void IPLUndistort::init()
{
// init
_result = NULL;
// basic settings
setClassName("IPLUndistort");
setTitle("Undistort Image");
setDescription("The function transforms an image to compensate radial and tangential lens distortion.");
setCategory(IPLProcess::CATEGORY_GEOMETRY);
setOpenCVSupport(IPLProcess::OPENCV_ONLY);
setKeywords("distortion, undistortion, barrel, lens correction");
// inputs and outputs
addInput("Image", IPL_IMAGE_COLOR);
addOutput("Image", IPL_IMAGE_COLOR);
// properties
addProcessPropertyInt("f", "f", "Focal Length", 1000, IPL_WIDGET_SLIDER, 0, 10000.0);
addProcessPropertyDouble("p1", "p1", "", 0.0, IPL_WIDGET_SLIDER, -10.0, 10.0);
addProcessPropertyDouble("p2", "p2", "Tangential Distortion", 0.0, IPL_WIDGET_SLIDER, -10.0, 10.0);
addProcessPropertyDouble("k1", "k1", "", 0.0, IPL_WIDGET_SLIDER, -100.0, 100.0);
addProcessPropertyDouble("k2", "k2", "", 0.0, IPL_WIDGET_SLIDER, -100.0, 100.0);
addProcessPropertyDouble("k3", "k3", "Radial Distortion", 0.0, IPL_WIDGET_SLIDER, -100.0, 100.0);
}
void IPLCanny::init()
{
// init
_result = NULL;
_binaryImage = NULL;
_orientedImage = NULL;
// basic settings
setClassName("IPLCanny");
setTitle("Canny Edge Detector");
setCategory(IPLProcess::CATEGORY_LOCALOPERATIONS);
setOpenCVSupport(IPLOpenCVSupport::OPENCV_ONLY);
setDescription("The Canny edge detector delivers the magnitude and the gradient of the edge "
"image. Thresholding has to be done by an appropriate operator. The σ value "
"is used for both, smoothing and derivation operation.");
// inputs and outputs
addInput("Image", IPLData::IMAGE_COLOR);
addOutput("Magnitude", IPLImage::IMAGE_GRAYSCALE);
addOutput("Edge", IPLImage::IMAGE_GRAYSCALE);
addOutput("Gradient", IPLImage::IMAGE_GRAYSCALE);
// properties
addProcessPropertyInt("window", "Window", "", 3, IPL_WIDGET_SLIDER_ODD, 3, 7);
addProcessPropertyDouble("sigma", "Sigma", "", 1.5, IPL_WIDGET_SLIDER, 0.5, 10);
addProcessPropertyDouble("lowThreshold", "Low Threshold", "", 0.3, IPL_WIDGET_SLIDER, 0.0, 1.0);
addProcessPropertyDouble("highThreshold", "Hight Threshold", "Thresholds for the hysteresis procedure", 0.6, IPL_WIDGET_SLIDER, 0.0, 1.0);
}
void IPLMedian::init()
{
// init
_result = NULL;
// basic settings
setClassName("IPLMedian");
setTitle("Median Operator");
setCategory(IPLProcess::CATEGORY_MORPHOLOGY);
setOpenCVSupport(IPLProcess::OPENCV_OPTIONAL);
// inputs and outputs
addInput("Image", IPLData::IMAGE_COLOR);
addOutput("Image", IPLImage::IMAGE_COLOR);
// properties
addProcessPropertyInt("window", "Window", "", 3, IPL_WIDGET_SLIDER_ODD, 3, 9);
}
void IPLGradientOperator::init()
{
// init
_result = NULL;
// basic settings
setClassName("IPLGradientOperator");
setTitle("Gradient Operator");
setCategory(IPLProcess::CATEGORY_GRADIENTS);
setKeywords("Fast Gradient, Roberts, Sobel, Cubic Spline");
// inputs and outputs
addInput("Image", IPLData::IMAGE_GRAYSCALE);
addOutput("Image", IPLData::IMAGE_ORIENTED);
// set the openCV support
setOpenCVSupport( IPLOpenCVSupport::OPENCV_ONLY );
