Added handling of ROI in stitching features matchers

modules/stitching/include/opencv2/stitching/detail/matchers.hpp

@@ -67,6 +67,7 @@ class CV_EXPORTS FeaturesFinder
 public:
     virtual ~FeaturesFinder() {}
     void operator ()(const Mat &image, ImageFeatures &features);
+    void operator ()(const Mat &image, ImageFeatures &features, const std::vector<cv::Rect> &rois);
     virtual void collectGarbage() {}
 
 protected:

modules/stitching/include/opencv2/stitching/stitcher.hpp

@@ -66,6 +66,7 @@ public:
 
     // Stitches the biggest found pano. Returns status code.
     Status stitch(InputArray imgs, OutputArray pano);
+    Status stitch(InputArray imgs, const std::vector<std::vector<cv::Rect> > &rois, OutputArray pano);
 
     double registrationResol() const { return registr_resol_; }
     void setRegistrationResol(double resol_mpx) { registr_resol_ = resol_mpx; }
@@ -147,6 +148,7 @@ private:
     Ptr<detail::Blender> blender_;
 
     std::vector<cv::Mat> imgs_;
+    std::vector<std::vector<cv::Rect> > rois_;
     std::vector<cv::Size> full_img_sizes_;
     std::vector<detail::ImageFeatures> features_;
     std::vector<detail::MatchesInfo> pairwise_matches_;

modules/stitching/src/matchers.cpp

@@ -249,10 +249,47 @@ namespace detail {
 void FeaturesFinder::operator ()(const Mat &image, ImageFeatures &features)
 { 
     find(image, features);
+    cout << features.descriptors.cols << " " << features.descriptors.rows << " " << features.descriptors.type() << endl;
     features.img_size = image.size();
 }
 
 
+// TODO add tests for this function
+void FeaturesFinder::operator ()(const Mat &image, ImageFeatures &features, const vector<Rect> &rois)
+{ 
+    vector<ImageFeatures> roi_features;
+    size_t total_kps_count = 0;
+    int total_descriptors_width = 0;
+
+    for (size_t i = 0; i < rois.size(); ++i)
+    {
+        find(image(rois[i]), roi_features[i]);
+        total_kps_count += roi_features[i].keypoints.size();
+        total_descriptors_width += roi_features[i].descriptors.cols;
+    }
+
+    features.img_size = image.size();
+    features.keypoints.resize(total_kps_count);
+    features.descriptors.create(1, total_descriptors_width, roi_features[0].descriptors.type());
+
+    int kp_idx = 0;
+    int descr_offset = 0;
+    for (size_t i = 0; i < rois.size(); ++i)
+    {
+        for (size_t j = 0; j < features.keypoints.size(); ++j, ++kp_idx)
+        {
+            features.keypoints[kp_idx] = roi_features[i].keypoints[j];
+            features.keypoints[kp_idx].pt.x += (float)rois[i].x;
+            features.keypoints[kp_idx].pt.y += (float)rois[i].y;
+        }
+        Mat subdescr = features.descriptors.colRange(
+                descr_offset, descr_offset + roi_features[i].descriptors.cols);
+        roi_features[i].descriptors.copyTo(subdescr);
+        descr_offset += roi_features[i].descriptors.cols;
+    }
+}
+
+
 SurfFeaturesFinder::SurfFeaturesFinder(double hess_thresh, int num_octaves, int num_layers,
                                        int num_octaves_descr, int num_layers_descr)
 {

modules/stitching/src/stitcher.cpp

@@ -100,6 +100,13 @@ Stitcher::Status Stitcher::stitch(InputArray imgs, OutputArray pano)
 }
 
 
+Stitcher::Status Stitcher::stitch(InputArray imgs, const vector<vector<Rect> > &rois, OutputArray pano)
+{    
+    rois_ = rois;
+    return stitch(imgs, pano);
+}
+
+
 Stitcher::Status Stitcher::matchImages()
 {
     if ((int)imgs_.size() < 2)
@@ -148,7 +155,10 @@ Stitcher::Status Stitcher::matchImages()
             is_seam_scale_set = true;
         }
 
-        (*features_finder_)(img, features_[i]);
+        if (rois_.empty())
+            (*features_finder_)(img, features_[i]);
+        else
+            (*features_finder_)(img, features_[i], rois_[i]);
         features_[i].img_idx = i;
         LOGLN("Features in image #" << i+1 << ": " << features_[i].keypoints.size());