpticalFlowSingleScaleSF(const Mat& prev,
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sum_e += e;
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sum_e += e;
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min_e = std::min(min_e, e);
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min_e = std::min(min_e, e);
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}
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}
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if (!mask.at<uchar>(r0, c0)) {
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}
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continue;
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}
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int windows_square = (bottom_row_shift - top_row_shift + 1) *
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(right_col_shift - left_col_shift + 1);
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confidence.at<float>(r0, c0) = (windows_square == 0) ? 0
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: sum_e / windows_square - min_e;
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CV_Assert(confidence.at<float>(r0, c0) >= 0);
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}
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}
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}
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static void calcOpticalFlowSingleScaleSF(const Mat& prev_extended,
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const Mat& next_extended,
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const Mat& mask,
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Mat& flow,
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int averaging_radius,
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int max_flow,
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float sigma_dist,
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float sigma_color) {
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const int averaging_radius_2 = averaging_radius << 1;
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const int rows = prev_extended.rows - averaging_radius_2;
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const int cols = prev_extended.cols - averaging_radius_2;
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Mat weight_window(averaging_radius_2 + 1, averaging_radius_2 + 1, CV_32F);
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Mat space_weight_window(averaging_radius_2 + 1, averaging_radius_2 + 1, CV_32F);
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wd(space_weight_window, averaging_radius, averaging_radius, averaging_radius, averaging_radius, sigma_dist);
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for (int r0 = 0; r0 < rows; ++r0) {
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for (int c0 = 0; c0 < cols; ++c0) {
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if (!mask.at<uchar>(r0, c0)) {
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continue;
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}
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// TODO: do smth with this creepy staff
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Vec2f flow_at_point = flow.at<Vec2f>(r0, c0);
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int u0 = floor(flow_at_point[0] + 0.5);
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if (r0 + u0 < 0) { u0 = -r0; }
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if (r0 + u0 >= rows) { u0 = rows - 1 - r0; }
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int v0 = floor(flow_at_point[1] + 0.5);
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if (c0 + v0 < 0) { v0 = -c0; }
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if (c0 + v0 >= cols) { v0 = cols - 1 - c0; }
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const int top_row_shift = -min(r0 + u0, max_flow);
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const int bottom_row_shift = min(rows - 1 - (r0 + u0), max_flow);
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const int left_col_shift = -min(c0 + v0, max_flow);
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const int right_col_shift = min(cols - 1 - (c0 + v0), max_flow);
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float min_cost = DBL_MAX, best_u = u0, best_v = v0;
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wc(prev_extended, weight_window, r0 + averaging_radius, c0 + averaging_radius,
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averaging_radius, averaging_radius, averaging_radius, averaging_radius, sigma_color);
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multiply(weight_window, space_weight_window, weight_window);
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const int prev_extended_top_window_row = r0;
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const int prev_extended_left_window_col = c0;
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for (int u = top_row_shift; u <= bottom_row_shift; ++u) {
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const int next_extended_top_window_row = r0 + u0 + u;
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for (int v = left_col_shift; v <= right_col_shift; ++v) {
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const int next_extended_left_window_col = c0 + v0 + v;
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float cost = 0;
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for (int r = 0; r <= averaging_radius_2; ++r) {
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const Vec3b *prev_extended_window_row = prev_extended.ptr<Vec3b>(prev_extended_top_window_row + r);
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const Vec3b *next_extended_window_row = next_extended.ptr<Vec3b>(next_extended_top_window_row + r);
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const float* weight_window_row = weight_window.ptr<float>(r);
