dnn: add a documentation for NMS, fix missing experimantal namespace

modules/dnn/include/opencv2/dnn/dnn.hpp

@@ -734,18 +734,20 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
      */
     CV_EXPORTS_W void shrinkCaffeModel(const String& src, const String& dst);
 
-    /** @brief
-     * @param bboxes
-     * @param scores
-     * @param score_threshold
-     * @param nms_threshold
-     * @param eta
-     * @param top_k
-     * @param indices
+    /** @brief Performs non maximum suppression given boxes and corresponding scores.
+
+     * @param bboxes a set of bounding boxes to apply NMS.
+     * @param scores a set of corresponding confidences.
+     * @param score_threshold a threshold used to filter boxes by score.
+     * @param nms_threshold a threshold used in non maximum suppression.
+     * @param indices the kept indices of bboxes after NMS.
+     * @param eta a coefficient in adaptive threshold formula: \f$nms\_threshold_{i+1}=eta\cdot nms\_threshold_i\f$.
+     * @param top_k if `>0`, keep at most @p top_k picked indices.
      */
     CV_EXPORTS_W void NMSBoxes(const std::vector<Rect>& bboxes, const std::vector<float>& scores,
                                const float score_threshold, const float nms_threshold,
-                               const float eta, const int top_k, CV_OUT std::vector<int>& indices);
+                               CV_OUT std::vector<int>& indices,
+                               const float eta = 1.f, const int top_k = 0);
 
 
 //! @}

modules/dnn/include/opencv2/dnn/nms.inl.hpp

@@ -48,39 +48,26 @@ inline void GetMaxScoreIndex(const std::vector<float>& scores, const float thres
                      SortScorePairDescend<int>);
 
     // Keep top_k scores if needed.
-    if (top_k > -1 && top_k < (int)score_index_vec.size())
+    if (top_k > 0 && top_k < (int)score_index_vec.size())
     {
         score_index_vec.resize(top_k);
     }
 }
 
-template <typename BoxType>
-struct NMSOverlap
-{
-    float operator() (const BoxType& a, const BoxType& b);
-};
-
-template <>
-inline float NMSOverlap<Rect>::operator() (const Rect& a, const Rect& b)
-{
-    float rectIntersectionArea = (float)(a & b).area();
-    return rectIntersectionArea / (a.area() + b.area() - rectIntersectionArea);
-}
-
 // Do non maximum suppression given bboxes and scores.
 // Inspired by Piotr Dollar's NMS implementation in EdgeBox.
 // https://goo.gl/jV3JYS
 //    bboxes: a set of bounding boxes.
 //    scores: a set of corresponding confidences.
 //    score_threshold: a threshold used to filter detection results.
 //    nms_threshold: a threshold used in non maximum suppression.
-//    top_k: if not -1, keep at most top_k picked indices.
+//    top_k: if not > 0, keep at most top_k picked indices.
 //    indices: the kept indices of bboxes after nms.
 template <typename BoxType>
 inline void NMSFast_(const std::vector<BoxType>& bboxes,
       const std::vector<float>& scores, const float score_threshold,
       const float nms_threshold, const float eta, const int top_k,
-      std::vector<int>& indices, NMSOverlap<BoxType> computeOverlap)
+      std::vector<int>& indices, float (*computeOverlap)(const BoxType&, const BoxType&))
 {
     CV_Assert(bboxes.size() == scores.size());
 
@@ -91,8 +78,8 @@ inline void NMSFast_(const std::vector<BoxType>& bboxes,
     // Do nms.
     float adaptive_threshold = nms_threshold;
     indices.clear();
-    while (score_index_vec.size() != 0) {
-        const int idx = score_index_vec.front().second;
+    for (size_t i = 0; i < score_index_vec.size(); ++i) {
+        const int idx = score_index_vec[i].second;
         bool keep = true;
         for (int k = 0; k < (int)indices.size() && keep; ++k) {
             const int kept_idx = indices[k];
@@ -101,7 +88,6 @@ inline void NMSFast_(const std::vector<BoxType>& bboxes,
         }
         if (keep)
             indices.push_back(idx);
-        score_index_vec.erase(score_index_vec.begin());
         if (keep && eta < 1 && adaptive_threshold > 0.5) {
           adaptive_threshold *= eta;
         }

modules/dnn/src/layers/detection_output_layer.cpp

@@ -62,6 +62,8 @@ static inline bool SortScorePairDescend(const std::pair<float, T>& pair1,
     return pair1.first > pair2.first;
 }
 
