diff --git a/Documentation/Cookbook/Scripts/otbGenerateWrappersRstDoc.py b/Documentation/Cookbook/Scripts/otbGenerateWrappersRstDoc.py
index f9c22a7397be3bba3e0f06f32cbff39fd4daa1ed..4ff87275380103a80c6ad7e929d0c50bb487f333 100755
--- a/Documentation/Cookbook/Scripts/otbGenerateWrappersRstDoc.py
+++ b/Documentation/Cookbook/Scripts/otbGenerateWrappersRstDoc.py
@@ -29,8 +29,6 @@ from otbApplication import ParameterType_Bool, ParameterType_Int, ParameterType_
from otb_warnings import application_documentation_warnings
linesep = os.linesep
-pixeltypes = {' uchar' : 1, ' int8' : 0, ' uint8' : 1, ' int16' : 2, ' uint16': 3, ' int32' : 4, ' uint32' : 5, ' float' : 6, ' double': 7}
-
def EncloseString(s):
if not s.startswith("\"") :
@@ -54,6 +52,7 @@ def ExpandPath(filename,path,exp):
return os.path.join(path,filename)
def GetPixelType(value):
+ pixeltypes = {' uchar' : 1, ' int8' : 0, ' uint8' : 1, ' int16' : 2, ' uint16': 3, ' int32' : 4, ' uint32' : 5, ' float' : 6, ' double': 7}
# look for type
foundcode = -1
foundname = ""
@@ -64,38 +63,16 @@ def GetPixelType(value):
break
return foundcode,foundname
-def render_choice(app, key):
- "Render a choice parameter to rst"
-
- # First render all the choice values
- choice_keys = app.GetChoiceKeys(key)
- choice_names = app.GetChoiceNames(key)
-
- choice_entries = ""
- for (choice_key, choice_name) in zip(choice_keys, choice_names):
- # For the description, replace newlines by |br| because we are in a bullet list item
- choice_description = app.GetParameterDescription(key + "." + choice_key).replace("\n", " |br| ")
- choice_entries += template_parameter_choice_entry.format(
- name=choice_name,
- #key=choice_key, # if we want to show the key in choice parameter values
- description=choice_description
- )
-
- # Then render the full choice parameter
- return template_parameter_choice.format(
- name=app.GetParameterName(key),
- key=key,
- value="[" + "|".join(choice_keys) + "]",
- flags=rst_parameter_flags(app, key),
- description=app.GetParameterDescription(key),
- choices=choice_entries,
- )
-
def GetApplicationExamplePythonSnippet(app,idx,expand = False, inputpath="",outputpath=""):
appname = "app"
-
output = ""
+ # Render example comment
+ if len(app.GetExampleComment(idx)) > 0:
+ output += app.GetExampleComment(idx) + ":\n\n"
+
+ output += ".. code-block:: python\n\n"
+
output+= "\timport otbApplication" + linesep + linesep
output+= "\t" + appname + " = otbApplication.Registry.CreateApplication(\"" + app.GetName() + "\")" + linesep + linesep
for i in range(0, app.GetExampleNumberOfParameters(idx)):
@@ -172,9 +149,36 @@ def GetApplicationExamplePythonSnippet(app,idx,expand = False, inputpath="",outp
output += "\t" + appname + ".SetParameterStringList("+EncloseString(param)+ ", " + str(values) + ")"
output+=linesep
output += linesep
- output+= "\t" + appname + ".ExecuteAndWriteOutput()"+ linesep
+ output+= "\t" + appname + ".ExecuteAndWriteOutput()" + linesep + linesep
return output
+def render_choice(app, key):
+ "Render a choice parameter to rst"
+
+ # First render all the choice values
+ choice_keys = app.GetChoiceKeys(key)
+ choice_names = app.GetChoiceNames(key)
+
+ choice_entries = ""
+ for (choice_key, choice_name) in zip(choice_keys, choice_names):
+ # For the description, replace newlines by |br| because we are in a bullet list item
+ choice_description = app.GetParameterDescription(key + "." + choice_key).replace("\n", " |br| ")
+ choice_entries += template_parameter_choice_entry.format(
+ name=choice_name,
+ #key=choice_key, # if we want to show the key in choice parameter values
+ description=choice_description
+ )
+
+ # Then render the full choice parameter
+ return template_parameter_choice.format(
+ name=app.GetParameterName(key),
+ key=key,
+ value="[" + "|".join(choice_keys) + "]",
+ flags=rst_parameter_flags(app, key),
+ description=app.GetParameterDescription(key),
+ choices=choice_entries,
+ )
+
def rst_section(text, delimiter, ref=None):
"Make a rst section title"
@@ -235,22 +239,22 @@ def detect_abuse(app):
fake_groups = {}
keys = app.GetParametersKeys()
+ choice_keys = [k for k in keys if app.GetParameterType(k) == ParameterType_Choice]
# For each choice parameter
- for key in keys:
- if app.GetParameterType(key) == ParameterType_Choice:
+ for key in choice_keys:
- # Consider all its possible values
- for choice_key in app.GetChoiceKeys(key):
- fullkey = key + "." + choice_key
+ # Consider all its possible values
+ for choice_key in app.GetChoiceKeys(key):
+ fullkey = key + "." + choice_key
- # See if that value is also used as a group anywhere in the application
- for k in keys:
- if k.startswith(fullkey) and k != fullkey:
+ # See if that value is also used as a group anywhere in the application
+ for k in keys:
+ if k.startswith(fullkey) and k != fullkey:
- # In that case, mark the first element of that group
- if fullkey not in fake_groups.values():
- fake_groups[k] = fullkey
+ # In that case, mark the first element of that group
+ if fullkey not in fake_groups.values():
+ fake_groups[k] = fullkey
return fake_groups
diff --git a/Documentation/Cookbook/Scripts/otb_warnings.py b/Documentation/Cookbook/Scripts/otb_warnings.py
