Fixed #3, #4

tanchinluh · Dec 2, 2023 · 4a58c1f · 4a58c1f
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diff --git a/help/en_US/Analytic Geometry/plot3dot.xml b/help/en_US/Analytic Geometry/plot3dot.xml
@@ -33,16 +33,26 @@
 <refsection>
    <title>Parameters</title>
    <variablelist>
-   <varlistentry><term>x :</term>
-      <listitem><para> x data</para></listitem></varlistentry>
-   <varlistentry><term>y :</term>
-      <listitem><para> y data</para></listitem></varlistentry>
-   <varlistentry><term>z :</term>
-      <listitem><para> z data</para></listitem></varlistentry>
-   <varlistentry><term>mark_foreground :</term>
-      <listitem><para> marker color</para></listitem></varlistentry>
-   <varlistentry><term>mark_style :</term>
-      <listitem><para> marker style</para></listitem></varlistentry>
+        <varlistentry>
+            <term>x :</term>
+            <listitem><para> x data</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>y :</term>
+            <listitem><para> y data</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>z :</term>
+            <listitem><para> z data</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>mark_foreground :</term>
+            <listitem><para> marker color</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>mark_style :</term>
+            <listitem><para> marker style</para></listitem>
+        </varlistentry>
    </variablelist>
 </refsection>
 

diff --git a/help/en_US/Camera Handling/camclose.xml b/help/en_US/Camera Handling/camclose.xml
@@ -63,7 +63,7 @@ camclose(n);
    ]]></programlisting>
 </refsection>
 
-<refsection>
+<refsection role="see also">
    <title>See also</title>
    <simplelist type="inline">
    <member><link linkend="camclose">camclose</link></member>

diff --git a/help/en_US/Camera Handling/camcloseall.xml b/help/en_US/Camera Handling/camcloseall.xml
@@ -53,7 +53,7 @@ camcloseall();
    ]]></programlisting>
 </refsection>
 
-<refsection>
+<refsection role="see also">
    <title>See also</title>
    <simplelist type="inline">
    <member><link linkend="camclose">camclose</link></member>

diff --git a/help/en_US/Camera Handling/camlistopened.xml b/help/en_US/Camera Handling/camlistopened.xml
@@ -61,7 +61,7 @@ camcloseall()
    ]]></programlisting>
 </refsection>
 
-<refsection>
+<refsection role="see also">
    <title>See also</title>
    <simplelist type="inline">
    <member><link linkend="camclose">camclose</link></member>

diff --git a/help/en_US/Camera Handling/camopen.xml b/help/en_US/Camera Handling/camopen.xml
@@ -70,7 +70,7 @@ camcloseall();
    ]]></programlisting>
 </refsection>
 
-<refsection>
+<refsection role="see also">
    <title>See also</title>
    <simplelist type="inline">
    <member><link linkend="camclose">camclose</link></member>

diff --git a/help/en_US/Camera Handling/camread.xml b/help/en_US/Camera Handling/camread.xml
@@ -67,7 +67,7 @@ camcloseall();
    ]]></programlisting>
 </refsection>
 
-<refsection>
+<refsection role="see also">
    <title>See also</title>
    <simplelist type="inline">
    <member><link linkend="camclose">camclose</link></member>

diff --git a/help/en_US/Deep Learning/dnn_forward.xml b/help/en_US/Deep Learning/dnn_forward.xml
@@ -83,9 +83,9 @@ This function is used to run forward pass to compute output of layer with name l
 <refsection>
    <title>Examples</title>
    <programlisting role="example"><![CDATA[
-dnn_path = fullfile(getIPCVpath(),'images','dnn');
-net = dnn_readmodel(fullfile(dnn_path,'lenet5.pb'),'','tensorflow');
-S = imread(fullfile(dnn_path,'3.jpg'));
+dnn_path = fullpath(getIPCVpath() + '/images/dnn/');
+net = dnn_readmodel(dnn_path + 'lenet5.pb','','tensorflow');
+S = imread(dnn_path + '3.jpg');
 imshow(S);
 out = dnn_forward(net,~S,[28,28]);
 [maxV,maxI]=max(out);

