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Merge pull request #425 from berak:python_tracking

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pull/446/head
Vadim Pisarevsky 9 years ago
parent c8053da4f2 59e9a9ae21
commit bcbbb63b79
6 changed files with 108 additions and 43 deletions
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  1. 2
      modules/tracking/CMakeLists.txt
  2. 2
      modules/tracking/include/opencv2/tracking/onlineMIL.hpp
  3. 74
      modules/tracking/include/opencv2/tracking/tracker.hpp
  4. 35
      modules/tracking/samples/multitracker.py
  5. 30
      modules/tracking/samples/tracker.py
  6. 8
      modules/tracking/src/roiSelector.cpp

2
modules/tracking/CMakeLists.txt
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@ -1,2 +1,2 @@
set(the_description "Tracking API")
ocv_define_module(tracking opencv_imgproc opencv_core opencv_video opencv_highgui opencv_datasets)
ocv_define_module(tracking opencv_imgproc opencv_core opencv_video opencv_highgui opencv_datasets WRAP python)

2
modules/tracking/include/opencv2/tracking/onlineMIL.hpp
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@ -58,7 +58,7 @@ namespace cv
class ClfOnlineStump;
class ClfMilBoost
class CV_EXPORTS ClfMilBoost
{
public:
struct CV_EXPORTS Params

