mirror/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2025-06-28 07:23:30 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

Merge pull request #20474 from dbudniko:dbudniko/mtcnn_graph_without_resizes

Browse Source 
Remove explicit PNet resizes from MTCNN graph

* remove PNet resizes

* address comment from Ruslan
This commit is contained in:
Dmitry Budnikov 2021-08-02 13:58:18 +03:00 committed by GitHub
parent d52e4e5df3
commit ba0cea6826
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 2 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

9
modules/gapi/samples/face_detection_mtcnn.cpp
View File

@ -591,16 +591,13 @@ int main(int argc, char* argv[]) {
cv::GMat in_originalRGB = cv::gapi::BGR2RGB(in_original); cv::GMat in_originalRGB = cv::gapi::BGR2RGB(in_original);
cv::GMat in_transposedRGB = cv::gapi::transpose(in_originalRGB); cv::GMat in_transposedRGB = cv::gapi::transpose(in_originalRGB);
cv::GOpaque<cv::Size> in_sz = cv::gapi::streaming::size(in_original); cv::GOpaque<cv::Size> in_sz = cv::gapi::streaming::size(in_original);
cv::GMat in_resized[MAX_PYRAMID_LEVELS];
cv::GMat regressions[MAX_PYRAMID_LEVELS]; cv::GMat regressions[MAX_PYRAMID_LEVELS];
cv::GMat scores[MAX_PYRAMID_LEVELS]; cv::GMat scores[MAX_PYRAMID_LEVELS];
cv::GArray<custom::Face> nms_p_faces[MAX_PYRAMID_LEVELS]; cv::GArray<custom::Face> nms_p_faces[MAX_PYRAMID_LEVELS];
cv::GArray<custom::Face> total_faces[MAX_PYRAMID_LEVELS]; cv::GArray<custom::Face> total_faces[MAX_PYRAMID_LEVELS];
//The very first PNet pyramid layer to init total_faces[0] //The very first PNet pyramid layer to init total_faces[0]
cv::Size currentSize = cv::Size(level_size[0].height, level_size[0].width); std::tie(regressions[0], scores[0]) = run_mtcnn_p(in_transposedRGB, get_pnet_level_name(level_size[0]));
in_resized[0] = cv::gapi::resize(in_transposedRGB, currentSize);
std::tie(regressions[0], scores[0]) = run_mtcnn_p(in_resized[0], get_pnet_level_name(level_size[0]));
cv::GArray<custom::Face> faces0 = custom::BuildFaces::on(scores[0], regressions[0], static_cast<float>(scales[0]), conf_thresh_p); cv::GArray<custom::Face> faces0 = custom::BuildFaces::on(scores[0], regressions[0], static_cast<float>(scales[0]), conf_thresh_p);
cv::GArray<custom::Face> final_p_faces_for_bb2squares = custom::ApplyRegression::on(faces0, true); cv::GArray<custom::Face> final_p_faces_for_bb2squares = custom::ApplyRegression::on(faces0, true);
cv::GArray<custom::Face> final_faces_pnet0 = custom::BBoxesToSquares::on(final_p_faces_for_bb2squares); cv::GArray<custom::Face> final_faces_pnet0 = custom::BBoxesToSquares::on(final_p_faces_for_bb2squares);
@ -608,9 +605,7 @@ int main(int argc, char* argv[]) {
//The rest PNet pyramid layers to accumlate all layers result in total_faces[PYRAMID_LEVELS - 1]] //The rest PNet pyramid layers to accumlate all layers result in total_faces[PYRAMID_LEVELS - 1]]
for (int i = 1; i < pyramid_levels; ++i) for (int i = 1; i < pyramid_levels; ++i)
{ {
currentSize = cv::Size(level_size[i].height, level_size[i].width); std::tie(regressions[i], scores[i]) = run_mtcnn_p(in_transposedRGB, get_pnet_level_name(level_size[i]));
in_resized[i] = cv::gapi::resize(in_transposedRGB, currentSize);
std::tie(regressions[i], scores[i]) = run_mtcnn_p(in_resized[i], get_pnet_level_name(level_size[i]));
cv::GArray<custom::Face> faces = custom::BuildFaces::on(scores[i], regressions[i], static_cast<float>(scales[i]), conf_thresh_p); cv::GArray<custom::Face> faces = custom::BuildFaces::on(scores[i], regressions[i], static_cast<float>(scales[i]), conf_thresh_p);
cv::GArray<custom::Face> final_p_faces_for_bb2squares_i = custom::ApplyRegression::on(faces, true); cv::GArray<custom::Face> final_p_faces_for_bb2squares_i = custom::ApplyRegression::on(faces, true);
cv::GArray<custom::Face> final_faces_pnet_i = custom::BBoxesToSquares::on(final_p_faces_for_bb2squares_i); cv::GArray<custom::Face> final_faces_pnet_i = custom::BBoxesToSquares::on(final_p_faces_for_bb2squares_i);