static IntelligentScissorsMB |
IntelligentScissorsMB.__fromPtr__(long addr) |
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IntelligentScissorsMB |
IntelligentScissorsMB.applyImage(Mat image) |
Specify input image and extract image features
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IntelligentScissorsMB |
IntelligentScissorsMB.applyImageFeatures(Mat non_edge,
Mat gradient_direction,
Mat gradient_magnitude) |
Specify custom features of imput image
Customized advanced variant of applyImage() call.
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IntelligentScissorsMB |
IntelligentScissorsMB.applyImageFeatures(Mat non_edge,
Mat gradient_direction,
Mat gradient_magnitude,
Mat image) |
Specify custom features of imput image
Customized advanced variant of applyImage() call.
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IntelligentScissorsMB |
IntelligentScissorsMB.setEdgeFeatureCannyParameters(double threshold1,
double threshold2) |
Switch edge feature extractor to use Canny edge detector
Note: "Laplacian Zero-Crossing" feature extractor is used by default (following to original article)
SEE: Canny
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IntelligentScissorsMB |
IntelligentScissorsMB.setEdgeFeatureCannyParameters(double threshold1,
double threshold2,
int apertureSize) |
Switch edge feature extractor to use Canny edge detector
Note: "Laplacian Zero-Crossing" feature extractor is used by default (following to original article)
SEE: Canny
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IntelligentScissorsMB |
IntelligentScissorsMB.setEdgeFeatureCannyParameters(double threshold1,
double threshold2,
int apertureSize,
boolean L2gradient) |
Switch edge feature extractor to use Canny edge detector
Note: "Laplacian Zero-Crossing" feature extractor is used by default (following to original article)
SEE: Canny
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IntelligentScissorsMB |
IntelligentScissorsMB.setEdgeFeatureZeroCrossingParameters() |
Switch to "Laplacian Zero-Crossing" edge feature extractor and specify its parameters
This feature extractor is used by default according to article.
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IntelligentScissorsMB |
IntelligentScissorsMB.setEdgeFeatureZeroCrossingParameters(float gradient_magnitude_min_value) |
Switch to "Laplacian Zero-Crossing" edge feature extractor and specify its parameters
This feature extractor is used by default according to article.
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IntelligentScissorsMB |
IntelligentScissorsMB.setGradientMagnitudeMaxLimit() |
Specify gradient magnitude max value threshold
Zero limit value is used to disable gradient magnitude thresholding (default behavior, as described in original article).
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IntelligentScissorsMB |
IntelligentScissorsMB.setGradientMagnitudeMaxLimit(float gradient_magnitude_threshold_max) |
Specify gradient magnitude max value threshold
Zero limit value is used to disable gradient magnitude thresholding (default behavior, as described in original article).
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IntelligentScissorsMB |
IntelligentScissorsMB.setWeights(float weight_non_edge,
float weight_gradient_direction,
float weight_gradient_magnitude) |
Specify weights of feature functions
Consider keeping weights normalized (sum of weights equals to 1.0)
Discrete dynamic programming (DP) goal is minimization of costs between pixels.
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