Nabiha | 19 Jun 18:47 2012
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conversion of type with image on opencv

hello, I changed the type of an image from an IpImage (pointer) to a matrix thanks to this function
cvarrToMat, but later in the program I must do the reverse. knowing that I'm programming with opencv and
visual basic 2010. help please :)

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Fadi | 19 Jun 17:27 2012
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Stitching missing in iOS build

Hello

Not sure if this is the right place to post my issue or not. I am all new to OpenCV :)

I was trying to use OpenCV for the first time on iOS. I am a vivid mobile apps developer with some good
knowledge of computer vision. I wanted to test the Stitching feature of OpenCV but i could not find it in the
source for 2.3 iOS. Is this feature missing? I was under the impression that the library would support all
of its functions on any platform it is ported to. Please correct me if I am wrong.

Many thanks in advance
AF

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Gonçalo Lopes | 21 Jun 12:57 2012
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Best way to scale channels independently?



Hi all,

What is the best way to scale each channel of an image independently? cvConvertScale only accepts a single real number for all channels, cvScaleAdd seems to ignore all other values of the scale parameter except the first, and so on.... Do we really have to split, scale and merge again to achieve this? It seems incredibly roundabout if that's true...

Cheers,
Gonçalo


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rami Batal | 21 Jun 02:17 2012
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(unknown)





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Mathieu Dubois | 20 Jun 21:30 2012
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Strange results in LAB conversion [1 Attachment]

[Attachment(s) from Mathieu Dubois included below]

Hello,

I wanted to check some code that I wrote for Lab conversion by comparing the output to OpenCV but I'm facing some problems.
In order to check that, I wrote the attached program and tested it with attached image (use ./convert_lab test2.ppm).
The image is 1x4 matrix and consists in a white pixel, a red pixel, a green pixel, a blue pixel and soft green pixel.

The program loads an image, and convert it to Lab. Here are the values disaplyed by OpenCV:
(0,0): [100,-1.30398e-05,6.61304e-06]
(0,1): [53.2406,80.0942,67.2015]
(0,2): [72.5174,-1103.15,64.0418]
(0,3): [32.2957,79.187,-107.862]
(0,4): [55.2719,24.1407,62.3391]
Clearly the value of the (0,2) pixel (the green one) and the (0,4) pixel (which is also green) are strange (especially the one in bold).

In order to test I first converted the image to XYZ with OpenCV and then computed Lab with my own code (using the formulas found on OpenCV help). Here are the values:
(0,0): [100,0,-0.000248181]
(0,1): [53.2406,80.0942,67.2015]
(0,2): [87.7351,-86.1813,83.1774]
(0,3): [32.2957,79.187,-107.862]
(0,4): [63.3196,-65.8973,63.6004]
While I won't claim that my code is correct the values make more sense.  Note that they are very close to those computed by OpenCV except for the green pixels.

My question is then: is there something wrong in the way I convert to Lab with OpenCV? if no, why I don't get the same results than in OpenCV?

Thanks in advance,
Mathieu


Attachment(s) from Mathieu Dubois

1 of 1 File(s)


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rgap123 | 19 Jun 20:01 2012
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Re: Error installing OpenCV2.4.1 on windows 7 x64 - Mingw & codeblocks


