From ae23e0c3518d6271e1520f436ee1927bdc2862aa Mon Sep 17 00:00:00 2001 From: Suleyman TURKMEN Date: Sun, 10 Oct 2021 19:35:08 +0300 Subject: [PATCH] Update tutorial.markdown --- .../tutorials/tutorial.markdown | 26 +++++++++---------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/modules/line_descriptor/tutorials/tutorial.markdown b/modules/line_descriptor/tutorials/tutorial.markdown index bfff1292153..f8012c24da4 100644 --- a/modules/line_descriptor/tutorials/tutorial.markdown +++ b/modules/line_descriptor/tutorials/tutorial.markdown @@ -3,9 +3,9 @@ Line Features Tutorial {#tutorial_line_descriptor_main} In this tutorial it will be shown how to: -- use the *BinaryDescriptor* interface to extract lines and store them in *KeyLine* objects -- use the same interface to compute descriptors for every extracted line -- use the *BynaryDescriptorMatcher* to determine matches among descriptors obtained from different +- Use the *BinaryDescriptor* interface to extract the lines and store them in *KeyLine* objects +- Use the same interface to compute descriptors for every extracted line +- Use the *BynaryDescriptorMatcher* to determine matches among descriptors obtained from different images Lines extraction and descriptors computation @@ -18,7 +18,7 @@ displayed using random colors for octave 0. @includelineno line_descriptor/samples/lsd_lines_extraction.cpp -This is the result obtained for famous cameraman image: +This is the result obtained from the famous cameraman image: ![alternate text](pics/lines_cameraman_edl.png) @@ -54,7 +54,7 @@ choosing the one at closest distance: @includelineno line_descriptor/samples/matching.cpp Sometimes, we could be interested in searching for the closest *k* descriptors, given an input one. -This requires to modify slightly previous code: +This requires modifying previous code slightly: @code{.cpp} // prepare a structure to host matches @@ -66,7 +66,7 @@ bdm->knnMatch( descr1, descr2, matches, 6 ); In the above example, the closest 6 descriptors are returned for every query. In some cases, we could have a search radius and look for all descriptors distant at the most *r* from input query. -Previous code must me modified: +Previous code must be modified like: @code{.cpp} // prepare a structure to host matches @@ -76,7 +76,7 @@ std::vector > matches; bdm->radiusMatch( queries, matches, 30 ); @endcode -Here's an example om matching among descriptors extratced from original cameraman image and its +Here's an example of matching among descriptors extracted from original cameraman image and its downsampled (and blurred) version: ![alternate text](pics/matching2.png) @@ -84,15 +84,15 @@ downsampled (and blurred) version: Querying internal database -------------------------- -The *BynaryDescriptorMatcher* class, owns an internal database that can be populated with -descriptors extracted from different images and queried using one of the modalities described in +The *BynaryDescriptorMatcher* class owns an internal database that can be populated with +descriptors extracted from different images and queried using one of the modalities described in the previous section. Population of internal dataset can be done using the *add* function; such function -doesn't directly add new data to database, but it just stores it them locally. The real update -happens when function *train* is invoked or when any querying function is executed, since each of +doesn't directly add new data to the database, but it just stores it them locally. The real update +happens when the function *train* is invoked or when any querying function is executed, since each of them invokes *train* before querying. When queried, internal database not only returns required -descriptors, but, for every returned match, it is able to tell which image matched descriptor was +descriptors, but for every returned match, it is able to tell which image matched descriptor was extracted from. An example of internal dataset usage is described in the following code; after adding locally new descriptors, a radius search is invoked. This provokes local data to be -transferred to dataset, which, in turn, is then queried. +transferred to dataset which in turn, is then queried. @includelineno line_descriptor/samples/radius_matching.cpp