Fixed whitespace warnings in new tutorials

This commit is contained in:
Maksim Shabunin 2014-12-05 15:33:53 +03:00
parent 6d282ddf72
commit ecfd056111
22 changed files with 4 additions and 32 deletions

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@ -144,4 +144,3 @@ proper macros in their appropriate positions. Rest is done by generator scripts.
may be an exceptional cases where generator scripts cannot create the wrappers. Such functions need may be an exceptional cases where generator scripts cannot create the wrappers. Such functions need
to be handled manually. But most of the time, a code written according to OpenCV coding guidelines to be handled manually. But most of the time, a code written according to OpenCV coding guidelines
will be automatically wrapped by generator scripts. will be automatically wrapped by generator scripts.

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@ -65,4 +65,3 @@ Exercises
-# OpenCV samples contain an example of generating disparity map and its 3D reconstruction. Check -# OpenCV samples contain an example of generating disparity map and its 3D reconstruction. Check
stereo_match.py in OpenCV-Python samples. stereo_match.py in OpenCV-Python samples.

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@ -172,4 +172,3 @@ Exercises
2. Fundamental Matrix estimation is sensitive to quality of matches, outliers etc. It becomes worse 2. Fundamental Matrix estimation is sensitive to quality of matches, outliers etc. It becomes worse
when all selected matches lie on the same plane. [Check this when all selected matches lie on the same plane. [Check this
discussion](http://answers.opencv.org/question/18125/epilines-not-correct/). discussion](http://answers.opencv.org/question/18125/epilines-not-correct/).

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@ -80,4 +80,3 @@ Additional Resources
Independent Elementary Features", 11th European Conference on Computer Vision (ECCV), Heraklion, Independent Elementary Features", 11th European Conference on Computer Vision (ECCV), Heraklion,
Crete. LNCS Springer, September 2010. Crete. LNCS Springer, September 2010.
2. LSH (Locality Sensitive Hasing) at wikipedia. 2. LSH (Locality Sensitive Hasing) at wikipedia.

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@ -109,4 +109,3 @@ Exercises
-# In our last example, we drew filled rectangle. You modify the code to draw an unfilled -# In our last example, we drew filled rectangle. You modify the code to draw an unfilled
rectangle. rectangle.

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@ -72,4 +72,3 @@ Exercises
-# Create a Paint application with adjustable colors and brush radius using trackbars. For drawing, -# Create a Paint application with adjustable colors and brush radius using trackbars. For drawing,
refer previous tutorial on mouse handling. refer previous tutorial on mouse handling.

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@ -135,4 +135,3 @@ Exercises
-# OpenCV samples contain digits.py which applies a slight improvement of the above method to get -# OpenCV samples contain digits.py which applies a slight improvement of the above method to get
improved result. It also contains the reference. Check it and understand it. improved result. It also contains the reference. Check it and understand it.

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@ -87,4 +87,3 @@ Exercises
Adobe Photoshop. On further search, I was able to find that same technique is already there in Adobe Photoshop. On further search, I was able to find that same technique is already there in
GIMP with different name, "Resynthesizer" (You need to install separate plugin). I am sure you GIMP with different name, "Resynthesizer" (You need to install separate plugin). I am sure you
will enjoy the technique. will enjoy the technique.

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@ -84,4 +84,3 @@ Additional Resources
3. [Numpy Examples List](http://wiki.scipy.org/Numpy_Example_List) 3. [Numpy Examples List](http://wiki.scipy.org/Numpy_Example_List)
4. [OpenCV Documentation](http://docs.opencv.org/) 4. [OpenCV Documentation](http://docs.opencv.org/)
5. [OpenCV Forum](http://answers.opencv.org/questions/) 5. [OpenCV Forum](http://answers.opencv.org/questions/)

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@ -223,4 +223,3 @@ Exercises
-# Check the code in samples/python2/lk_track.py. Try to understand the code. -# Check the code in samples/python2/lk_track.py. Try to understand the code.
2. Check the code in samples/python2/opt_flow.py. Try to understand the code. 2. Check the code in samples/python2/opt_flow.py. Try to understand the code.