// properties
addProcessPropertyInt("algorithm", "Algorithm:Fast Gradient|Roberts|Sobel|Cubic Spline", "", 0, IPL_WIDGET_RADIOBUTTONS);
}
void IPLHarrisCorner::init()
{
// init
_result = NULL;
// basic settings
setClassName("IPLHarrisCorner");
setTitle("Harris Corner Detector");
setCategory(IPLProcess::CATEGORY_OBJECTS);
setOpenCVSupport(IPLOpenCVSupport::OPENCV_ONLY);
setDescription("");
// inputs and outputs
addInput("Image", IPLData::IMAGE_COLOR);
addOutput("Magnitude", IPLImage::IMAGE_GRAYSCALE);
addOutput("Edge", IPLImage::IMAGE_GRAYSCALE);
addOutput("Gradient", IPLImage::IMAGE_GRAYSCALE);
// properties
addProcessPropertyInt("threshold", "Threshold", "", 1, IPL_WIDGET_SLIDER, 1, 255);
addProcessPropertyDouble("highThreshold", "High Threshold", "Thresholds for the hysteresis procedure", 0.6, IPL_WIDGET_SLIDER, 0.0, 1.0);
}
void IPLConvolutionFilter::init()
{
// init
_result = NULL;
_offset = 0;
_divisor = 0;
_borders = 0;
_kernel.clear();
// basic settings
setClassName("IPLConvolutionFilter");
setTitle("2D Convolution");
setKeywords("filter");
setCategory(IPLProcess::CATEGORY_LOCALOPERATIONS);
setDescription("Convolution of a kernel with image.");
setOpenCVSupport(IPLOpenCVSupport::OPENCV_OPTIONAL);
// default values
// 0 0 0
// 0 1 0
// 0 0 0
int nrElements = 9;
for(int i=0; i<nrElements; i++)
{
// set the center to 1, all others to 0
_kernel.push_back(i == nrElements/2 ? 1 : 0);
}
// inputs and outputs
addInput("Image", IPLData::IMAGE_COLOR);
addOutput("Image", IPLData::IMAGE_COLOR);
// properties
addProcessPropertyVectorInt("kernel", "Kernel", "", _kernel, IPL_WIDGET_KERNEL);
addProcessPropertyBool("normalize", "Normalize", "Divisor is computed automatically", true, IPL_WIDGET_CHECKBOXES);
addProcessPropertyInt("divisor", "Divisor", "", 1, IPL_WIDGET_SLIDER, 1, 512);
addProcessPropertyDouble("offset", "Offset", "", 0.0, IPL_WIDGET_SLIDER, -1.0, 1.0);
addProcessPropertyInt("borders", "Borders:Crop|Extend|Wrap", "Wrap is not available under OpenCV.", 0, IPL_WIDGET_RADIOBUTTONS, 0, 0);
}
void IPLMorphologyBinary::init()
{
// init
_result = NULL;
// basic settings
setClassName("IPLMorphologyBinary");
setTitle("Binary Morphology");
setCategory(IPLProcess::CATEGORY_MORPHOLOGY);
setOpenCVSupport(IPLOpenCVSupport::OPENCV_OPTIONAL);
// default value
// 0 0 0
// 0 1 0
// 0 0 0
int nrElements = 9;
_kernel.clear();
for(int i=0; i<nrElements; i++)
{
_kernel.push_back((i==4 ? 1 : 0));
}
_operation = 0;
_iterations = 1;
// inputs and outputs
addInput("Image", IPLImage::IMAGE_BW);
addOutput("Image", IPLImage::IMAGE_BW);
// properties
addProcessPropertyVectorInt("kernel", "Kernel", "", _kernel, IPL_WIDGET_BINARY_MORPHOLOGY);
addProcessPropertyInt("iterations", "Iterations",
"Run the algorithm x times\nCaution: big kernels and too many iterations can take a long time to compute!",
_iterations, IPL_WIDGET_SLIDER, 1, 16);
addProcessPropertyInt("operation", "Operation:Dilate|Erode|Opening|Closing", "", _operation, IPL_WIDGET_RADIOBUTTONS);
}