index 4ed62aee4ac43211bf914aaed7fc45d3e72e19a1..5391cf5cf88633bd4c61c4d7446e35097435af3f 100644
--- a/Documentation/Cookbook/Scripts/otb_warnings.py
+++ b/Documentation/Cookbook/Scripts/otb_warnings.py
@@ -20,8 +20,8 @@ def parameter_warnings(app_warn, app, key):
#if description == "":
#warn("missing description")
- #if len(description) > 0 and description[-1] != ".":
- #warn("description does not end with a period")
+ if len(description) > 0 and description[-1] != ".":
+ warn("description does not end with a period")
if len(description) > 0 and " :" in description:
warn("description has a space before a colon")
diff --git a/Documentation/Cookbook/rst/templates/application.rst b/Documentation/Cookbook/rst/templates/application.rst
index e5d1081d054db1454dcb957b2c6a8e1ca03cae34..a05c9699e3aef827d6b575837f4e75a0ec9d07e9 100644
--- a/Documentation/Cookbook/rst/templates/application.rst
+++ b/Documentation/Cookbook/rst/templates/application.rst
@@ -32,8 +32,6 @@ From the command-line:
From Python:
-.. code-block:: python
-
{examples_python}
{limitations}
diff --git a/Modules/Applications/AppSegmentation/app/otbSegmentation.cxx b/Modules/Applications/AppSegmentation/app/otbSegmentation.cxx
index 0103fee6b29d5602b478ff2d448231d09c2bd048..ba14bc854e30d26b119ceabd3f393203ceb0c4c7 100644
--- a/Modules/Applications/AppSegmentation/app/otbSegmentation.cxx
+++ b/Modules/Applications/AppSegmentation/app/otbSegmentation.cxx
@@ -144,18 +144,24 @@ private:
// Documentation
SetDocName("Segmentation");
- SetDocLongDescription("This application allows one to perform various segmentation algorithms on a multispectral image."
- "Available segmentation algorithms are two different versions of Mean-Shift segmentation algorithm (one being multi-threaded),"
- " simple pixel based connected components according to a user-defined criterion, and watershed from the gradient of the intensity"
- " (norm of spectral bands vector). The application has two different modes that affects the nature of its output.\n\nIn raster mode,"
- " the output of the application is a classical image of unique labels identifying the segmented regions. The labeled output can be passed to the"
- " ColorMapping application to render regions with contrasted colours. Please note that this mode loads the whole input image into memory, and as such"
- " can not handle large images. \n\n To segment large data, one can use the vector mode. In this case, the output of the application is a"
- " vector file or database. The input image is split into tiles (whose size can be set using the tilesize parameter), and each tile is loaded, segmented"
- " with the chosen algorithm, vectorized, and written into the output file or database. This piece-wise behavior ensure that memory will never get overloaded,"
- " and that images of any size can be processed. There are few more options in the vector mode. The simplify option allows simplifying the geometry"
- " (i.e. remove nodes in polygons) according to a user-defined tolerance. The stitch option tries to stitch together the polygons corresponding"
- " to segmented region that may have been split by the tiling scheme. ");
+ SetDocLongDescription(
+ "This application allows one to perform various segmentation algorithms on a multispectral image."
+ " Available segmentation algorithms are two different versions of Mean-Shift segmentation algorithm (one being multi-threaded),"
+ " simple pixel based connected components according to a user-defined criterion, and watershed from the gradient of the intensity"
+ " (norm of spectral bands vector). The application has two different modes that affects the nature of its output.\n\n"
+
+ "In raster mode, the output of the application is a classical image of unique labels identifying the segmented regions. The labeled output can be "
+ "passed to the"
+ " ColorMapping application to render regions with contrasted colours. Please note that this mode loads the whole input image into memory, and as such"
+ " can not handle large images.\n\n"
+
+ "To segment large data, one can use the vector mode. In this case, the output of the application is a"
+ " vector file or database. The input image is split into tiles (whose size can be set using the tilesize parameter), and each tile is loaded, segmented"
+ " with the chosen algorithm, vectorized, and written into the output file or database. This piece-wise behavior ensure that memory will never get"
+ " overloaded, and that images of any size can be processed. There are few more options in the vector mode. The simplify option allows simplifying the "
+ "geometry"
+ " (i.e. remove nodes in polygons) according to a user-defined tolerance. The stitch option tries to stitch together the polygons corresponding"
+ " to segmented region that may have been split by the tiling scheme. ");
SetDocLimitations("In raster mode, the application can not handle large input images. Stitching step of vector mode might become slow with very large input images."
" \nMeanShift filter results depends on the number of threads used. \nWatershed and multiscale geodesic morphology segmentation will be performed on the amplitude "