74
modules/tracking/include/opencv2/tracking/tracker.hpp
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@ -74,7 +74,7 @@ namespace cv
/** @brief Abstract base class for TrackerFeature that represents the feature.
*/
class CV_EXPORTS_W TrackerFeature
class CV_EXPORTS TrackerFeature
{
public:
virtual ~TrackerFeature();
@ -131,7 +131,7 @@ TrackerFeatureSet is an aggregation of TrackerFeature
TrackerFeature
*/
class CV_EXPORTS_W TrackerFeatureSet
class CV_EXPORTS TrackerFeatureSet
{
public:
@ -209,7 +209,7 @@ class CV_EXPORTS_W TrackerFeatureSet
/** @brief Abstract base class for TrackerSamplerAlgorithm that represents the algorithm for the specific
sampler.
*/
class CV_EXPORTS_W TrackerSamplerAlgorithm
class CV_EXPORTS TrackerSamplerAlgorithm
{
public:
/**
@ -261,7 +261,7 @@ TrackerSampler is an aggregation of TrackerSamplerAlgorithm
@sa
TrackerSamplerAlgorithm
*/
class CV_EXPORTS_W TrackerSampler
class CV_EXPORTS TrackerSampler
{
public:
@ -334,7 +334,7 @@ See @cite AAM \f$\hat{x}^{i}_{k}\f$ all the states candidates.
Inherits this class with your Target state, In own implementation you can add scale variation,
width, height, orientation, etc.
*/
class CV_EXPORTS_W TrackerTargetState
class CV_EXPORTS TrackerTargetState
{
public:
virtual ~TrackerTargetState()
@ -403,7 +403,7 @@ See @cite AAM State estimator
See @cite AMVOT Statistical modeling (Fig. 3), Table III (generative) - IV (discriminative) - V (hybrid)
*/
class CV_EXPORTS_W TrackerStateEstimator
class CV_EXPORTS TrackerStateEstimator
{
public:
virtual ~TrackerStateEstimator();
@ -449,7 +449,7 @@ See @cite AAM Ak
Inherits this with your TrackerModel
*/
class CV_EXPORTS_W TrackerModel
class CV_EXPORTS TrackerModel
{
public:
@ -539,7 +539,7 @@ class CV_EXPORTS_W Tracker : public virtual Algorithm
@return True if initialization went succesfully, false otherwise
*/
bool init( const Mat& image, const Rect2d& boundingBox );
CV_WRAP bool init( const Mat& image, const Rect2d& boundingBox );
/** @brief Update the tracker, find the new most likely bounding box for the target
@param image The current frame
@ -550,7 +550,7 @@ class CV_EXPORTS_W Tracker : public virtual Algorithm
current frame. Note, that latter *does not* imply that tracker has failed, maybe target is indeed
missing from the frame (say, out of sight)
*/
bool update( const Mat& image, Rect2d& boundingBox );
CV_WRAP bool update( const Mat& image, CV_OUT Rect2d& boundingBox );
/** @brief Creates a tracker by its name.
@param trackerType Tracker type
@ -560,7 +560,7 @@ class CV_EXPORTS_W Tracker : public virtual Algorithm
- "MIL" -- TrackerMIL
- "BOOSTING" -- TrackerBoosting
*/
static Ptr<Tracker> create( const String& trackerType );
CV_WRAP static Ptr<Tracker> create( const String& trackerType );
virtual void read( const FileNode& fn )=0;
virtual void write( FileStorage& fs ) const=0;
@ -587,7 +587,7 @@ class CV_EXPORTS_W Tracker : public virtual Algorithm
/** @brief TrackerStateEstimator based on Boosting
*/
class CV_EXPORTS_W TrackerStateEstimatorMILBoosting : public TrackerStateEstimator
class CV_EXPORTS TrackerStateEstimatorMILBoosting : public TrackerStateEstimator
{
public:
@ -664,7 +664,7 @@ class CV_EXPORTS_W TrackerStateEstimatorMILBoosting : public TrackerStateEstimat
/** @brief TrackerStateEstimatorAdaBoosting based on ADA-Boosting
*/
class CV_EXPORTS_W TrackerStateEstimatorAdaBoosting : public TrackerStateEstimator
class CV_EXPORTS TrackerStateEstimatorAdaBoosting : public TrackerStateEstimator
{
public:
/** @brief Implementation of the target state for TrackerAdaBoostingTargetState
@ -774,7 +774,7 @@ class CV_EXPORTS_W TrackerStateEstimatorAdaBoosting : public TrackerStateEstimat
/**
* \brief TrackerStateEstimator based on SVM
*/
class CV_EXPORTS_W TrackerStateEstimatorSVM : public TrackerStateEstimator
class CV_EXPORTS TrackerStateEstimatorSVM : public TrackerStateEstimator
{
public:
TrackerStateEstimatorSVM();
@ -789,7 +789,7 @@ class CV_EXPORTS_W TrackerStateEstimatorSVM : public TrackerStateEstimator
/** @brief TrackerSampler based on CSC (current state centered), used by MIL algorithm TrackerMIL
*/
class CV_EXPORTS_W TrackerSamplerCSC : public TrackerSamplerAlgorithm
class CV_EXPORTS TrackerSamplerCSC : public TrackerSamplerAlgorithm
{
public:
enum
@ -847,7 +847,7 @@ class CV_EXPORTS_W TrackerSamplerCSC : public TrackerSamplerAlgorithm
/** @brief TrackerSampler based on CS (current state), used by algorithm TrackerBoosting
*/
class CV_EXPORTS_W TrackerSamplerCS : public TrackerSamplerAlgorithm
class CV_EXPORTS TrackerSamplerCS : public TrackerSamplerAlgorithm
{
public:
enum
@ -914,7 +914,7 @@ It should be noted, that the definition of "similarity" between two rectangles i
their histograms. As experiments show, tracker is *not* very succesfull if target is assumed to
strongly change its dimensions.
*/
class CV_EXPORTS_W TrackerSamplerPF : public TrackerSamplerAlgorithm
class CV_EXPORTS TrackerSamplerPF : public TrackerSamplerAlgorithm
{
public:
/** @brief This structure contains all the parameters that can be varied during the course of sampling
@ -949,7 +949,7 @@ private:
/**
* \brief TrackerFeature based on Feature2D
*/
class CV_EXPORTS_W TrackerFeatureFeature2d : public TrackerFeature
class CV_EXPORTS TrackerFeatureFeature2d : public TrackerFeature
{
public:
@ -976,7 +976,7 @@ class CV_EXPORTS_W TrackerFeatureFeature2d : public TrackerFeature
/**
* \brief TrackerFeature based on HOG
*/
class CV_EXPORTS_W TrackerFeatureHOG : public TrackerFeature
class CV_EXPORTS TrackerFeatureHOG : public TrackerFeature
{
public:
@ -995,7 +995,7 @@ class CV_EXPORTS_W TrackerFeatureHOG : public TrackerFeature
/** @brief TrackerFeature based on HAAR features, used by TrackerMIL and many others algorithms
@note HAAR features implementation is copied from apps/traincascade and modified according to MIL
*/
class CV_EXPORTS_W TrackerFeatureHAAR : public TrackerFeature
