Commit 43c63b95 authored by Victor Poughon's avatar Victor Poughon

DOC: doc review and warnings

parent d6c4a8d6
......@@ -38,8 +38,9 @@ def application_documentation_warnings(app):
description = app.GetDescription()
longdescription = app.GetDocLongDescription()
if not longdescription[-1] == ".":
warn("Application Long Description does not end with a period (.)")
# disable because there are so many for now
#if not longdescription[-1] == ".":
#warn("Application Long Description does not end with a period (.)")
if re.search("\\n [a-zA-Z]", longdescription):
warn("Application Long Description contains '\\n ' pattern (usually not intended)")
......
......@@ -82,7 +82,7 @@ private:
SetDescription("This application computes the chosen descriptors for each studied polyline contained in the input VectorData.");
SetDocName("Compute Polyline Feature From Image");
SetDocLongDescription("The first step in the classifier fusion based validation is to compute the chosen descriptors for each studied polyline. ");
SetDocLongDescription("The first step in the classifier fusion based validation is to compute the chosen descriptors for each studied polyline.");
SetDocLimitations("Since it does not rely on streaming process, take care of the size of input image before launching application.");
SetDocAuthors("OTB-Team");
SetDocSeeAlso(" ");
......
......@@ -108,7 +108,7 @@ private:
AddParameter(ParameterType_OutputImage, "out", "Output Image");
SetParameterDescription("out", "output image. Components are ordered by decreasing eigenvalues.");
MandatoryOff("out");
AddParameter(ParameterType_Group, "rescale", "Rescale Output.");
AddParameter(ParameterType_Group, "rescale", "Rescale Output");
MandatoryOff("rescale");
// AddChoice("rescale.no","No rescale");
......@@ -132,10 +132,10 @@ private:
SetParameterDescription("method.pca", "Principal Component Analysis.");
AddChoice("method.napca", "NA-PCA");
SetParameterDescription("method.napca", "Noise Adjusted Principal Component Analysis.");
AddParameter(ParameterType_Int, "method.napca.radiusx", "Set the x radius of the sliding window.");
AddParameter(ParameterType_Int, "method.napca.radiusx", "Set the x radius of the sliding window");
SetMinimumParameterIntValue("method.napca.radiusx", 1);
SetDefaultParameterInt("method.napca.radiusx", 1);
AddParameter(ParameterType_Int, "method.napca.radiusy", "Set the y radius of the sliding window.");
AddParameter(ParameterType_Int, "method.napca.radiusy", "Set the y radius of the sliding window");
SetMinimumParameterIntValue("method.napca.radiusy", 1);
SetDefaultParameterInt("method.napca.radiusy", 1);
......@@ -158,14 +158,14 @@ private:
//SetParameterDescription("method.vd","Virtual Dimension.");
//MandatoryOff("method");
AddParameter(ParameterType_Int, "nbcomp", "Number of Components.");
AddParameter(ParameterType_Int, "nbcomp", "Number of Components");
SetParameterDescription("nbcomp", "Number of relevant components kept. By default all components are kept.");
SetDefaultParameterInt("nbcomp", 0);
MandatoryOff("nbcomp");
SetMinimumParameterIntValue("nbcomp", 0);
AddParameter(ParameterType_Bool, "normalize", "Normalize.");
SetParameterDescription("normalize", "center AND reduce data before Dimensionality reduction.");
AddParameter(ParameterType_Bool, "normalize", "Normalize");
SetParameterDescription("normalize", "Center and reduce data before Dimensionality reduction.");
AddParameter(ParameterType_OutputFilename, "outmatrix", "Transformation matrix output (text format)");
SetParameterDescription("outmatrix", "Filename to store the transformation matrix (csv format)");
......
......@@ -137,7 +137,7 @@ private:
"the model. The input pixels"
" can be optionally centered and reduced according "
"to the statistics file produced by the "
"ComputeImagesStatistics application. ");
"ComputeImagesStatistics application.");
SetDocLimitations("The input image must contain the feature bands used for"
" the model training. "
......
......@@ -106,7 +106,7 @@ private:
// Documentation
SetDocName("DomainTransform");
SetDocLongDescription("Domain Transform application for wavelet and fourier");
SetDocLongDescription("Domain Transform application for wavelet and fourier.");
SetDocLimitations("This application is not streamed, check your system resources when processing large images");
SetDocAuthors("OTB-Team");
SetDocSeeAlso("otbWaveletImageFilter, otbWaveletInverseImageFilter, otbWaveletTransform");
......
