| Package | Description |
|---|---|
| org.openimaj.image.objectdetection.haar | |
| org.openimaj.image.objectdetection.haar.training |
| Modifier and Type | Method and Description |
|---|---|
static HaarFeature |
HaarFeature.create(boolean tilted,
int x0,
int y0,
int w0,
int h0,
float wt0,
int x1,
int y1,
int w1,
int h1,
float wt1)
Construct a feature with the given parameters.
|
static HaarFeature |
HaarFeature.create(boolean tilted,
int x0,
int y0,
int w0,
int h0,
float wt0,
int x1,
int y1,
int w1,
int h1,
float wt1,
int x2,
int y2,
int w2,
int h2,
float wt2)
Construct a feature with the given parameters.
|
static HaarFeature |
HaarFeature.create(List<WeightedRectangle> rectList,
boolean tilted)
Create a feature from the given data.
|
| Constructor and Description |
|---|
HaarFeatureClassifier(HaarFeature feature,
float threshold,
Classifier left,
Classifier right)
Construct with the given feature, threshold and left/right nodes.
|
| Modifier and Type | Method and Description |
|---|---|
abstract HaarFeature |
HaarFeatureType.create(int x,
int y,
int dx,
int dy,
int winWidth,
int winHeight)
Create a feature.
|
HaarFeature |
BasicTrainingData.getFeature(int dimension) |
HaarFeature |
CachedTrainingData.getFeature(int dimension) |
| Modifier and Type | Method and Description |
|---|---|
static List<HaarFeature> |
HaarFeatureType.generateFeatures(int winWidth,
int winHeight,
Collection<HaarFeatureType> types)
Generate features of the given types for all possible locations and sizes
in the given window bounds.
|
static List<HaarFeature> |
HaarFeatureType.generateFeatures(int winWidth,
int winHeight,
HaarFeatureType... types)
Generate features of the given types for all possible locations and sizes
in the given window bounds.
|
| Constructor and Description |
|---|
BasicTrainingData(List<SummedSqTiltAreaTable> positive,
List<SummedSqTiltAreaTable> negative,
List<HaarFeature> features) |
CachedTrainingData(List<SummedSqTiltAreaTable> positive,
List<SummedSqTiltAreaTable> negative,
List<HaarFeature> features) |