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@ -183,4 +183,3 @@ Exercises
-# OpenCV comes with a Python sample on interactive demo of camshift. Use it, hack it, understand -# OpenCV comes with a Python sample on interactive demo of camshift. Use it, hack it, understand
it. it.

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@ -52,4 +52,3 @@ image.
opencv/samples/cpp/calibration.cpp, function computeReprojectionErrors). opencv/samples/cpp/calibration.cpp, function computeReprojectionErrors).
Question: how to calculate the distance from the camera origin to any of the corners? Question: how to calculate the distance from the camera origin to any of the corners?

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@ -241,4 +241,3 @@ Result
Compiling and running your program should give you a result like this: Compiling and running your program should give you a result like this:
![](images/Drawing_1_Tutorial_Result_0.png) ![](images/Drawing_1_Tutorial_Result_0.png)

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@ -50,5 +50,3 @@ known planar objects in scenes.
Mat points1Projected; perspectiveTransform(Mat(points1), points1Projected, H); Mat points1Projected; perspectiveTransform(Mat(points1), points1Projected, H);
- Use drawMatches for drawing inliers. - Use drawMatches for drawing inliers.

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@ -137,5 +137,3 @@ Result
-# And here is the result for the detected object (highlighted in green) -# And here is the result for the detected object (highlighted in green)
![](images/Feature_Homography_Result.jpg) ![](images/Feature_Homography_Result.jpg)

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@ -127,4 +127,3 @@ Result
Here is the result: Here is the result:
![](images/Corner_Subpixeles_Result.jpg) ![](images/Corner_Subpixeles_Result.jpg)

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@ -33,4 +33,3 @@ Result
![](images/My_Harris_corner_detector_Result.jpg) ![](images/My_Harris_corner_detector_Result.jpg)
![](images/My_Shi_Tomasi_corner_detector_Result.jpg) ![](images/My_Shi_Tomasi_corner_detector_Result.jpg)

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@ -112,4 +112,3 @@ Result
------ ------
![](images/Feature_Detection_Result_a.jpg) ![](images/Feature_Detection_Result_a.jpg)

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@ -206,4 +206,3 @@ The original image:
The detected corners are surrounded by a small black circle The detected corners are surrounded by a small black circle
![](images/Harris_Detector_Result.jpg) ![](images/Harris_Detector_Result.jpg)

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@ -74,4 +74,3 @@ As always, we would be happy to hear your comments and receive your contribution
- @subpage tutorial_table_of_content_viz - @subpage tutorial_table_of_content_viz
These tutorials show how to use Viz module effectively. These tutorials show how to use Viz module effectively.

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@ -1,8 +1,5 @@
HighGUI {#tutorial_ug_highgui} Using Kinect and other OpenNI compatible depth sensors {#tutorial_ug_highgui}
======= ======================================================
Using Kinect and other OpenNI compatible depth sensors
------------------------------------------------------
Depth sensors compatible with OpenNI (Kinect, XtionPRO, ...) are supported through VideoCapture Depth sensors compatible with OpenNI (Kinect, XtionPRO, ...) are supported through VideoCapture
class. Depth map, RGB image and some other formats of output can be retrieved by using familiar class. Depth map, RGB image and some other formats of output can be retrieved by using familiar

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@ -1,8 +1,5 @@
HighGUI {#tutorial_ug_intelperc} Using Creative Senz3D and other Intel Perceptual Computing SDK compatible depth sensors {#tutorial_ug_intelperc}
======= =======================================================================================
Using Creative Senz3D and other Intel Perceptual Computing SDK compatible depth sensors
---------------------------------------------------------------------------------------
Depth sensors compatible with Intel Perceptual Computing SDK are supported through VideoCapture Depth sensors compatible with Intel Perceptual Computing SDK are supported through VideoCapture
class. Depth map, RGB image and some other formats of output can be retrieved by using familiar class. Depth map, RGB image and some other formats of output can be retrieved by using familiar