......@@ -108,9 +108,9 @@ private:
"This filter is more suited for radar images. It has a spatial parameter "
"to avoid speckle noise perturbations. The larger the radius is, "
"less sensible to the speckle noise the filter is, but micro edge will be missed.");
AddParameter(ParameterType_Int, "filter.touzi.xradius", "The X radius of the neighborhood.");
AddParameter(ParameterType_Int, "filter.touzi.xradius", "X radius of the neighborhood");
SetDefaultParameterInt("filter.touzi.xradius", 1);
AddParameter(ParameterType_Int, "filter.touzi.yradius", "The Y radius of the neighborhood.");
AddParameter(ParameterType_Int, "filter.touzi.yradius", "Y radius of the neighborhood");
SetDefaultParameterInt("filter.touzi.yradius", 1);
// Canny Section
......
......@@ -304,7 +304,7 @@ private:
// --- OPERATION --- : Label to color / Color to label
AddParameter(ParameterType_Choice, "op", "Operation");
SetParameterDescription("op","Selection of the operation to execute (default is : label to color).");
SetParameterDescription("op", "Selection of the operation to execute (default is: label to color).");
AddChoice("op.labeltocolor","Label to color");
......
......@@ -230,7 +230,7 @@ private:
"check which tiles are already downloaded.");
// UserDefined values
AddParameter(ParameterType_Choice, "mode", "Download/List corresponding SRTM tiles.");
AddParameter(ParameterType_Choice, "mode", "Download/List corresponding SRTM tiles");
AddChoice("mode.download", "Download");
SetParameterDescription("mode.download","Download corresponding tiles on USGE server.");
......
......@@ -107,7 +107,7 @@ private:
"* **All**: keep all bands.\n"
"* **Grayscale**: to display mono image as standard color image \n"
"* **RGB**: select 3 bands in the input image (multi-bands) \n"
"* **RGB**: select 3 bands in the input image (multi-bands)\n"
);
SetDocLimitations("The application does not support complex pixel types as output.");
SetDocAuthors("OTB-Team");
......
......@@ -81,7 +81,7 @@ private:
"allows the user to enter one point (upper left corner of the region to "
"extract) and a size. The extent mode needs two points (upper left "
"corner and lower right) and the radius mode need the center of the "
"region and the radius : it will extract the rectangle containing the "
"region and the radius: it will extract the rectangle containing the "
"circle defined and limited by the image dimension. The fit mode "
"needs a reference image or vector and the dimension of the extracted "
"region will be the same as the extent of the reference. "
......@@ -103,14 +103,14 @@ private:
AddParameter(ParameterType_Choice,"mode","Extraction mode");
AddChoice("mode.standard","Standard");
SetParameterDescription("mode.standard",
"In standard mode extraction is done with 2 parameters : the "
"In standard mode extraction is done with 2 parameters: the "
"upper left corner and the size of the region, decomposed "
"in X and Y coordinates.");
// Fit mode : the ROI is computed through a ref vector dataset or a ref image
// Fit mode: the ROI is computed through a ref vector dataset or a ref image
AddChoice("mode.fit","Fit");
SetParameterDescription("mode.fit",
"In fit mode, extract is made from a reference : image or vector dataset.");
"In fit mode, extract is made from a reference: image or vector dataset.");
AddParameter( ParameterType_InputImage , "mode.fit.im" ,
"Reference image" );
......@@ -122,28 +122,25 @@ private:
"The extent of the input vector file is computed and then "
"gives a region of interest that will be extracted." );
// Extent mode : ROI is computed with two point (upper left and lower left corners)
// Extent mode: ROI is computed with two point (upper left and lower left corners)
AddChoice( "mode.extent" , "Extent" );
SetParameterDescription( "mode.extent" ,
"In extent mode, the ROI is defined by two points, the upper left corner "
"and the lower right corner, decomposed in 2 coordinates : "
"and the lower right corner, decomposed in 2 coordinates: "
"X and Y. The unit for those coordinates can be set." );
AddParameter( ParameterType_Float , "mode.extent.ulx" ,
"X coordinate of the Upper left corner" );
SetParameterDescription( "mode.extent.ulx" ,
"X coordinate of upper left corner point." );
AddParameter( ParameterType_Float , "mode.extent.uly" ,
"Y coordinate of Upper Left corner point." );
SetParameterDescription( "mode.extent.uly" ,
"Y coordinate of upper left corner point." );
AddParameter( ParameterType_Float , "mode.extent.lrx" ,
"X coordinate of Lower Right corner point." );
SetParameterDescription( "mode.extent.lrx" ,
"X coordinate of lower right corner point." );
AddParameter( ParameterType_Float , "mode.extent.lry" ,
"Y coordinate of Lower Right corner point." );
SetParameterDescription( "mode.extent.lry" ,
"Y coordinate of lower right corner point." );
AddParameter(ParameterType_Float, "mode.extent.ulx", "X coordinate of the Upper left corner");
SetParameterDescription("mode.extent.ulx", "X coordinate of upper left corner point.");
AddParameter(ParameterType_Float, "mode.extent.uly", "Y coordinate of Upper Left corner point");
SetParameterDescription("mode.extent.uly", "Y coordinate of upper left corner point.");
AddParameter(ParameterType_Float, "mode.extent.lrx", "X coordinate of Lower Right corner point");
SetParameterDescription("mode.extent.lrx", "X coordinate of lower right corner point.");
AddParameter(ParameterType_Float, "mode.extent.lry", "Y coordinate of Lower Right corner point");
SetParameterDescription("mode.extent.lry", "Y coordinate of lower right corner point.");
// Unit of extent mode
AddParameter( ParameterType_Choice , "mode.extent.unit" , "Unit" );
AddChoice( "mode.extent.unit.pxl" , "Pixel" );
......@@ -160,7 +157,7 @@ private:
"the latitude.");
// Radius mode : ROI is computed through a point and a radius
// Radius mode: ROI is computed through a point and a radius
AddChoice( "mode.radius" , "Radius" );
SetParameterDescription( "mode.radius" ,
"In radius mode, the ROI is defined by a point and a radius. The "
......