class CV_EXPORTS TrackerFeatureHAAR : public TrackerFeature
{
public:
struct CV_EXPORTS Params
@ -1057,7 +1057,7 @@ class CV_EXPORTS_W TrackerFeatureHAAR : public TrackerFeature
/**
* \brief TrackerFeature based on LBP
*/
class CV_EXPORTS_W TrackerFeatureLBP : public TrackerFeature
class CV_EXPORTS TrackerFeatureLBP : public TrackerFeature
{
public:
@ -1083,7 +1083,7 @@ based on @cite MIL .
Original code can be found here <http://vision.ucsd.edu/~bbabenko/project_miltrack.shtml>
*/
class CV_EXPORTS_W TrackerMIL : public Tracker
class CV_EXPORTS TrackerMIL : public Tracker
{
public:
struct CV_EXPORTS Params
@ -1113,7 +1113,7 @@ class CV_EXPORTS_W TrackerMIL : public Tracker
The classifier uses the surrounding background as negative examples in update step to avoid the
drifting problem. The implementation is based on @cite OLB .
*/
class CV_EXPORTS_W TrackerBoosting : public Tracker
class CV_EXPORTS TrackerBoosting : public Tracker
{
public:
struct CV_EXPORTS Params
@ -1151,7 +1151,7 @@ by authors to outperform MIL). During the implementation period the code at
<http://www.aonsquared.co.uk/node/5>, the courtesy of the author Arthur Amarra, was used for the
reference purpose.
*/
class CV_EXPORTS_W TrackerMedianFlow : public Tracker
class CV_EXPORTS TrackerMedianFlow : public Tracker
{
public:
struct CV_EXPORTS Params
@ -1180,7 +1180,7 @@ The Median Flow algorithm (see cv::TrackerMedianFlow) was chosen as a tracking c
implementation, following authors. Tracker is supposed to be able to handle rapid motions, partial
occlusions, object absence etc.
*/
class CV_EXPORTS_W TrackerTLD : public Tracker
class CV_EXPORTS TrackerTLD : public Tracker
{
public:
struct CV_EXPORTS Params
@ -1202,7 +1202,7 @@ class CV_EXPORTS_W TrackerTLD : public Tracker
* as well as the matlab implementation. For more information about KCF with color-names features, please refer to
* <http://www.cvl.isy.liu.se/research/objrec/visualtracking/colvistrack/index.html>.
*/
class CV_EXPORTS_W TrackerKCF : public Tracker
class CV_EXPORTS TrackerKCF : public Tracker
{
public:
/**
@ -1271,7 +1271,7 @@ public:
* In the case of trackerType is given, it will be set as the default algorithm for all trackers.
* @param trackerType the name of the tracker algorithm to be used
*/
MultiTracker(const String& trackerType = "");
CV_WRAP MultiTracker(const String& trackerType = "");
/**
* \brief Destructor
@ -1284,7 +1284,7 @@ public:
* @param image input image
* @param boundingBox a rectangle represents ROI of the tracked object
*/
bool add(const Mat& image, const Rect2d& boundingBox);
CV_WRAP bool add(const Mat& image, const Rect2d& boundingBox);
/**
* \brief Add a new object to be tracked.
@ -1292,7 +1292,7 @@ public:
* @param image input image
* @param boundingBox a rectangle represents ROI of the tracked object
*/
bool add(const String& trackerType, const Mat& image, const Rect2d& boundingBox);
CV_WRAP bool add(const String& trackerType, const Mat& image, const Rect2d& boundingBox);
/**
* \brief Add a set of objects to be tracked.
@ -1300,14 +1300,14 @@ public:
* @param image input image
* @param boundingBox list of the tracked objects
*/
bool add(const String& trackerType, const Mat& image, std::vector<Rect2d> boundingBox);
CV_WRAP bool add(const String& trackerType, const Mat& image, std::vector<Rect2d> boundingBox);
/**
* \brief Add a set of objects to be tracked using the defaultAlgorithm tracker.
* @param image input image
* @param boundingBox list of the tracked objects
*/
bool add(const Mat& image, std::vector<Rect2d> boundingBox);
CV_WRAP bool add(const Mat& image, std::vector<Rect2d> boundingBox);
/**
* \brief Update the current tracking status.
@ -1324,7 +1324,7 @@ public:
* @param image input image
* @param boundingBox the tracking result, represent a list of ROIs of the tracked objects.
*/
bool update(const Mat& image, std::vector<Rect2d> & boundingBox);
CV_WRAP bool update(const Mat& image, CV_OUT std::vector<Rect2d> & boundingBox);
protected:
//!< storage for the tracker algorithms.
@ -1337,8 +1337,8 @@ protected:
class ROISelector {
public:
Rect2d select(Mat img, bool fromCenter = true);
Rect2d select(const std::string& windowName, Mat img, bool showCrossair = true, bool fromCenter = true);
void select(const std::string& windowName, Mat img, std::vector<Rect2d> & boundingBox, bool fromCenter = true);
Rect2d select(const cv::String& windowName, Mat img, bool showCrossair = true, bool fromCenter = true);
void select(const cv::String& windowName, Mat img, std::vector<Rect2d> & boundingBox, bool fromCenter = true);
struct handlerT{
// basic parameters
@ -1366,8 +1366,8 @@ private:
};
Rect2d CV_EXPORTS_W selectROI(Mat img, bool fromCenter = true);
Rect2d CV_EXPORTS_W selectROI(const std::string& windowName, Mat img, bool showCrossair = true, bool fromCenter = true);
void CV_EXPORTS_W selectROI(const std::string& windowName, Mat img, std::vector<Rect2d> & boundingBox, bool fromCenter = true);
Rect2d CV_EXPORTS_W selectROI(const cv::String& windowName, Mat img, bool showCrossair = true, bool fromCenter = true);
void CV_EXPORTS_W selectROI(const cv::String& windowName, Mat img, std::vector<Rect2d> & boundingBox, bool fromCenter = true);
/************************************ Multi-Tracker Classes ---By Tyan Vladimir---************************************/
@ -1376,7 +1376,7 @@ void CV_EXPORTS_W selectROI(const std::string& windowName, Mat img, std::vector<
@sa Tracker, MultiTrackerTLD
*/
class CV_EXPORTS_W MultiTracker_Alt
class CV_EXPORTS MultiTracker_Alt
{
public:
/** @brief Constructor for Multitracker
@ -1433,7 +1433,7 @@ occlusions, object absence etc.
@sa Tracker, MultiTracker, TrackerTLD
*/
class CV_EXPORTS_W MultiTrackerTLD : public MultiTracker_Alt
class CV_EXPORTS MultiTrackerTLD : public MultiTracker_Alt
{
public:
/** @brief Update all trackers from the tracking-list, find a new most likely bounding boxes for the targets by

