public class LBPHFaceRecognizer extends FaceRecognizer
Modifier | Constructor and Description |
---|---|
protected |
LBPHFaceRecognizer(long addr) |
Modifier and Type | Method and Description |
---|---|
static LBPHFaceRecognizer |
__fromPtr__(long addr) |
static LBPHFaceRecognizer |
create()
radius, the smoother the image but more spatial information you can get.
|
static LBPHFaceRecognizer |
create(int radius) |
static LBPHFaceRecognizer |
create(int radius,
int neighbors) |
static LBPHFaceRecognizer |
create(int radius,
int neighbors,
int grid_x) |
static LBPHFaceRecognizer |
create(int radius,
int neighbors,
int grid_x,
int grid_y) |
static LBPHFaceRecognizer |
create(int radius,
int neighbors,
int grid_x,
int grid_y,
double threshold) |
protected void |
finalize() |
int |
getGridX()
SEE: setGridX
|
int |
getGridY()
SEE: setGridY
|
List<Mat> |
getHistograms() |
Mat |
getLabels() |
int |
getNeighbors()
SEE: setNeighbors
|
int |
getRadius()
SEE: setRadius
|
double |
getThreshold()
SEE: setThreshold
|
void |
setGridX(int val)
getGridX SEE: getGridX
|
void |
setGridY(int val)
getGridY SEE: getGridY
|
void |
setNeighbors(int val)
getNeighbors SEE: getNeighbors
|
void |
setRadius(int val)
getRadius SEE: getRadius
|
void |
setThreshold(double val)
getThreshold SEE: getThreshold
|
getLabelInfo, getLabelsByString, predict_collect, predict_label, predict, read, setLabelInfo, train, update, write
clear, empty, getDefaultName, getNativeObjAddr, save
public static LBPHFaceRecognizer __fromPtr__(long addr)
public Mat getLabels()
public static LBPHFaceRecognizer create(int radius, int neighbors, int grid_x, int grid_y, double threshold)
radius
- The radius used for building the Circular Local Binary Pattern. The greater the
radius, the smoother the image but more spatial information you can get.neighbors
- The number of sample points to build a Circular Local Binary Pattern from. An
appropriate value is to use 8
sample points. Keep in mind: the more sample points you include,
the higher the computational cost.grid_x
- The number of cells in the horizontal direction, 8 is a common value used in
publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
feature vector.grid_y
- The number of cells in the vertical direction, 8 is a common value used in
publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
feature vector.threshold
- The threshold applied in the prediction. If the distance to the nearest neighbor
is larger than the threshold, this method returns -1.
### Notes:
public static LBPHFaceRecognizer create(int radius, int neighbors, int grid_x, int grid_y)
radius
- The radius used for building the Circular Local Binary Pattern. The greater the
radius, the smoother the image but more spatial information you can get.neighbors
- The number of sample points to build a Circular Local Binary Pattern from. An
appropriate value is to use 8
sample points. Keep in mind: the more sample points you include,
the higher the computational cost.grid_x
- The number of cells in the horizontal direction, 8 is a common value used in
publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
feature vector.grid_y
- The number of cells in the vertical direction, 8 is a common value used in
publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
feature vector.
is larger than the threshold, this method returns -1.
### Notes:
public static LBPHFaceRecognizer create(int radius, int neighbors, int grid_x)
radius
- The radius used for building the Circular Local Binary Pattern. The greater the
radius, the smoother the image but more spatial information you can get.neighbors
- The number of sample points to build a Circular Local Binary Pattern from. An
appropriate value is to use 8
sample points. Keep in mind: the more sample points you include,
the higher the computational cost.grid_x
- The number of cells in the horizontal direction, 8 is a common value used in
publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
feature vector.
publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
feature vector.
is larger than the threshold, this method returns -1.
### Notes:
public static LBPHFaceRecognizer create(int radius, int neighbors)
radius
- The radius used for building the Circular Local Binary Pattern. The greater the
radius, the smoother the image but more spatial information you can get.neighbors
- The number of sample points to build a Circular Local Binary Pattern from. An
appropriate value is to use 8
sample points. Keep in mind: the more sample points you include,
the higher the computational cost.
publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
feature vector.
publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
feature vector.
is larger than the threshold, this method returns -1.
### Notes:
public static LBPHFaceRecognizer create(int radius)
radius
- The radius used for building the Circular Local Binary Pattern. The greater the
radius, the smoother the image but more spatial information you can get.
appropriate value is to use 8
sample points. Keep in mind: the more sample points you include,
the higher the computational cost.
publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
feature vector.
publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
feature vector.
is larger than the threshold, this method returns -1.
### Notes:
public static LBPHFaceRecognizer create()
8
sample points. Keep in mind: the more sample points you include,
the higher the computational cost.
publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
feature vector.
publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
feature vector.
is larger than the threshold, this method returns -1.
### Notes:
public double getThreshold()
public int getGridX()
public int getGridY()
public int getNeighbors()
public int getRadius()
public void setGridX(int val)
val
- automatically generatedpublic void setGridY(int val)
val
- automatically generatedpublic void setNeighbors(int val)
val
- automatically generatedpublic void setRadius(int val)
val
- automatically generatedpublic void setThreshold(double val)
val
- automatically generatedprotected void finalize() throws Throwable
finalize
in class FaceRecognizer
Throwable
Generated on Wed Oct 9 2019 23:24:43 UTC / OpenCV 4.1.2