@Namespace(value="cv::dnn") @NoOffset @Properties(inherit=opencv_dnn.class) public class Model extends Net
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter
Constructor and Description |
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Model()
\brief Default constructor.
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Model(BytePointer model) |
Model(BytePointer model,
BytePointer config)
\brief Create model from deep learning network represented in one of the supported formats.
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Model(long size)
Native array allocator.
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Model(Net network)
\brief Create model from deep learning network.
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Model(Pointer p)
Pointer cast constructor.
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Model(String model) |
Model(String model,
String config) |
Modifier and Type | Method and Description |
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Model |
position(long position) |
void |
predict(GpuMat frame,
GpuMatVector outs) |
void |
predict(GpuMat frame,
MatVector outs) |
void |
predict(GpuMat frame,
UMatVector outs) |
void |
predict(Mat frame,
GpuMatVector outs) |
void |
predict(Mat frame,
MatVector outs)
\brief Given the \p input frame, create input blob, run net and return the output \p blobs.
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void |
predict(Mat frame,
UMatVector outs) |
void |
predict(UMat frame,
GpuMatVector outs) |
void |
predict(UMat frame,
MatVector outs) |
void |
predict(UMat frame,
UMatVector outs) |
Model |
setInputCrop(boolean crop)
\brief Set flag crop for frame.
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Model |
setInputMean(Scalar mean)
\brief Set mean value for frame.
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void |
setInputParams() |
void |
setInputParams(double scale,
Size size,
Scalar mean,
boolean swapRB,
boolean crop)
\brief Set preprocessing parameters for frame.
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Model |
setInputScale(double scale)
\brief Set scalefactor value for frame.
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Model |
setInputSize(int width,
int height)
\brief Set input size for frame.
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Model |
setInputSize(Size size)
\brief Set input size for frame.
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Model |
setInputSwapRB(boolean swapRB)
\brief Set flag swapRB for frame.
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addLayer, addLayer, addLayerToPrev, addLayerToPrev, connect, connect, connect, dump, dumpToFile, dumpToFile, empty, enableFusion, forward, forward, forward, forward, forward, forward, forward, forward, forward, forward, forward, forward, forward, forward, forward, forwardAndRetrieve, forwardAsync, forwardAsync, forwardAsync, getFLOPS, getFLOPS, getFLOPS, getFLOPS, getLayer, getLayerId, getLayerId, getLayerNames, getLayersCount, getLayersCount, getLayerShapes, getLayerShapes, getLayersShapes, getLayersShapes, getLayersShapes, getLayersShapes, getLayersShapes, getLayersShapes, getLayerTypes, getMemoryConsumption, getMemoryConsumption, getMemoryConsumption, getMemoryConsumption, getMemoryConsumption, getMemoryConsumption, getMemoryConsumption, getMemoryConsumption, getMemoryConsumption, getMemoryConsumption, getParam, getParam, getPerfProfile, getPerfProfile, getPerfProfile, getUnconnectedOutLayers, getUnconnectedOutLayersNames, readFromModelOptimizer, readFromModelOptimizer, readFromModelOptimizer, readFromModelOptimizer, readFromModelOptimizer, readFromModelOptimizer, readFromModelOptimizer, setHalideScheduler, setHalideScheduler, setInput, setInput, setInput, setInput, setInput, setInput, setInput, setInput, setInput, setInputShape, setInputShape, setInputsNames, setParam, setPreferableBackend, setPreferableTarget
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero
public Model(Pointer p)
Pointer.Pointer(Pointer)
.public Model(long size)
Pointer.position(long)
.public Model()
public Model(@opencv_core.Str BytePointer model, @opencv_core.Str BytePointer config)
model
- [in] Binary file contains trained weights.config
- [in] Text file contains network configuration.public Model(@opencv_core.Str BytePointer model)
public Model(@opencv_core.Str String model, @opencv_core.Str String config)
public Model(@opencv_core.Str String model)
@ByRef public Model setInputSize(@Const @ByRef Size size)
size
- [in] New input size.
\note If shape of the new blob less than 0, then frame size not change.@ByRef public Model setInputSize(int width, int height)
width
- [in] New input width.height
- [in] New input height.
\note If shape of the new blob less than 0,
then frame size not change.@ByRef public Model setInputMean(@Const @ByRef Scalar mean)
mean
- [in] Scalar with mean values which are subtracted from channels.@ByRef public Model setInputScale(double scale)
scale
- [in] Multiplier for frame values.@ByRef public Model setInputCrop(@Cast(value="bool") boolean crop)
crop
- [in] Flag which indicates whether image will be cropped after resize or not.@ByRef public Model setInputSwapRB(@Cast(value="bool") boolean swapRB)
swapRB
- [in] Flag which indicates that swap first and last channels.public void setInputParams(double scale, @Const @ByRef(nullValue="cv::Size()") Size size, @Const @ByRef(nullValue="cv::Scalar()") Scalar mean, @Cast(value="bool") boolean swapRB, @Cast(value="bool") boolean crop)
size
- [in] New input size.mean
- [in] Scalar with mean values which are subtracted from channels.scale
- [in] Multiplier for frame values.swapRB
- [in] Flag which indicates that swap first and last channels.crop
- [in] Flag which indicates whether image will be cropped after resize or not.
blob(n, c, y, x) = scale * resize( frame(y, x, c) ) - mean(c) )public void setInputParams()
public void predict(@ByVal Mat frame, @ByVal MatVector outs)
frame
- [in] The input image.outs
- [out] Allocated output blobs, which will store results of the computation.public void predict(@ByVal Mat frame, @ByVal UMatVector outs)
public void predict(@ByVal Mat frame, @ByVal GpuMatVector outs)
public void predict(@ByVal UMat frame, @ByVal UMatVector outs)
public void predict(@ByVal UMat frame, @ByVal GpuMatVector outs)
public void predict(@ByVal GpuMat frame, @ByVal UMatVector outs)
public void predict(@ByVal GpuMat frame, @ByVal GpuMatVector outs)
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