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| SegmentationModel (string model, string config) |
| Create segmentation model from network represented in one of the supported formats. An order of model and config arguments does not matter.
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| SegmentationModel (string model) |
| Create segmentation model from network represented in one of the supported formats. An order of model and config arguments does not matter.
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| SegmentationModel (Net network) |
| Create model from deep learning network.
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void | segment (Mat frame, Mat mask) |
| Given the input frame, create input blob, run net.
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IntPtr | getNativeObjAddr () |
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| Model (string model, string config) |
| Create model from deep learning network represented in one of the supported formats. An order of model and config arguments does not matter.
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| Model (string model) |
| Create model from deep learning network represented in one of the supported formats. An order of model and config arguments does not matter.
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| Model (Net network) |
| Create model from deep learning network.
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Model | setInputSize (Size size) |
| Set input size for frame.
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Model | setInputSize (int width, int height) |
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Model | setInputMean (Scalar mean) |
| Set mean value for frame.
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Model | setInputScale (Scalar scale) |
| Set scalefactor value for frame.
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Model | setInputCrop (bool crop) |
| Set flag crop for frame.
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Model | setInputSwapRB (bool swapRB) |
| Set flag swapRB for frame.
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Model | setOutputNames (List< string > outNames) |
| Set output names for frame.
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void | setInputParams (double scale, Size size, Scalar mean, bool swapRB, bool crop) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, Size size, Scalar mean, bool swapRB) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, Size size, Scalar mean) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, Size size) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale) |
| Set preprocessing parameters for frame.
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void | setInputParams () |
| Set preprocessing parameters for frame.
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void | predict (Mat frame, List< Mat > outs) |
| Given the input frame, create input blob, run net and return the output blobs .
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Model | setPreferableBackend (int backendId) |
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Model | setPreferableTarget (int targetId) |
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Model | enableWinograd (bool useWinograd) |
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Model | setInputSize (in Vec2d size) |
| Set input size for frame.
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Model | setInputMean (in Vec4d mean) |
| Set mean value for frame.
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Model | setInputScale (in Vec4d scale) |
| Set scalefactor value for frame.
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void | setInputParams (double scale, in Vec2d size, in Vec4d mean, bool swapRB, bool crop) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in Vec2d size, in Vec4d mean, bool swapRB) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in Vec2d size, in Vec4d mean) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in Vec2d size) |
| Set preprocessing parameters for frame.
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Model | setInputSize (in(double width, double height) size) |
| Set input size for frame.
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Model | setInputMean (in(double v0, double v1, double v2, double v3) mean) |
| Set mean value for frame.
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Model | setInputScale (in(double v0, double v1, double v2, double v3) scale) |
| Set scalefactor value for frame.
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void | setInputParams (double scale, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB, bool crop) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in(double width, double height) size) |
| Set preprocessing parameters for frame.
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void | Dispose () |
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void | ThrowIfDisposed () |
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This class represents high-level API for segmentation models.
SegmentationModel allows to set params for preprocessing input image. SegmentationModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and returns the class prediction for each pixel.