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for (int c = 0; c <= averaging_radius_2; ++c) {
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cost += weight_window_row[c] *
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dist(prev_extended_window_row[prev_extended_left_window_col + c],
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next_extended_window_row[next_extended_left_window_col + c]);
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}
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}
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}
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// cost should be divided by sum(weight_window), but because
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// we interested only in min(cost) and sum(weight_window) is constant
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// for every point - we remove it
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const int window_top_shift = min(r0, r0 + u + u0, averaging_radius);
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const int window_bottom_shift = min(rows - 1 - r0,
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rows - 1 - (r0 + u + u0),
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averaging_radius);
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const int window_left_shift = min(c0, c0 + v + v0, averaging_radius);
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const int window_right_shift = min(cols - 1 - c0,
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cols - 1 - (c0 + v + v0),
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averaging_radius);
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const Range prev_row_range(r0 - window_top_shift, r0 + window_bottom_shift + 1);
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const Range prev_col_range(c0 - window_left_shift, c0 + window_right_shift + 1);
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const Range next_row_range(r0 + u0 + u - window_top_shift,
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r0 + u0 + u + window_bottom_shift + 1);
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const Range next_col_range(c0 + v0 + v - window_left_shift,
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c0 + v0 + v + window_right_shift + 1);
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Mat diff2;
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Mat w;
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float w_sum;
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if (window_top_shift == averaging_radius &&
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window_bottom_shift == averaging_radius &&
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window_left_shift == averaging_radius &&
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window_right_shift == averaging_radius) {
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w = w_full_window;
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w_sum = w_full_window_sum;
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diff2 = diff_storage;
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dist(prev(prev_row_range, prev_col_range), next(next_row_range, next_col_range), diff2);
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} else {
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diff2 = diff_storage(Range(averaging_radius - window_top_shift,
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averaging_radius + 1 + window_bottom_shift),
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Range(averaging_radius - window_left_shift,
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averaging_radius + 1 + window_right_shift));
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dist(prev(prev_row_range, prev_col_range), next(next_row_range, next_col_range), diff2);
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w = w_full_window(Range(averaging_radius - window_top_shift,
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averaging_radius + 1 + window_bottom_shift),
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Range(averaging_radius - window_left_shift,
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averaging_radius + 1 + window_right_shift));
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w_sum = (float)sum(w)[0];
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}
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multiply(diff2, w, diff2);
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const float cost = (float)(sum(diff2)[0] / w_sum);
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if (cost < min_cost) {
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if (cost < min_cost) {
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min_cost = cost;
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min_cost = cost;
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best_u = (float)(u + u0);
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best_u = (float)(u + u0);
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@ -267,14 +264,7 @@ static void calcOpticalFlowSingleScaleSF(const Mat& prev,
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}
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}
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}
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}
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}
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}
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int windows_square = (max_row_shift - min_row_shift + 1) *
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flow.at<Vec2f>(r0, c0) = Vec2f(best_u, best_v);
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(max_col_shift - min_col_shift + 1);
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confidence.at<float>(r0, c0) = (windows_square == 0) ? 0
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: sum_e / windows_square - min_e;
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CV_Assert(confidence.at<float>(r0, c0) >= 0); // TODO: remove it after testing
