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Commit 6c5dd5cf authored by Dmitry Kurtaev's avatar Dmitry Kurtaev
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Replace caffe::NormalizedBBox to local structure

parent c7f18435
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Showing with 119 additions and 104 deletions
modules/dnn/src/layers/detection_output_layer.cpp
View file @ 6c5dd5cf
......@@ -44,7 +44,6 @@
#include "layers_common.hpp"
#include <float.h>
#include <string>
#include <caffe.pb.h>
#include "../nms.inl.hpp"
namespace cv
......@@ -55,6 +54,27 @@ namespace dnn
namespace util
{
class NormalizedBBox
{
public:
float xmin, ymin, xmax, ymax;
NormalizedBBox()
: xmin(0), ymin(0), xmax(0), ymax(0), has_size_(false), size_(0) {}
float size() const { return size_; }
bool has_size() const { return has_size_; }
void set_size(float value) { size_ = value; has_size_ = true; }
void clear_size() { size_ = 0; has_size_ = false; }
private:
bool has_size_;
float size_;
};
template <typename T>
static inline bool SortScorePairDescend(const std::pair<float, T>& pair1,
const std::pair<float, T>& pair2)
......@@ -62,7 +82,7 @@ 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);
static inline float caffe_box_overlap(const util::NormalizedBBox& a, const util::NormalizedBBox& b);
} // namespace
......@@ -75,8 +95,7 @@ public:
int _backgroundLabelId;
typedef caffe::PriorBoxParameter_CodeType CodeType;
CodeType _codeType;
cv::String _codeType;
bool _varianceEncodedInTarget;
int _keepTopK;
......@@ -90,7 +109,7 @@ public:
enum { _numAxes = 4 };
static const std::string _layerName;
typedef std::map<int, std::vector<caffe::NormalizedBBox> > LabelBBox;
typedef std::map<int, std::vector<util::NormalizedBBox> > LabelBBox;
bool getParameterDict(const LayerParams &params,
const std::string &parameterName,
......@@ -135,12 +154,10 @@ public:
void getCodeType(const LayerParams &params)
{
String codeTypeString = params.get<String>("code_type").toLowerCase();
if (codeTypeString == "corner")
_codeType = caffe::PriorBoxParameter_CodeType_CORNER;
else if (codeTypeString == "center_size")
_codeType = caffe::PriorBoxParameter_CodeType_CENTER_SIZE;
if (codeTypeString == "center_size")
_codeType = "CENTER_SIZE";
else
_codeType = caffe::PriorBoxParameter_CodeType_CORNER;
_codeType = "CORNER";
}
DetectionOutputLayerImpl(const LayerParams &params)
......@@ -229,7 +246,7 @@ public:
GetConfidenceScores(confidenceData, num, numPriors, _numClasses, allConfidenceScores);
// Retrieve all prior bboxes
std::vector<caffe::NormalizedBBox> priorBBoxes;
std::vector<util::NormalizedBBox> priorBBoxes;
std::vector<std::vector<float> > priorVariances;
GetPriorBBoxes(priorData, numPriors, priorBBoxes, priorVariances);
......@@ -310,7 +327,7 @@ public:
GetConfidenceScores(confidenceData, num, numPriors, _numClasses, allConfidenceScores);
// Retrieve all prior bboxes
std::vector<caffe::NormalizedBBox> priorBBoxes;
std::vector<util::NormalizedBBox> priorBBoxes;
std::vector<std::vector<float> > priorVariances;
GetPriorBBoxes(priorData, numPriors, priorBBoxes, priorVariances);
......@@ -370,14 +387,14 @@ public:
for (size_t j = 0; j < indices.size(); ++j, ++count)
{
int idx = indices[j];
const caffe::NormalizedBBox& decode_bbox = label_bboxes->second[idx];
const util::NormalizedBBox& decode_bbox = label_bboxes->second[idx];
outputsData[count * 7] = i;
outputsData[count * 7 + 1] = label;
outputsData[count * 7 + 2] = scores[idx];
outputsData[count * 7 + 3] = decode_bbox.xmin();
outputsData[count * 7 + 4] = decode_bbox.ymin();
outputsData[count * 7 + 5] = decode_bbox.xmax();
outputsData[count * 7 + 6] = decode_bbox.ymax();
outputsData[count * 7 + 3] = decode_bbox.xmin;
outputsData[count * 7 + 4] = decode_bbox.ymin;
outputsData[count * 7 + 5] = decode_bbox.xmax;
outputsData[count * 7 + 6] = decode_bbox.ymax;
}
}
return count;
......@@ -454,9 +471,9 @@ public:
// Compute bbox size
template<bool normalized>
static float BBoxSize(const caffe::NormalizedBBox& bbox)
static float BBoxSize(const util::NormalizedBBox& bbox)
{
if (bbox.xmax() < bbox.xmin() || bbox.ymax() < bbox.ymin())
if (bbox.xmax < bbox.xmin || bbox.ymax < bbox.ymin)
{
return 0; // If bbox is invalid (e.g. xmax < xmin or ymax < ymin), return 0.