......@@ -72,7 +72,7 @@ private:
"The formula can be written using:\n\n"
"* numerical values ( 2.3, -5, 3.1e4, ...)\n"
"* variables containing pixel values (e.g. : ``im2b3`` is the pixel value"
"* variables containing pixel values (e.g. ``im2b3`` is the pixel value"
" in 2nd image, 3rd band)\n"
"* binary operators:\n\n"
......@@ -87,7 +87,7 @@ private:
" * ``or`` logical or, ``and`` logical and\n"
"* if-then-else operator: ``if(condition;value_true;value_false)``\n"
#endif
"* functions : ``exp()``, ``log()``, ``sin()``, ``cos()``, ``min()``, ``max()``, ...\n\n"
"* functions: ``exp()``, ``log()``, ``sin()``, ``cos()``, ``min()``, ``max()``, ...\n\n"
"The full list of features and operators is available on the muParser website [1]."
);
......
......@@ -102,7 +102,7 @@ private:
" * ``==`` equal, ``!=`` not equal\n"
" * logical operators: ``or``, ``and``, ``xor``\n"
"* if-then-else operator: ``(condition ? value_true : value_false)``\n"
"* functions : abs(), exp(), log(), sin(), cos(), min(), max(), ...\n\n"
"* functions: abs(), exp(), log(), sin(), cos(), min(), max(), ...\n\n"
"Always keep in mind that this application only addresses mathematically "
"well-defined formulas. For instance, it is not possible to add vectors of"
......@@ -188,7 +188,7 @@ private:
"whereas #M allows the definition of a vector/matrix. In the latter case, "
"elements of a row must be separated by commas, and rows must be separated"
" by semicolons. It is also possible to define expressions within the same"
" txt file, with #E <expr> (see limitations, below).\n"
" txt file, with #E <expr> (see limitations, below)."
);
SetDocLimitations(
......@@ -376,12 +376,12 @@ private:
std::string expStr = GetParameterString("exp");
if (useContext)
{
otbAppLogINFO("Using input context : " << expStr );
otbAppLogINFO("Using input context: " << expStr );
m_Filter->ImportContext(GetParameterString("incontext"));
}
else
{
otbAppLogINFO("Using expression : " << expStr );
otbAppLogINFO("Using expression: " << expStr );
m_Filter->SetExpression(expStr);
}
......
......@@ -179,7 +179,7 @@ SetOfficialDocLink();
void DoUpdateParameters() override
{
// Nothing to do here : all parameters are independent
// Nothing to do here: all parameters are independent
}
void DoExecute() override
......
......@@ -70,10 +70,10 @@ private:
" different mathematical models of the phenomenon. The application includes four"
" methods: Lee [1], Frost [2], GammaMAP [3] and Kuan [4]. \n\n"
"We sum up below the basic principle of this four methods:\n\n"
"* Lee : Estimate the signal by mean square error minimization (MMSE) on a sliding window.\n"
"* Frost : Also derived from the MMSE criteria with a weighted sum of the values within the window. The weighting factors decrease with distance from the pixel of interest.\n"
"* GammaMAP : Derived under the assumption of the image follows a Gamma distribution.\n"
"* Kuan : Also derived from the MMSE criteria under the assumption of non stationary mean and variance. It is quite similar to Lee filter in form."
"* Lee: Estimate the signal by mean square error minimization (MMSE) on a sliding window.\n"
"* Frost: Also derived from the MMSE criteria with a weighted sum of the values within the window. The weighting factors decrease with distance from the pixel of interest.\n"
"* GammaMAP: Derived under the assumption of the image follows a Gamma distribution.\n"
"* Kuan: Also derived from the MMSE criteria under the assumption of non stationary mean and variance. It is quite similar to Lee filter in form."