35
modules/tracking/samples/multitracker.py
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@ -0,0 +1,35 @@
import numpy as np
import cv2
cv2.namedWindow("tracking")
camera = cv2.VideoCapture("E:/code/opencv/samples/data/768x576.avi")
tracker = cv2.MultiTracker("MIL")
bbox1 = (638.0,230.0,56.0,101.0)
bbox2 = (240.0,210.0,60.0,104.0)
bbox3 = (486.0,149.0,54.0,83.0)
init_once = False
while camera.isOpened():
ok, image=camera.read()
if not ok:
print 'no image read'
break
if not init_once:
# add a list of boxes:
ok = tracker.add(image, (bbox1,bbox2))
# or add single box:
ok = tracker.add(image, bbox3)
init_once = True
ok, boxes = tracker.update(image)
print ok, boxes
for newbox in boxes:
p1 = (int(newbox[0]), int(newbox[1]))
p2 = (int(newbox[0] + newbox[2]), int(newbox[1] + newbox[3]))
cv2.rectangle(image, p1, p2, (200,0,0))
cv2.imshow("tracking", image)
k = cv2.waitKey(1) & 0xff
if k == 27 : break # esc pressed

30
modules/tracking/samples/tracker.py
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@ -0,0 +1,30 @@
import numpy as np
import cv2
cv2.namedWindow("tracking")
camera = cv2.VideoCapture("E:/code/opencv/samples/data/768x576.avi")
bbox = (638.0,230.0,56.0,101.0)
tracker = cv2.Tracker_create("MIL")
init_once = False
while camera.isOpened():
ok, image=camera.read()
if not ok:
print 'no image read'
break
if not init_once:
ok = tracker.init(image, bbox)
init_once = True
ok, newbox = tracker.update(image)
print ok, newbox
if ok:
p1 = (int(newbox[0]), int(newbox[1]))
p2 = (int(newbox[0] + newbox[2]), int(newbox[1] + newbox[3]))
cv2.rectangle(image, p1, p2, (200,0,0))
cv2.imshow("tracking", image)
k = cv2.waitKey(1) & 0xff
if k == 27 : break # esc pressed

8
modules/tracking/src/roiSelector.cpp
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@ -91,7 +91,7 @@ namespace cv {
return select("ROI selector", img, fromCenter);
}
Rect2d ROISelector::select(const std::string& windowName, Mat img, bool showCrossair, bool fromCenter){
Rect2d ROISelector::select(const cv::String& windowName, Mat img, bool showCrossair, bool fromCenter){
key=0;
@ -149,7 +149,7 @@ namespace cv {
return selectorParams.box;
}
void ROISelector::select(const std::string& windowName, Mat img, std::vector<Rect2d> & boundingBox, bool fromCenter){
void ROISelector::select(const cv::String& windowName, Mat img, std::vector<Rect2d> & boundingBox, bool fromCenter){
std::vector<Rect2d> box;
Rect2d temp;
key=0;
@ -172,12 +172,12 @@ namespace cv {
return _selector.select("ROI selector", img, true, fromCenter);
};
Rect2d selectROI(const std::string& windowName, Mat img, bool showCrossair, bool fromCenter){
Rect2d selectROI(const cv::String& windowName, Mat img, bool showCrossair, bool fromCenter){
printf("Select an object to track and then press SPACE or ENTER button!\n" );
return _selector.select(windowName,img, showCrossair, fromCenter);
};
void selectROI(const std::string& windowName, Mat img, std::vector<Rect2d> & boundingBox, bool fromCenter){
void selectROI(const cv::String& windowName, Mat img, std::vector<Rect2d> & boundingBox, bool fromCenter){
return _selector.select(windowName, img, boundingBox, fromCenter);
}

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