Commit c704942b authored by Vladislav Sovrasov's avatar Vladislav Sovrasov

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

parent acedb4a5
...@@ -734,18 +734,20 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN ...@@ -734,18 +734,20 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
*/ */
CV_EXPORTS_W void shrinkCaffeModel(const String& src, const String& dst); CV_EXPORTS_W void shrinkCaffeModel(const String& src, const String& dst);
/** @brief /** @brief Performs non maximum suppression given boxes and corresponding scores.
* @param bboxes
* @param scores * @param bboxes a set of bounding boxes to apply NMS.
* @param score_threshold * @param scores a set of corresponding confidences.
* @param nms_threshold * @param score_threshold a threshold used to filter boxes by score.
* @param eta * @param nms_threshold a threshold used in non maximum suppression.
* @param top_k * @param indices the kept indices of bboxes after NMS.
* @param indices * @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, 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 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);
//! @} //! @}
......
...@@ -48,25 +48,12 @@ inline void GetMaxScoreIndex(const std::vector<float>& scores, const float thres ...@@ -48,25 +48,12 @@ inline void GetMaxScoreIndex(const std::vector<float>& scores, const float thres
SortScorePairDescend<int>); SortScorePairDescend<int>);
// Keep top_k scores if needed. // 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); 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. // Do non maximum suppression given bboxes and scores.
// Inspired by Piotr Dollar's NMS implementation in EdgeBox. // Inspired by Piotr Dollar's NMS implementation in EdgeBox.
// https://goo.gl/jV3JYS // https://goo.gl/jV3JYS
...@@ -74,13 +61,13 @@ inline float NMSOverlap<Rect>::operator() (const Rect& a, const Rect& b) ...@@ -74,13 +61,13 @@ inline float NMSOverlap<Rect>::operator() (const Rect& a, const Rect& b)
// scores: a set of corresponding confidences. // scores: a set of corresponding confidences.
// score_threshold: a threshold used to filter detection results. // score_threshold: a threshold used to filter detection results.
// nms_threshold: a threshold used in non maximum suppression. // 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. // indices: the kept indices of bboxes after nms.
template <typename BoxType> template <typename BoxType>
inline void NMSFast_(const std::vector<BoxType>& bboxes, inline void NMSFast_(const std::vector<BoxType>& bboxes,
const std::vector<float>& scores, const float score_threshold, const std::vector<float>& scores, const float score_threshold,
const float nms_threshold, const float eta, const int top_k, 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()); CV_Assert(bboxes.size() == scores.size());
...@@ -91,8 +78,8 @@ inline void NMSFast_(const std::vector<BoxType>& bboxes, ...@@ -91,8 +78,8 @@ inline void NMSFast_(const std::vector<BoxType>& bboxes,
// Do nms. // Do nms.
float adaptive_threshold = nms_threshold; float adaptive_threshold = nms_threshold;
indices.clear(); indices.clear();
while (score_index_vec.size() != 0) { for (size_t i = 0; i < score_index_vec.size(); ++i) {
const int idx = score_index_vec.front().second; const int idx = score_index_vec[i].second;
bool keep = true; bool keep = true;
for (int k = 0; k < (int)indices.size() && keep; ++k) { for (int k = 0; k < (int)indices.size() && keep; ++k) {
const int kept_idx = indices[k]; const int kept_idx = indices[k];
...@@ -101,7 +88,6 @@ inline void NMSFast_(const std::vector<BoxType>& bboxes, ...@@ -101,7 +88,6 @@ inline void NMSFast_(const std::vector<BoxType>& bboxes,
} }
if (keep) if (keep)
indices.push_back(idx); indices.push_back(idx);
score_index_vec.erase(score_index_vec.begin());
if (keep && eta < 1 && adaptive_threshold > 0.5) { if (keep && eta < 1 && adaptive_threshold > 0.5) {
adaptive_threshold *= eta; adaptive_threshold *= eta;
} }
......
...@@ -62,6 +62,8 @@ static inline bool SortScorePairDescend(const std::pair<float, T>& pair1, ...@@ -62,6 +62,8 @@ static inline bool SortScorePairDescend(const std::pair<float, T>& pair1,
return pair1.first > pair2.first; return pair1.first > pair2.first;
} }
static inline float caffe_box_overlap(const caffe::NormalizedBBox& a, const caffe::NormalizedBBox& b);
} // namespace } // namespace
class DetectionOutputLayerImpl : public DetectionOutputLayer class DetectionOutputLayerImpl : public DetectionOutputLayer
...@@ -309,7 +311,8 @@ public: ...@@ -309,7 +311,8 @@ public:
LabelBBox::const_iterator label_bboxes = decodeBBoxes.find(label); LabelBBox::const_iterator label_bboxes = decodeBBoxes.find(label);
if (label_bboxes == decodeBBoxes.end()) if (label_bboxes == decodeBBoxes.end())
CV_ErrorNoReturn_(cv::Error::StsError, ("Could not find location predictions for label %d", label)); 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(); numDetections += indices[c].size();
} }
if (_keepTopK > -1 && numDetections > (size_t)_keepTopK) if (_keepTopK > -1 && numDetections > (size_t)_keepTopK)
...@@ -620,16 +623,6 @@ public: ...@@ -620,16 +623,6 @@ public:
} }
} }
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. // Compute the jaccard (intersection over union IoU) overlap between two bboxes.
template<bool normalized> template<bool normalized>
static float JaccardOverlap(const caffe::NormalizedBBox& bbox1, static float JaccardOverlap(const caffe::NormalizedBBox& bbox1,
...@@ -675,8 +668,7 @@ public: ...@@ -675,8 +668,7 @@ public:
} }
}; };
template <> float util::caffe_box_overlap(const caffe::NormalizedBBox& a, const caffe::NormalizedBBox& b)
float NMSOverlap<caffe::NormalizedBBox>::operator() (const caffe::NormalizedBBox& a, const caffe::NormalizedBBox& b)
{ {
return DetectionOutputLayerImpl::JaccardOverlap<true>(a, b); return DetectionOutputLayerImpl::JaccardOverlap<true>(a, b);
} }
......
...@@ -12,13 +12,22 @@ namespace cv ...@@ -12,13 +12,22 @@ namespace cv
{ {
namespace dnn 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, void NMSBoxes(const std::vector<Rect>& bboxes, const std::vector<float>& scores,
const float score_threshold, const float nms_threshold, 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 }// dnn
}// cv }// cv
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