+static inline float caffe_box_overlap(const caffe::NormalizedBBox& a, const caffe::NormalizedBBox& b);
+
 } // namespace
 
 class DetectionOutputLayerImpl : public DetectionOutputLayer
@@ -309,7 +311,8 @@ class DetectionOutputLayerImpl : public DetectionOutputLayer
             LabelBBox::const_iterator label_bboxes = decodeBBoxes.find(label);
             if (label_bboxes == decodeBBoxes.end())
                 CV_ErrorNoReturn_(cv::Error::StsError, ("Could not find location predictions for label %d", label));
-            ApplyNMSFast(label_bboxes->second, scores, _confidenceThreshold, _nmsThreshold, 1.0, _topK, indices[c]);
+            NMSFast_(label_bboxes->second, scores, _confidenceThreshold, _nmsThreshold, 1.0, _topK,
+                indices[c], util::caffe_box_overlap);
             numDetections += indices[c].size();
         }
         if (_keepTopK > -1 && numDetections > (size_t)_keepTopK)
@@ -620,16 +623,6 @@ class DetectionOutputLayerImpl : public DetectionOutputLayer
         }
     }
 
-
-
-    static void ApplyNMSFast(const std::vector<caffe::NormalizedBBox>& bboxes,
-          const std::vector<float>& scores, const float score_threshold,
-          const float nms_threshold, const float eta, const int top_k,
-          std::vector<int>& indices)
-    {
-        NMSFast_(bboxes, scores, score_threshold, nms_threshold, eta, top_k, indices, NMSOverlap<caffe::NormalizedBBox>());
-    }
-
     // Compute the jaccard (intersection over union IoU) overlap between two bboxes.
     template<bool normalized>
     static float JaccardOverlap(const caffe::NormalizedBBox& bbox1,
@@ -675,8 +668,7 @@ class DetectionOutputLayerImpl : public DetectionOutputLayer
     }
 };
 
-template <>
-float NMSOverlap<caffe::NormalizedBBox>::operator() (const caffe::NormalizedBBox& a, const caffe::NormalizedBBox& b)
+float util::caffe_box_overlap(const caffe::NormalizedBBox& a, const caffe::NormalizedBBox& b)
 {
     return DetectionOutputLayerImpl::JaccardOverlap<true>(a, b);
 }

modules/dnn/src/nms.cpp

@@ -12,13 +12,22 @@ namespace cv
 {
 namespace dnn
 {
+CV__DNN_EXPERIMENTAL_NS_BEGIN
+
+static inline float rectOverlap(const Rect& a, const Rect& b)
+{
+    return 1.f - static_cast<float>(jaccardDistance(a, b));
+}
 
 void NMSBoxes(const std::vector<Rect>& bboxes, const std::vector<float>& scores,
                           const float score_threshold, const float nms_threshold,
-                          const float eta, const int top_k, std::vector<int>& indices)
+                          std::vector<int>& indices, const float eta, const int top_k)
 {
-    NMSFast_(bboxes, scores, score_threshold, nms_threshold, eta, top_k, indices, NMSOverlap<Rect>());
+    CV_Assert(bboxes.size() == scores.size(), score_threshold >= 0,
+        nms_threshold >= 0, eta > 0);
+    NMSFast_(bboxes, scores, score_threshold, nms_threshold, eta, top_k, indices, rectOverlap);
 }
 
+CV__DNN_EXPERIMENTAL_NS_END
 }// dnn
 }// cv