);
SetDocLimitations("The application does not handle complex image as input.");
......@@ -169,7 +169,7 @@ private:
void DoUpdateParameters() override
{
// Nothing to do here : all parameters are independent
// Nothing to do here: all parameters are independent
}
void DoExecute() override
......
......@@ -149,9 +149,9 @@ private:
"vertical directions). A winner-take-all approach is used to select the "
"best match. There are different metrics implemented to evaluate the "
"match between two local windows:\n\n"
"* SSD : Sum of Squared Distances\n"
"* NCC : Normalized Cross-Correlation\n"
"* Lp : Lp pseudo norm\n\n"
"* SSD: Sum of Squared Distances\n"
"* NCC: Normalized Cross-Correlation\n"
"* Lp: Lp pseudo norm\n\n"
"Once the best integer disparity is found, an optional step of sub-pixel "
"disparity estimation can be performed, with various algorithms "
......@@ -165,7 +165,7 @@ private:
" by avoiding to investigate disparities that will not be reliable anyway"
". For efficiency reasons, if the image of optimal metric values is "
"desired, it will be concatenated to the output image (which will then "
"have three bands : horizontal disparity, vertical disparity and metric "
"have three bands: horizontal disparity, vertical disparity and metric "
"value). One can split these images afterward.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
......
......@@ -83,7 +83,7 @@ private:
"* skip if position is discarded by the disparity mask\n"
"* compute left ray: transform the current position from epipolar "
"geometry to left sensor geometry (left rectification grid)\n"
"* compute right ray : shift the current position with current "
"* compute right ray: shift the current position with current "
"disparity and transform from epipolar geometry to right sensor (right "
"rectification grid)\n"
"* estimate best 3D intersection between left and right rays\n"
......@@ -202,8 +202,8 @@ private:
m_DispToElev->UpdateOutputInformation();
FloatVectorImageType::RegionType outputRegion = m_DispToElev->GetOutput()->GetLargestPossibleRegion();
otbAppLogINFO(<<"Elevation map origin : [" << m_DispToElev->GetOutput()->GetOrigin()[0] << "," << m_DispToElev->GetOutput()->GetOrigin()[1] << "]" << std::endl);
otbAppLogINFO(<<"Elevation map size : [" << outputRegion.GetSize()[0] << "," << outputRegion.GetSize()[1] << "]" << std::endl);
otbAppLogINFO(<<"Elevation map origin: [" << m_DispToElev->GetOutput()->GetOrigin()[0] << "," << m_DispToElev->GetOutput()->GetOrigin()[1] << "]" << std::endl);
otbAppLogINFO(<<"Elevation map size: [" << outputRegion.GetSize()[0] << "," << outputRegion.GetSize()[1] << "]" << std::endl);
this->SetParameterOutputImage("io.out",m_DispToElev->GetOutput());
}
......
......@@ -74,21 +74,24 @@ SetDescription("Computes Haralick textural features on the selected channel of t
// Documentation
SetDocName("Haralick Texture Extraction");
SetDocLongDescription("This application computes three sets of Haralick features [1][2].\n"
" * simple: a set of 8 local Haralick features: Energy (texture uniformity) , "
SetDocLongDescription(
"This application computes three sets of Haralick features [1][2].\n\n"
"* simple: a set of 8 local Haralick features: Energy (texture uniformity) , "
"Entropy (measure of randomness of intensity image), Correlation (how "
"correlated a pixel is to its neighborhood), Inverse Difference Moment (measures "
"the texture homogeneity), Inertia (intensity contrast between a pixel and its "
"neighborhood), Cluster Shade, Cluster Prominence, Haralick Correlation;\n"
" * advanced: a set of 10 advanced Haralick features : Mean, Variance (measures the "
"* advanced: a set of 10 advanced Haralick features: Mean, Variance (measures the "
"texture heterogeneity), Dissimilarity, Sum Average, Sum Variance, Sum Entropy, "
"Difference of Entropies, Difference of Variances, IC1, IC2;\n"
" * higher: a set of 11 higher Haralick features : Short Run Emphasis (measures the "
"* higher: a set of 11 higher Haralick features: Short Run Emphasis (measures the "
"texture sharpness), Long Run Emphasis (measures the texture roughness), Grey-Level "
"Nonuniformity, Run Length Nonuniformity, Run Percentage (measures the texture "
"sharpness homogeneity), Low Grey-Level Run Emphasis, High Grey-Level Run Emphasis, "
"Short Run Low Grey-Level Emphasis, Short Run High Grey-Level Emphasis, Long Run Low "
"Grey-Level Emphasis and Long Run High Grey-Level Emphasis.");
SetDocLimitations("The computation of the features is based on a Gray Level Co-occurrence "
"matrix (GLCM) from the quantized input image. Consequently the quantization "
"parameters (min, max, nbbin) must be appropriate to the range of the pixel values.");
......
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