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if (mask.at<uchar>(r0, c0)) {
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flow.at<Vec2f>(r0, c0) = Vec2f(best_u, best_v);
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}
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}
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}
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}
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}
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}
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}
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@ -319,7 +309,7 @@ static Mat calcIrregularityMat(const Mat& flow, int radius) {
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static void selectPointsToRecalcFlow(const Mat& flow,
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static void selectPointsToRecalcFlow(const Mat& flow,
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int irregularity_metric_radius,
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int irregularity_metric_radius,
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int speed_up_thr,
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float speed_up_thr,
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int curr_rows,
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int curr_rows,
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int curr_cols,
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int curr_cols,
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const Mat& prev_speed_up,
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const Mat& prev_speed_up,
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@ -474,22 +464,22 @@ static void buildPyramidWithResizeMethod(Mat& src,
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}
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}
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}
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}
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void calcOpticalFlowSF(Mat& from,
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CV_EXPORTS_W void calcOpticalFlowSF(Mat& from,
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Mat& to,
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Mat& to,
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Mat& resulted_flow,
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Mat& resulted_flow,
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int layers,
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int layers,
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int averaging_block_size,
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int averaging_radius,
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int max_flow,
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int max_flow,
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double sigma_dist,
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double sigma_dist,
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double sigma_color,
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double sigma_color,
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int postprocess_window,
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int postprocess_window,
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double sigma_dist_fix,
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double sigma_dist_fix,
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double sigma_color_fix,
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double sigma_color_fix,
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double occ_thr,
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double occ_thr,
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int upscale_averaging_radius,
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int upscale_averaging_radius,
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double upscale_sigma_dist,
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double upscale_sigma_dist,
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double upscale_sigma_color,
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double upscale_sigma_color,
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double speed_up_thr) {
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double speed_up_thr) {
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vector<Mat> pyr_from_images;
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vector<Mat> pyr_from_images;
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vector<Mat> pyr_to_images;
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vector<Mat> pyr_to_images;
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@ -498,34 +488,43 @@ void calcOpticalFlowSF(Mat& from,
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CV_Assert((int)pyr_from_images.size() == layers && (int)pyr_to_images.size() == layers);
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CV_Assert((int)pyr_from_images.size() == layers && (int)pyr_to_images.size() == layers);
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Mat first_from_image = pyr_from_images[layers - 1];
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Mat curr_from, curr_to, prev_from, prev_to;
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Mat first_to_image = pyr_to_images[layers - 1];
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Mat curr_from_extended, curr_to_extended;
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||||||
Mat mask = Mat::ones(first_from_image.rows, first_from_image.cols, CV_8U);
|
curr_from = pyr_from_images[layers - 1];
|
||||||
Mat mask_inv = Mat::ones(first_from_image.rows, first_from_image.cols, CV_8U);
|
curr_to = pyr_to_images[layers - 1];
|
||||||
|
|
||||||
Mat flow(first_from_image.rows, first_from_image.cols, CV_32FC2);
|
copyMakeBorder(curr_from, curr_from_extended,
|
||||||
Mat flow_inv(first_to_image.rows, first_to_image.cols, CV_32FC2);