diff --git a/help/en_US/Deep Learning/dnn_getparam.xml b/help/en_US/Deep Learning/dnn_getparam.xml
@@ -65,11 +65,12 @@ This function is used to retrieve the layer's parameters (filter coefficients)
    <programlisting role="example"><![CDATA[
 // Initialize
 dnn_unloadallmodels
-dnn_path = fullfile(getIPCVpath(),'images','dnn');
-net = dnn_readmodel(fullfile(dnn_path,'lenet5.pb'),'','tensorflow');
+dnn_path = fullpath(getIPCVpath() + '/images/dnn/');
+net = dnn_readmodel(dnn_path + 'lenet5.pb','','tensorflow');
+
 
 // Read Image
-S = imread(fullfile(dnn_path,'3.jpg'));
+S = imread(dnn_path + '3.jpg');
 
 // Forward Pass
 para1 = dnn_getparam(net,"conv2d/Conv2D");

diff --git a/help/en_US/Deep Learning/dnn_readmodel.xml b/help/en_US/Deep Learning/dnn_readmodel.xml
@@ -38,7 +38,7 @@
         </varlistentry>
         <varlistentry>
             <term>modelinfo :</term>
-            <listitem><para> MOdel info (Caffe - &gt; .prototxt file. TF -&gt; .pbtxt file).</para></listitem>
+            <listitem><para> Model info (Caffe - &gt; .prototxt file. TF -&gt; .pbtxt file).</para></listitem>
         </varlistentry>
         <varlistentry>
             <term>modeltype :</term>
@@ -63,9 +63,9 @@ This function is used for loading DNN model and used in Scilab for inference sys
 <refsection>
    <title>Examples</title>
    <programlisting role="example"><![CDATA[
-dnn_path = fullfile(getIPCVpath(),'images','dnn');
-net = dnn_readmodel(fullfile(dnn_path,'lenet5.pb'),'','tensorflow');
-S = imread(fullfile(dnn_path,'3.jpg'));
+dnn_path = fullpath(getIPCVpath() + '/images/dnn/');
+net = dnn_readmodel(dnn_path + 'lenet5.pb','','tensorflow');
+S = imread(dnn_path + '3.jpg');
 imshow(S);
 out = dnn_forward(net,~S,[28,28]);
 [maxV,maxI]=max(out);

diff --git a/help/en_US/Deep Learning/dnn_showfeature.xml b/help/en_US/Deep Learning/dnn_showfeature.xml
@@ -61,11 +61,12 @@ This function is used to visualize the DNN feature maps
    <programlisting role="example"><![CDATA[
 // Initialize
 dnn_unloadallmodels
-dnn_path = fullfile(getIPCVpath(),'images','dnn');
-net = dnn_readmodel(fullfile(dnn_path,'lenet5.pb'),'','tensorflow');
+dnn_path = fullpath(getIPCVpath() + '/images/dnn/');
+net = dnn_readmodel(dnn_path + 'lenet5.pb','','tensorflow');
+
 
 // Read Image
-S = imread(fullfile(dnn_path,'3.jpg'));
+S = imread(dnn_path + '3.jpg');
 
 // Forward Pass
 out1 = dnn_forward(net,~S,[28,28],"conv2d/Conv2D");

diff --git a/help/en_US/Deep Learning/dnn_showparam.xml b/help/en_US/Deep Learning/dnn_showparam.xml
@@ -61,11 +61,12 @@ This function is used to visualize the DNN parameters (filter) in spatial domain
    <programlisting role="example"><![CDATA[
 // Initialize
 dnn_unloadallmodels
-dnn_path = fullfile(getIPCVpath(),'images','dnn');
-net = dnn_readmodel(fullfile(dnn_path,'lenet5.pb'),'','tensorflow');
+dnn_path = fullpath(getIPCVpath() + '/images/dnn/');
+net = dnn_readmodel(dnn_path + 'lenet5.pb','','tensorflow');
+
 