}
......@@ -468,8 +485,8 @@ public:
}
else
{
float width = bbox.xmax() - bbox.xmin();
float height = bbox.ymax() - bbox.ymin();
float width = bbox.xmax - bbox.xmin;
float height = bbox.ymax - bbox.ymin;
if (normalized)
{
return width * height;
......@@ -487,54 +504,52 @@ public:
// Decode a bbox according to a prior bbox
template<bool variance_encoded_in_target>
static void DecodeBBox(
const caffe::NormalizedBBox& prior_bbox, const std::vector<float>& prior_variance,
const CodeType code_type,
const bool clip_bbox, const caffe::NormalizedBBox& bbox,
caffe::NormalizedBBox& decode_bbox)
const util::NormalizedBBox& prior_bbox, const std::vector<float>& prior_variance,
const cv::String& code_type,
const bool clip_bbox, const util::NormalizedBBox& bbox,
util::NormalizedBBox& decode_bbox)
{
float bbox_xmin = variance_encoded_in_target ? bbox.xmin() : prior_variance[0] * bbox.xmin();
float bbox_ymin = variance_encoded_in_target ? bbox.ymin() : prior_variance[1] * bbox.ymin();
float bbox_xmax = variance_encoded_in_target ? bbox.xmax() : prior_variance[2] * bbox.xmax();
float bbox_ymax = variance_encoded_in_target ? bbox.ymax() : prior_variance[3] * bbox.ymax();
switch(code_type)
{
case caffe::PriorBoxParameter_CodeType_CORNER:
decode_bbox.set_xmin(prior_bbox.xmin() + bbox_xmin);
decode_bbox.set_ymin(prior_bbox.ymin() + bbox_ymin);
decode_bbox.set_xmax(prior_bbox.xmax() + bbox_xmax);
decode_bbox.set_ymax(prior_bbox.ymax() + bbox_ymax);
break;
case caffe::PriorBoxParameter_CodeType_CENTER_SIZE:
{
float prior_width = prior_bbox.xmax() - prior_bbox.xmin();
CV_Assert(prior_width > 0);
float prior_height = prior_bbox.ymax() - prior_bbox.ymin();
CV_Assert(prior_height > 0);
float prior_center_x = (prior_bbox.xmin() + prior_bbox.xmax()) * .5;
float prior_center_y = (prior_bbox.ymin() + prior_bbox.ymax()) * .5;
float decode_bbox_center_x, decode_bbox_center_y;
float decode_bbox_width, decode_bbox_height;
decode_bbox_center_x = bbox_xmin * prior_width + prior_center_x;
decode_bbox_center_y = bbox_ymin * prior_height + prior_center_y;
decode_bbox_width = exp(bbox_xmax) * prior_width;
decode_bbox_height = exp(bbox_ymax) * prior_height;
decode_bbox.set_xmin(decode_bbox_center_x - decode_bbox_width * .5);
decode_bbox.set_ymin(decode_bbox_center_y - decode_bbox_height * .5);
decode_bbox.set_xmax(decode_bbox_center_x + decode_bbox_width * .5);
decode_bbox.set_ymax(decode_bbox_center_y + decode_bbox_height * .5);
break;
}
default:
CV_ErrorNoReturn(Error::StsBadArg, "Unknown type.");
};
float bbox_xmin = variance_encoded_in_target ? bbox.xmin : prior_variance[0] * bbox.xmin;
float bbox_ymin = variance_encoded_in_target ? bbox.ymin : prior_variance[1] * bbox.ymin;
float bbox_xmax = variance_encoded_in_target ? bbox.xmax : prior_variance[2] * bbox.xmax;
float bbox_ymax = variance_encoded_in_target ? bbox.ymax : prior_variance[3] * bbox.ymax;
if (code_type == "CORNER")
{
decode_bbox.xmin = prior_bbox.xmin + bbox_xmin;
decode_bbox.ymin = prior_bbox.ymin + bbox_ymin;
decode_bbox.xmax = prior_bbox.xmax + bbox_xmax;
decode_bbox.ymax = prior_bbox.ymax + bbox_ymax;
}
else if (code_type == "CENTER_SIZE")
{
float prior_width = prior_bbox.xmax - prior_bbox.xmin;
CV_Assert(prior_width > 0);
float prior_height = prior_bbox.ymax - prior_bbox.ymin;
CV_Assert(prior_height > 0);