--- In OpenCV <at> yahoogroups.com, "rgap123" <rgap449 <at> ...> wrote:
>
> Hi,
> I followed this tutorial
> 
> http://stackoverflow.com/questions/10860352/getting-started-with-opencv-2-4-and-mingw-on-windows-7
> 
> I configured the same except instead of x86, i put x64.
> 
> After running the example
> 
> #include "opencv2/highgui/highgui.hpp"
> #include <iostream>
> 
> using namespace cv;
> using namespace std;
> 
> int main(int argc, char** argv)
> {
>   Mat im = imread(argc == 2 ? argv[1] : "lena.jpg", 1);
>   if (im.empty())
>   {
>     cout << "Cannot open image!" << endl;
>     return -1;
>   }
> 
>   imshow("image", im);
>   waitKey(0);
> 
>   return 0;
> }
> 
> when i compile main.cpp
> 
> C:\Users\rgap\Desktop>g++ -I"C:\opencv\build\include" -L"C:\opencv\build\x64\mingw\lib"
main.cpp -lope
> ncv_core241 -lopencv_highgui241 -o main
> 
> I get the following error
> 
> C:\Users\rgap\Desktop>g++ -I"C:\opencv\build\include" -L"C:\opencv\build\x64\mingw\lib"
main.cpp -lope
> ncv_core241 -lopencv_highgui241 -o main
> C:\Users\rgap\AppData\Local\Temp\ccDgmPAT.o:main.cpp:(.text+0x62): undefined reference to `cv::imread(
> std::string const&, int)'
> C:\Users\rgap\AppData\Local\Temp\ccDgmPAT.o:main.cpp:(.text+0xc7): undefined reference to `cv::_InputA
> rray::_InputArray(cv::Mat const&)'
> C:\Users\rgap\AppData\Local\Temp\ccDgmPAT.o:main.cpp:(.text+0xfe): undefined reference to `cv::imshow(
> std::string const&, cv::_InputArray const&)'
> C:\Users\rgap\AppData\Local\Temp\ccDgmPAT.o:main.cpp:(.text+0x120): undefined reference to `cv::waitKe
> y(int)'
>
C:\Users\rgap\AppData\Local\Temp\ccDgmPAT.o:main.cpp:(.text$_ZN2cv3MatD1Ev[cv::Mat::~Mat()]+0x2b): und
> efined reference to `cv::fastFree(void*)'
> C:\Users\rgap\AppData\Local\Temp\ccDgmPAT.o:main.cpp:(.text$_ZN2cv3Mat7releaseEv[cv::Mat::release()]+0
> x3c): undefined reference to `cv::Mat::deallocate()'
> collect2: ld devolvió el estado de salida 1
> 
> I am trying this for more than 3 weeks. Is this a bug?
> 
> thanks
>

Please Help : (
...

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Ahmed Albhy | 19 Jun 17:56 2012
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(unknown)





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pattern | 19 Jun 17:31 2012
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HOG pedestrian detector is too slow!

Hi,

I am trying to find person in my video sequence using this code:

HOGDescriptor hog;
hog.setSVMDetector(HOGDescriptor::getDaimlerPeopleDetector());
vector<Rect> found;

hog.detectMultiScale(frame, found, 0, Size(8,8), Size(32,32), 1.05, 3);

the code is working but the problem is that the detection process takes long time (i.e., it is time consuming).

The video sequence I am using has a size of w 640 x h 420.

Any suggestion form you to overcome this serious problem is greatly appropriated. 

Thanks in advances

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Guido Maria | 18 Jun 18:48 2012
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Feature Detection by Ferns

Hi All,

I am working on a natural feature tracking system based on Ferns classifier.

In openCV there is a demo, find_obj_ferns.cpp, that it is helpful, but there is no documentation about the
Ferns, LDetector and Patchgenerator classes. I would like to tune the classifier in order to have a very
robust tracker.

The feature detector works pretty well when the camera is close to the object, but the quality decreases a
lot when I move the camera far. Basically, the system has some issues to recognize good features when the
planar object takes up 1/4 of the entire image.

I have read some papers about Ferns as well, but they didn't help me much...

I ask you if you have experience with this classifier and if you can give me some suggestions.

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sbemail | 19 Jun 09:25 2012

How to check if an image is divided in 8x8

How do you know if a certain image let's say a jpeg is divided into 8x8
blocks?

Another question:
How can I divide an image into 8x8 and display it's values?

any suggesstions??? 

--
View this message in context: http://opencv-users.1802565.n2.nabble.com/How-to-check-if-an-image-is-divided-in-8x8-tp7580472.html
Sent from the opencv-users mailing list archive at Nabble.com.

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Murray Macdonald | 19 Jun 08:14 2012

Auto Correction / Auto Enhancement



Hi guys,

 

I was wondering if anyone in the OpenCV community has worked on an Automatic Color Image Enhancement capability.    Many imaging applications out there preform automated color image enhancement or auto-correct capability, and I’d like to learn more.   Can anyone point me at an example or some good reading on the subject?

 

Thanks,

 

Murray

 



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