 // Read Image
-S = imread(fullfile(dnn_path,'3.jpg'));
+S = imread(dnn_path + '3.jpg');
 
 // Forward Pass
 para1 = dnn_getparam(net,"conv2d/Conv2D");

diff --git a/help/en_US/Deep Learning/dnn_showparamf2d.xml b/help/en_US/Deep Learning/dnn_showparamf2d.xml
@@ -61,11 +61,12 @@ This function is used to visualize the DNN  parameters (filter) in 2D frequency
    <programlisting role="example"><![CDATA[
 // Initialize
 dnn_unloadallmodels
-dnn_path = fullfile(getIPCVpath(),'images','dnn');
-net = dnn_readmodel(fullfile(dnn_path,'lenet5.pb'),'','tensorflow');
+dnn_path = fullpath(getIPCVpath() + '/images/dnn/');
+net = dnn_readmodel(dnn_path + 'lenet5.pb','','tensorflow');
+
 
 // Read Image
-S = imread(fullfile(dnn_path,'3.jpg'));
+S = imread(dnn_path + '3.jpg');
 
 // Forward Pass
 para1 = dnn_getparam(net,"conv2d/Conv2D");

diff --git a/help/en_US/Deep Learning/dnn_showparamf3d.xml b/help/en_US/Deep Learning/dnn_showparamf3d.xml
@@ -61,11 +61,12 @@ This function is used to visualize the DNN  parameters (filter) in 3D frequency
    <programlisting role="example"><![CDATA[
 // Initialize
 dnn_unloadallmodels
-dnn_path = fullfile(getIPCVpath(),'images','dnn');
-net = dnn_readmodel(fullfile(dnn_path,'lenet5.pb'),'','tensorflow');
+dnn_path = fullpath(getIPCVpath() + '/images/dnn/');
+net = dnn_readmodel(dnn_path + 'lenet5.pb','','tensorflow');
+
 
 // Read Image
-S = imread(fullfile(dnn_path,'3.jpg'));
+S = imread(dnn_path + '3.jpg');
 
 // Forward Pass
 para1 = dnn_getparam(net,"conv2d/Conv2D");

diff --git a/help/en_US/Feature Detection, Description and Matching/imbestmatches.xml b/help/en_US/Feature Detection, Description and Matching/imbestmatches.xml
@@ -32,20 +32,34 @@
 <refsection>
    <title>Parameters</title>
    <variablelist>
-   <varlistentry><term>fobj1 :</term>
-      <listitem><para> First feature object</para></listitem></varlistentry>
-   <varlistentry><term>fobj2 :</term>
-      <listitem><para> Second feature object</para></listitem></varlistentry>
-   <varlistentry><term>m :</term>
-      <listitem><para> Matching matrix</para></listitem></varlistentry>
-   <varlistentry><term>n :</term>
-      <listitem><para> Number of best matches to returned</para></listitem></varlistentry>
-   <varlistentry><term>fout1 :</term>
-      <listitem><para> First best feature object</para></listitem></varlistentry>
-   <varlistentry><term>fout2 :</term>
-      <listitem><para> Second best feature object</para></listitem></varlistentry>
-   <varlistentry><term>mout :</term>
-      <listitem><para> New matching matrix corresponding to the best matches</para></listitem></varlistentry>
+        <varlistentry>
+            <term>fobj1 :</term>
+            <listitem><para> First feature object</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>fobj2 :</term>
+            <listitem><para> Second feature object</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>m :</term>
+            <listitem><para> Matching matrix</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>n :</term>
+            <listitem><para> Number of best matches to returned</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>fout1 :</term>
+            <listitem><para> First best feature object</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>fout2 :</term>
+            <listitem><para> Second best feature object</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>mout :</term>
+            <listitem><para> New matching matrix corresponding to the best matches</para></listitem>
+        </varlistentry>
    </variablelist>
 </refsection>
 
