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Please explain a short algorithm,as to how you can apply SVM after resampling trajectory.Lets say,you after you have res

@berak: Ok lets say,I have resample my trajectory to 100 sample points. Then what would be your approach for classifying

@sjhalayka: I would be glad,if you can let me know,as to how,one can apply SVM classifier with the known freeman chain c

@sjhalayka: No, They do not have same number of points. Also, each of the trajectory can vary in translation,rotation an

Classify a trajectory using SVM from freeman chain codes Hi, Lets assume, I have set of testing trajectories (set of 2

So,if I use 'findContours()' method, I can get the contours array and then understand the number of entities in the Imag

Query regarding Canny Edge Detector - openCv Hi, I have the following code: import cv2 import numpy as np from matplot

@berak: Please do provide some sample code for Lenet. I would be glad,if you can clearly explain,how I can use !

@LBerger: Thanks Mate! I guess,they are considering training the data directly from Images right?

Ok :(..Please atleast provide some sample code for python please! I would try out with my data..

@berak: Do you recommend using tensorflow? I tried a lot, but I did not find any kind of help,for implementing CNN in C+

@berak: Please do help!

Training a CNN with openCv using C++ Hi, I have basically a set of 2D Points. So, lets say, I consider a big 200x200 Ma

Training a CNN with openCv using C++ Hi, I have basically a set of 2D Points. So, lets say, I consider a big 200x200 Ma

Creating Polylines from a set of 2D Points and then resizing the Image to be of size 32x32 Hi, I have a set of 2D Point

@Der Luftmensch: Mate, I would be really glad,if you could provide me some refrence for training out something. Thanks

@Der Luftmensch: Nope mate,I am not dismissing any of your ideas! Could you please provide some sample codes for my prob

@Der Luftmensch: There are many problems with building the model with contours.Because, each of my contour has different

Thanks a lot! I will look into it! Please suggest some some basic code,which can work correctly in my case. I will try t

Constructing a very simple neural network inorder to train Contour Images and predict the classification Hi, I have som

@berak: I am resampling my data like this; 1) In case, my contour consists of 30 points and I need to resample it to 50

@berak: Please do provide a code,which does resampling for a given Number.

Regarding resampling,could you share some other good function.The function used in 1$ Code is really bad and gives dupli

right.So,now,I dont have to rescale to image coordinates.I will remove that line. Yes,To take care of rotation,I use PCA

Could you elaborate a bit more? our main aim is to get the same number of characters size,when we generate freeman chain

yeah,thanks! Even the above procedure is fine right? Also, I have one query regarding your suggestion for yesterdays pro

yeah,thanks! Even the above procedure is fine right? Also, I have one query regarding your suggestion for yesterdays pro

yeah,thanks! Even the above procedure is fine right? Also, I have one query regarding your suggestion for yesterdays pro

@berak: Could you please have a look at the above procedure and suggest changes.Thanks

Writing your own freeman chain code without using openCv Hi, Since the openCv freeman chain code is a bit ambiguous. I

ah okay! So,I can go ahead with the first one right?

Please,do not make it complicated.Lets just assume that, I have only 1 sample for each class.So, in that case,for assign

Please,do not make it complicated.Lets just assume that, I have only 1 sample for each class.So, in that case,for assign

Please,do not make it complicated.Lets just assume that, I have only 1 sample for each class.So, in that case,for assign

Please,do not make it complicated.Lets just assume that, I have only 1 sample for each class.So, in that case,for assign

how about assigning Label? Could you once have a look at it and let me know I wrote like this: trainLabels.at<int>

trainLabels.at<int>( r, 0 ) = r; Is the line fine (or) do I need to assign Labels something differently?? Please

trainLabels.at<int>( r, 0 ) = r; Is the line fine (or) do I need to assign Labels something differently?? Please

Please look into it and let me know,if I am using SVM Properly.

for ( size_t c = 0; c < Tn.size(); c++ ) { testData.at<float>( 0, c * 2 ) =

for ( size_t c = 0; c < Tn.size(); c++ ) { testData.at<float>( 0, c * 2 ) = Tn.at(c

for ( size_t c = 0; c < Tn.size(); c++ ) { testData.at<float>( 0, c * 2 ) = Tn.at(c).x;

for ( size_t r = 0; r < trainingList.size(); r++ ) { for ( size_t c = 0; c < trainingList.at(r

This if my final revised code: void getSCMCategoryClass( std::vector<Point2d> Tn, std::vector<Point2d> R1n,

yeah,right.I changed it to FLOAT Now..But results are really bad in this case :(..I dont think, 1$'s normalize() functio

Really,wierd,I just changed my code..instead of "double",I used "float" dataType and it runs fine now!

not sure,why its happening, the MAT Size here is 3x390.In the first 'for loop' itself,it is going into excpetion. Wierd!