|
averaging_radius, averaging_radius, averaging_radius, averaging_radius,
|
||||||
|
BORDER_DEFAULT);
|
||||||
|
copyMakeBorder(curr_to, curr_to_extended,
|
||||||
|
averaging_radius, averaging_radius, averaging_radius, averaging_radius,
|
||||||
|
BORDER_DEFAULT);
|
||||||
|
|
||||||
|
Mat mask = Mat::ones(curr_from.size(), CV_8U);
|
||||||
|
Mat mask_inv = Mat::ones(curr_from.size(), CV_8U);
|
||||||
|
|
||||||
|
Mat flow(curr_from.size(), CV_32FC2);
|
||||||
|
Mat flow_inv(curr_to.size(), CV_32FC2);
|
||||||
|
|
||||||
Mat confidence;
|
Mat confidence;
|
||||||
Mat confidence_inv;
|
Mat confidence_inv;
|
||||||
|
|
||||||
calcOpticalFlowSingleScaleSF(first_from_image,
|
|
||||||
first_to_image,
|
calcOpticalFlowSingleScaleSF(curr_from_extended,
|
||||||
|
curr_to_extended,
|
||||||
mask,
|
mask,
|
||||||
flow,
|
flow,
|
||||||
confidence,
|
averaging_radius,
|
||||||
averaging_block_size,
|
|
||||||
max_flow,
|
max_flow,
|
||||||
(float)sigma_dist,
|
(float)sigma_dist,
|
||||||
(float)sigma_color);
|
(float)sigma_color);
|
||||||
|
|
||||||
calcOpticalFlowSingleScaleSF(first_to_image,
|
calcOpticalFlowSingleScaleSF(curr_to_extended,
|
||||||
first_from_image,
|
curr_from_extended,
|
||||||
mask_inv,
|
mask_inv,
|
||||||
flow_inv,
|
flow_inv,
|
||||||
confidence_inv,
|
averaging_radius,
|
||||||
averaging_block_size,
|
|
||||||
max_flow,
|
max_flow,
|
||||||
(float)sigma_dist,
|
(float)sigma_dist,
|
||||||
(float)sigma_color);
|
(float)sigma_color);
|
||||||
@ -540,14 +539,21 @@ void calcOpticalFlowSF(Mat& from,
|
|||||||
(float)occ_thr,
|
(float)occ_thr,
|
||||||
confidence_inv);
|
confidence_inv);
|
||||||
|
|
||||||
Mat speed_up = Mat::zeros(first_from_image.rows, first_from_image.cols, CV_8U);
|
Mat speed_up = Mat::zeros(curr_from.size(), CV_8U);
|
||||||
Mat speed_up_inv = Mat::zeros(first_from_image.rows, first_from_image.cols, CV_8U);
|
Mat speed_up_inv = Mat::zeros(curr_from.size(), CV_8U);
|
||||||
|
|
||||||
for (int curr_layer = layers - 2; curr_layer >= 0; --curr_layer) {
|
for (int curr_layer = layers - 2; curr_layer >= 0; --curr_layer) {
|
||||||
const Mat curr_from = pyr_from_images[curr_layer];
|
curr_from = pyr_from_images[curr_layer];
|
||||||
const Mat curr_to = pyr_to_images[curr_layer];
|
curr_to = pyr_to_images[curr_layer];
|
||||||
const Mat prev_from = pyr_from_images[curr_layer + 1];
|
prev_from = pyr_from_images[curr_layer + 1];
|
||||||
const Mat prev_to = pyr_to_images[curr_layer + 1];
|
prev_to = pyr_to_images[curr_layer + 1];
|
||||||
|
|
||||||
|
copyMakeBorder(curr_from, curr_from_extended,
|
||||||
|
averaging_radius, averaging_radius, averaging_radius, averaging_radius,
|
||||||
|
BORDER_DEFAULT);
|
||||||
|
copyMakeBorder(curr_to, curr_to_extended,
|
||||||
|
averaging_radius, averaging_radius, averaging_radius, averaging_radius,
|
||||||
|
BORDER_DEFAULT);
|
||||||
|
|
||||||
const int curr_rows = curr_from.rows;
|
const int curr_rows = curr_from.rows;
|
||||||
const int curr_cols = curr_from.cols;
|
const int curr_cols = curr_from.cols;
|
||||||
@ -555,8 +561,8 @@ void calcOpticalFlowSF(Mat& from,
|
|||||||
Mat new_speed_up, new_speed_up_inv;
|
Mat new_speed_up, new_speed_up_inv;
|
||||||
|
|
||||||
selectPointsToRecalcFlow(flow,
|
selectPointsToRecalcFlow(flow,
|
||||||
averaging_block_size,
|
averaging_radius,
|
||||||
(int)speed_up_thr,
|
speed_up_thr,
|
||||||
curr_rows,
|
curr_rows,
|
||||||
curr_cols,
|
curr_cols,
|
||||||
speed_up,
|
speed_up,
|
||||||
@ -564,8 +570,8 @@ void calcOpticalFlowSF(Mat& from,
|
|||||||
mask);
|
mask);
|
||||||
|
|
||||||
selectPointsToRecalcFlow(flow_inv,
|
selectPointsToRecalcFlow(flow_inv,
|
||||||
averaging_block_size,
|
averaging_radius,
|
||||||
(int)speed_up_thr,
|
speed_up_thr,
|
||||||
curr_rows,
|
curr_rows,
|
||||||
curr_cols,
|
curr_cols,
|
||||||
speed_up_inv,
|
speed_up_inv,
|
||||||
@ -593,22 +599,22 @@ void calcOpticalFlowSF(Mat& from,
|
|||||||
(float)upscale_sigma_dist,
|
(float)upscale_sigma_dist,
|
||||||
(float)upscale_sigma_color);
|
(float)upscale_sigma_color);
|
||||||
|
|
||||||
calcOpticalFlowSingleScaleSF(curr_from,
|
calcConfidence(curr_from, curr_to, flow, confidence, max_flow);
|
||||||
curr_to,
|
calcOpticalFlowSingleScaleSF(curr_from_extended,
|
||||||
|
curr_to_extended,
|
||||||
mask,
|
mask,
|
||||||
flow,
|
flow,
|
||||||
confidence,
|
averaging_radius,
|
||||||
averaging_block_size,
|
|
||||||
max_flow,
|
max_flow,
|
||||||
(float)sigma_dist,
|
(float)sigma_dist,
|
||||||
(float)sigma_color);
|
(float)sigma_color);
|
||||||
|
|
||||||
calcOpticalFlowSingleScaleSF(curr_to,
|
calcConfidence(curr_to, curr_from, flow_inv, confidence_inv, max_flow);
|
||||||
curr_from,
|
calcOpticalFlowSingleScaleSF(curr_to_extended,
|
||||||
|
curr_from_extended,
|
||||||
mask_inv,
|
mask_inv,
|
||||||
flow_inv,
|
flow_inv,
|
||||||
confidence_inv,
|
averaging_radius,
|
||||||
averaging_block_size,
|
|
||||||
max_flow,
|
max_flow,
|
||||||
(float)sigma_dist,
|
(float)sigma_dist,
|
||||||
(float)sigma_color);
|
(float)sigma_color);
|
||||||
@ -616,11 +622,12 @@ void calcOpticalFlowSF(Mat& from,
|
|||||||
extrapolateFlow(flow, speed_up);
|
extrapolateFlow(flow, speed_up);
|
||||||
extrapolateFlow(flow_inv, speed_up_inv);
|
extrapolateFlow(flow_inv, speed_up_inv);
|
||||||
|
|
||||||
|
//TODO: should we remove occlusions for the last stage?
|
||||||
removeOcclusions(flow, flow_inv, (float)occ_thr, confidence);
|
removeOcclusions(flow, flow_inv, (float)occ_thr, confidence);
|
||||||
removeOcclusions(flow_inv, flow, (float)occ_thr, confidence_inv);
|
removeOcclusions(flow_inv, flow, (float)occ_thr, confidence_inv);
|
||||||
}
|
}
|
||||||
|
|
||||||
crossBilateralFilter(flow, pyr_from_images[0], confidence, flow,
|
crossBilateralFilter(flow, curr_from, confidence, flow,
|
||||||
postprocess_window, (float)sigma_color_fix, (float)sigma_dist_fix);
|
postprocess_window, (float)sigma_color_fix, (float)sigma_dist_fix);
|
||||||
|
|
||||||
GaussianBlur(flow, flow, Size(3, 3), 5);
|
GaussianBlur(flow, flow, Size(3, 3), 5);
|
||||||
|
Loading…
Reference in New Issue
Block a user