@@ -82,7 +96,7 @@ imshow(SS);
    ]]></programlisting>
 </refsection>
 
-<refsection>
+<refsection role="see also">
    <title>See also</title>
    <simplelist type="inline">
    <member><link linkend="imdrawmatches">imdrawmatches</link></member>

diff --git a/help/en_US/Feature Detection, Description and Matching/imdetect_BRISK.xml b/help/en_US/Feature Detection, Description and Matching/imdetect_BRISK.xml
@@ -32,34 +32,62 @@
 <refsection>
    <title>Parameters</title>
    <variablelist>
-   <varlistentry><term>im :</term>
-      <listitem><para> Input image</para></listitem></varlistentry>
-   <varlistentry><term>thresh :</term>
-      <listitem><para> FAST/AGAST detection threshold score. Default value is 30.</para></listitem></varlistentry>
-   <varlistentry><term>octaves :</term>
-      <listitem><para> detection octaves. Use 0 to do single scale. Default value is 3.</para></listitem></varlistentry>
-   <varlistentry><term>patternScale :</term>
-      <listitem><para> apply this scale to the pattern used for sampling the neighbourhood of a keypoint. Default value is 1.0.</para></listitem></varlistentry>
-   <varlistentry><term>fobj :</term>
-      <listitem><para> Features object contains following fields -</para></listitem></varlistentry>
-   <varlistentry><term>type :</term>
-      <listitem><para> Type of features</para></listitem></varlistentry>
-   <varlistentry><term>n :</term>
-      <listitem><para> Numbers of detected features</para></listitem></varlistentry>
-   <varlistentry><term>x :</term>
-      <listitem><para> Coordinates of the detected features - X</para></listitem></varlistentry>
-   <varlistentry><term>y :</term>
-      <listitem><para> Coordinates of the detected features - Y</para></listitem></varlistentry>
-   <varlistentry><term>size :</term>
-      <listitem><para> Size of detected features</para></listitem></varlistentry>
-   <varlistentry><term>angle :</term>
-      <listitem><para> keypoint orientation</para></listitem></varlistentry>
-   <varlistentry><term>response :</term>
-      <listitem><para> The response by which the most strong keypoints have been selected.</para></listitem></varlistentry>
-   <varlistentry><term>octave :</term>
-      <listitem><para> pyramid octave in which the keypoint has been detected</para></listitem></varlistentry>
-   <varlistentry><term>class_id :</term>
-      <listitem><para> object id</para></listitem></varlistentry>
+        <varlistentry>
+            <term>im :</term>
+            <listitem><para> Input image</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>thresh :</term>
+            <listitem><para> FAST/AGAST detection threshold score. Default value is 30.</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>octaves :</term>
+            <listitem><para> detection octaves. Use 0 to do single scale. Default value is 3.</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>patternScale :</term>
+            <listitem><para> apply this scale to the pattern used for sampling the neighbourhood of a keypoint. Default value is 1.0.</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>fobj :</term>
+            <listitem><para> Features object contains following fields -</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>type :</term>
+            <listitem><para> Type of features</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>n :</term>
+            <listitem><para> Numbers of detected features</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>x :</term>
+            <listitem><para> Coordinates of the detected features - X</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>y :</term>
+            <listitem><para> Coordinates of the detected features - Y</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>size :</term>
+            <listitem><para> Size of detected features</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>angle :</term>
+            <listitem><para> keypoint orientation</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>response :</term>
+            <listitem><para> The response by which the most strong keypoints have been selected.</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>octave :</term>
+            <listitem><para> pyramid octave in which the keypoint has been detected</para></listitem>
+        </varlistentry>
+        <varlistentry>
+            <term>class_id :</term>
+            <listitem><para> object id</para></listitem>
+        </varlistentry>
    </variablelist>
 </refsection>
 
@@ -82,7 +110,7 @@ imshow(S); plotfeature(fobj);
    ]]></programlisting>
 </refsection>
 
-<refsection>
+<refsection role="see also">
    <title>See also</title>
    <simplelist type="inline">
    <member><link linkend="imdetect_FAST">imdetect_FAST</link></member>