Removed references to opencv.itseez.com

2013-06-28 12:48:12 +04:00
parent 0339dd51f1
commit aef347e7b3
8 changed files with 117 additions and 119 deletions
--- a/doc/tutorials/gpu/gpu-basics-similarity/gpu-basics-similarity.rst
+++ b/doc/tutorials/gpu/gpu-basics-similarity/gpu-basics-similarity.rst
@@ -62,7 +62,7 @@ The GPU has its own memory. When you read data from the hard drive with OpenCV i

   I1 = gI1;       // Download, gI1.download(I1) will work too

-Once you have your data up in the GPU memory you may call GPU enabled functions of OpenCV. Most of the functions keep the same name just as on the CPU, with the difference that they only accept *GpuMat* inputs. A full list of these you will find in the documentation: `online here <http://opencv.itseez.com/modules/gpu/doc/gpu.html>`_ or the OpenCV reference manual that comes with the source code.
+Once you have your data up in the GPU memory you may call GPU enabled functions of OpenCV. Most of the functions keep the same name just as on the CPU, with the difference that they only accept *GpuMat* inputs. A full list of these you will find in the documentation: `online here <http://docs.opencv.org/modules/gpu/doc/gpu.html>`_ or the OpenCV reference manual that comes with the source code.

 Another thing to keep in mind is that not for all channel numbers you can make efficient algorithms on the GPU. Generally, I found that the input images for the GPU images need to be either one or four channel ones and one of the char or float type for the item sizes. No double support on the GPU, sorry. Passing other types of objects for some functions will result in an exception thrown, and an error message on the error output. The documentation details in most of the places the types accepted for the inputs. If you have three channel images as an input you can do two things: either adds a new channel (and use char elements) or split up the image and call the function for each image. The first one isn't really recommended as you waste memory.