float prior_center_x = (prior_bbox.xmin + prior_bbox.xmax) * .5;
float prior_center_y = (prior_bbox.ymin + prior_bbox.ymax) * .5;
float decode_bbox_center_x, decode_bbox_center_y;
float decode_bbox_width, decode_bbox_height;
decode_bbox_center_x = bbox_xmin * prior_width + prior_center_x;
decode_bbox_center_y = bbox_ymin * prior_height + prior_center_y;
decode_bbox_width = exp(bbox_xmax) * prior_width;
decode_bbox_height = exp(bbox_ymax) * prior_height;
decode_bbox.xmin = decode_bbox_center_x - decode_bbox_width * .5;
decode_bbox.ymin = decode_bbox_center_y - decode_bbox_height * .5;
decode_bbox.xmax = decode_bbox_center_x + decode_bbox_width * .5;
decode_bbox.ymax = decode_bbox_center_y + decode_bbox_height * .5;
}
else
CV_ErrorNoReturn(Error::StsBadArg, "Unknown type.");
if (clip_bbox)
{
// Clip the caffe::NormalizedBBox such that the range for each corner is [0, 1]
decode_bbox.set_xmin(std::max(std::min(decode_bbox.xmin(), 1.f), 0.f));
decode_bbox.set_ymin(std::max(std::min(decode_bbox.ymin(), 1.f), 0.f));
decode_bbox.set_xmax(std::max(std::min(decode_bbox.xmax(), 1.f), 0.f));
decode_bbox.set_ymax(std::max(std::min(decode_bbox.ymax(), 1.f), 0.f));
// Clip the util::NormalizedBBox such that the range for each corner is [0, 1]
decode_bbox.xmin = std::max(std::min(decode_bbox.xmin, 1.f), 0.f);
decode_bbox.ymin = std::max(std::min(decode_bbox.ymin, 1.f), 0.f);
decode_bbox.xmax = std::max(std::min(decode_bbox.xmax, 1.f), 0.f);
decode_bbox.ymax = std::max(std::min(decode_bbox.ymax, 1.f), 0.f);
}
decode_bbox.clear_size();
decode_bbox.set_size(BBoxSize<true>(decode_bbox));
......@@ -542,11 +557,11 @@ public:
// Decode a set of bboxes according to a set of prior bboxes
static void DecodeBBoxes(
const std::vector<caffe::NormalizedBBox>& prior_bboxes,
const std::vector<util::NormalizedBBox>& prior_bboxes,
const std::vector<std::vector<float> >& prior_variances,
const CodeType code_type, const bool variance_encoded_in_target,
const bool clip_bbox, const std::vector<caffe::NormalizedBBox>& bboxes,
std::vector<caffe::NormalizedBBox>& decode_bboxes)
const cv::String& code_type, const bool variance_encoded_in_target,
const bool clip_bbox, const std::vector<util::NormalizedBBox>& bboxes,
std::vector<util::NormalizedBBox>& decode_bboxes)
{
CV_Assert(prior_bboxes.size() == prior_variances.size());
CV_Assert(prior_bboxes.size() == bboxes.size());
......@@ -569,11 +584,11 @@ public:
// Decode all bboxes in a batch
static void DecodeBBoxesAll(const std::vector<LabelBBox>& all_loc_preds,
const std::vector<caffe::NormalizedBBox>& prior_bboxes,
const std::vector<util::NormalizedBBox>& prior_bboxes,
const std::vector<std::vector<float> >& prior_variances,
const int num, const bool share_location,
const int num_loc_classes, const int background_label_id,
const CodeType code_type, const bool variance_encoded_in_target,
const cv::String& code_type, const bool variance_encoded_in_target,
const bool clip, std::vector<LabelBBox>& all_decode_bboxes)
{
CV_Assert(all_loc_preds.size() == num);
......@@ -602,10 +617,10 @@ public:
// Get prior bounding boxes from prior_data
// prior_data: 1 x 2 x num_priors * 4 x 1 blob.
// num_priors: number of priors.
// prior_bboxes: stores all the prior bboxes in the format of caffe::NormalizedBBox.
// prior_bboxes: stores all the prior bboxes in the format of util::NormalizedBBox.
