Commit 61e9617d authored by Kurnianggoro's avatar Kurnianggoro

Fixing warnings

parent 318415f2
...@@ -1200,6 +1200,9 @@ class CV_EXPORTS_W TrackerKCF : public Tracker ...@@ -1200,6 +1200,9 @@ class CV_EXPORTS_W TrackerKCF : public Tracker
public: public:
/** /**
* \brief Feature type to be used in the tracking grayscale, colornames, compressed color-names * \brief Feature type to be used in the tracking grayscale, colornames, compressed color-names
* The modes available now:
- "GRAY" -- Use grayscale values as the feature
- "CN" -- Color-names feature
*/ */
enum MODE {GRAY, CN, CN2}; enum MODE {GRAY, CN, CN2};
...@@ -1207,22 +1210,6 @@ class CV_EXPORTS_W TrackerKCF : public Tracker ...@@ -1207,22 +1210,6 @@ class CV_EXPORTS_W TrackerKCF : public Tracker
{ {
/** /**
* \brief Constructor * \brief Constructor
* \param sigma bandwidth of the gaussian kernel
* \param lambda regularization coefficient
* \param interp_factor inear interpolation factor for model updating
* \param output_sigma_factor spatial bandwidth (proportional to target)
* \param pca_learning_rate learning rate of the compression method
* \param resize activate the resize feature to improve the processing speed
* \param split_coeff split the training coefficients into two matrices
* \param wrap_kernel wrap around the kernel values
* \param compressFeature activate pca method to compress the features
* \param max_patch_size threshold for the ROI size
* \param compressed_size feature size after compression
* \param descriptor descriptor type
* The modes available now:
- "GRAY" -- Use grayscale values as the feature
- "CN" -- Color-names feature
- "CN2" -- Compressed color-names feature
*/ */
Params(); Params();
...@@ -1244,7 +1231,7 @@ class CV_EXPORTS_W TrackerKCF : public Tracker ...@@ -1244,7 +1231,7 @@ class CV_EXPORTS_W TrackerKCF : public Tracker
bool resize; //!< activate the resize feature to improve the processing speed bool resize; //!< activate the resize feature to improve the processing speed
bool split_coeff; //!< split the training coefficients into two matrices bool split_coeff; //!< split the training coefficients into two matrices
bool wrap_kernel; //!< wrap around the kernel values bool wrap_kernel; //!< wrap around the kernel values
bool compress_feature; //!< activate pca method to compress the features bool compress_feature; //!< activate the pca method to compress the features
int max_patch_size; //!< threshold for the ROI size int max_patch_size; //!< threshold for the ROI size
int compressed_size; //!< feature size after compression int compressed_size; //!< feature size after compression
MODE descriptor; //!< descriptor type MODE descriptor; //!< descriptor type
......
...@@ -165,16 +165,16 @@ Rect2d BoxExtractor::extract(const std::string& windowName, Mat img, bool showCr ...@@ -165,16 +165,16 @@ Rect2d BoxExtractor::extract(const std::string& windowName, Mat img, bool showCr
// horizontal line // horizontal line
line( line(
params.image, params.image,
Point(params.box.x,params.box.y+0.5*params.box.height), Point(params.box.x,params.box.y+(int)(0.5*params.box.height)),
Point(params.box.x+params.box.width,params.box.y+0.5*params.box.height), Point(params.box.x+params.box.width,params.box.y+(int)(0.5*params.box.height)),
Scalar(255,0,0),2,1 Scalar(255,0,0),2,1
); );
// vertical line // vertical line
line( line(
params.image, params.image,
Point(params.box.x+0.5*params.box.width,params.box.y), Point(params.box.x+(int)(0.5*params.box.width),params.box.y),
Point(params.box.x+0.5*params.box.width,params.box.y+params.box.height), Point(params.box.x+(int)(0.5*params.box.width),params.box.y+params.box.height),
Scalar(255,0,0),2,1 Scalar(255,0,0),2,1
); );
} }
......
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