// prior_variances: stores all the variances needed by prior bboxes.
static void GetPriorBBoxes(const float* priorData, const int& numPriors,
std::vector<caffe::NormalizedBBox>& priorBBoxes,
std::vector<util::NormalizedBBox>& priorBBoxes,
std::vector<std::vector<float> >& priorVariances)
{
priorBBoxes.clear(); priorBBoxes.resize(numPriors);
......@@ -613,11 +628,11 @@ public:
for (int i = 0; i < numPriors; ++i)
{
int startIdx = i * 4;
caffe::NormalizedBBox& bbox = priorBBoxes[i];
bbox.set_xmin(priorData[startIdx]);
bbox.set_ymin(priorData[startIdx + 1]);
bbox.set_xmax(priorData[startIdx + 2]);
bbox.set_ymax(priorData[startIdx + 3]);
util::NormalizedBBox& bbox = priorBBoxes[i];
bbox.xmin = priorData[startIdx];
bbox.ymin = priorData[startIdx + 1];
bbox.xmax = priorData[startIdx + 2];
bbox.ymax = priorData[startIdx + 3];
bbox.set_size(BBoxSize<true>(bbox));
}
......@@ -667,20 +682,20 @@ public:
{
labelBBox[label].resize(numPredsPerClass);
}
caffe::NormalizedBBox& bbox = labelBBox[label][p];
util::NormalizedBBox& bbox = labelBBox[label][p];
if (locPredTransposed)
{
bbox.set_ymin(locData[startIdx + c * 4]);
bbox.set_xmin(locData[startIdx + c * 4 + 1]);
bbox.set_ymax(locData[startIdx + c * 4 + 2]);
bbox.set_xmax(locData[startIdx + c * 4 + 3]);
bbox.ymin = locData[startIdx + c * 4];
bbox.xmin = locData[startIdx + c * 4 + 1];
bbox.ymax = locData[startIdx + c * 4 + 2];
bbox.xmax = locData[startIdx + c * 4 + 3];
}
else
{
bbox.set_xmin(locData[startIdx + c * 4]);
bbox.set_ymin(locData[startIdx + c * 4 + 1]);
bbox.set_xmax(locData[startIdx + c * 4 + 2]);
bbox.set_ymax(locData[startIdx + c * 4 + 3]);
bbox.xmin = locData[startIdx + c * 4];
bbox.ymin = locData[startIdx + c * 4 + 1];
bbox.xmax = locData[startIdx + c * 4 + 2];
bbox.ymax = locData[startIdx + c * 4 + 3];
}
}
}
......@@ -717,30 +732,30 @@ public:
// Compute the jaccard (intersection over union IoU) overlap between two bboxes.
template<bool normalized>
static float JaccardOverlap(const caffe::NormalizedBBox& bbox1,
const caffe::NormalizedBBox& bbox2)
static float JaccardOverlap(const util::NormalizedBBox& bbox1,
const util::NormalizedBBox& bbox2)
{
caffe::NormalizedBBox intersect_bbox;
if (bbox2.xmin() > bbox1.xmax() || bbox2.xmax() < bbox1.xmin() ||
bbox2.ymin() > bbox1.ymax() || bbox2.ymax() < bbox1.ymin())
util::NormalizedBBox intersect_bbox;
if (bbox2.xmin > bbox1.xmax || bbox2.xmax < bbox1.xmin ||
bbox2.ymin > bbox1.ymax || bbox2.ymax < bbox1.ymin)
{
// Return [0, 0, 0, 0] if there is no intersection.
intersect_bbox.set_xmin(0);
intersect_bbox.set_ymin(0);
intersect_bbox.set_xmax(0);
intersect_bbox.set_ymax(0);
intersect_bbox.xmin = 0;
intersect_bbox.ymin = 0;
intersect_bbox.xmax = 0;
intersect_bbox.ymax = 0;
}
else
{
intersect_bbox.set_xmin(std::max(bbox1.xmin(), bbox2.xmin()));
intersect_bbox.set_ymin(std::max(bbox1.ymin(), bbox2.ymin()));
intersect_bbox.set_xmax(std::min(bbox1.xmax(), bbox2.xmax()));
intersect_bbox.set_ymax(std::min(bbox1.ymax(), bbox2.ymax()));
intersect_bbox.xmin = std::max(bbox1.xmin, bbox2.xmin);
intersect_bbox.ymin = std::max(bbox1.ymin, bbox2.ymin);
intersect_bbox.xmax = std::min(bbox1.xmax, bbox2.xmax);
intersect_bbox.ymax = std::min(bbox1.ymax, bbox2.ymax);
}
float intersect_width, intersect_height;
intersect_width = intersect_bbox.xmax() - intersect_bbox.xmin();
intersect_height = intersect_bbox.ymax() - intersect_bbox.ymin();
intersect_width = intersect_bbox.xmax - intersect_bbox.xmin;
intersect_height = intersect_bbox.ymax - intersect_bbox.ymin;
if (intersect_width > 0 && intersect_height > 0)
{
if (!normalized)
......@@ -760,7 +775,7 @@ public:
}
};
float util::caffe_box_overlap(const caffe::NormalizedBBox& a, const caffe::NormalizedBBox& b)
float util::caffe_box_overlap(const util::NormalizedBBox& a, const util::NormalizedBBox& b)
{
return DetectionOutputLayerImpl::JaccardOverlap<true>(a, b);
}
......
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