I am adapting an old code which uses cvMat. I use the constructor from cvMat :
Mat A(B); // B is a cvMat
When I write A[i][j], I get the error no operator [] match these operands.
Why? For information: B is a single channel float matrix (from a MLData object read from a csv file).
The documentation lists the at operator as being used to access a member.
A.at<int>(i,j); //Or whatever type you are storing.
first, you should have a look at the most basic opencv tutorials
so, if you have a 3channel, bgr image (the most common case), you will have to access it like:
Vec3b & pixel = A.at<Vec3b>(y,x); // we're in row,col world, here !
pixel = Vec3b(17,18,19); // at() returns a reference, so you can *set* that, too.
the 1channel (grayscale) version would look like this:
uchar & pixel = A.at<uchar>(y,x);
since you mention float images:
float & pixel = A.at<float>(y,x);
you can't choose the type at will, you have to use, what's inside the Mat, so try to query A.type() before.
Related
cv::recoverPose has parameter "triangulatedPoints" as seen in documentation, though math behind it is not documented, even in sources (relevant commit on github).
When I use it, I get this matrix in following form:
[0.06596200907402348, 0.1074107606919504, 0.08120752154556411,
0.07162400555712592, 0.1112415181779849, 0.06479560707001968,
0.06812069103377787, 0.07274771866295617, 0.1036230973846902,
0.07643884790206311, 0.09753859499789987, 0.1050111597547035,
0.08431322508162108, 0.08653721971228882, 0.06607013741719928,
0.1088621999959361, 0.1079215237863785, 0.07874160849424018,
0.07888037486261903, 0.07311940086190356;
-0.3474319603010109, -0.3492386196164926, -0.3592673043398864,
-0.3301695131649525, -0.3398606744869519, -0.3240186574427479,
-0.3302508442361889, -0.3534091474425142, -0.3134288005980755,
-0.3456284001726975, -0.3372514921152191, -0.3229005408417835,
-0.3156005118578394, -0.3545418178651592, -0.3427899760859008,
-0.3552801904337188, -0.3368860879000375, -0.3268499974874541,
-0.3221050630233929, -0.3395139819250934;
-0.9334091581425227, -0.9288726274060354, -0.9277125424980246,
-0.9392374374147775, -0.9318967835907961, -0.941870018271934,
-0.9394698966781299, -0.9306592884695234, -0.9419749503870455,
-0.9332801148509925, -0.9343740431697417, -0.9386198310107222,
-0.9431781968459053, -0.9290466865633286, -0.9351167772249444,
-0.9264105322194914, -0.933362882155191, -0.9398254944757025,
-0.9414486961893244, -0.935785675955617;
-0.0607238817598344, -0.0607532477465341, -0.06067768097603395,
-0.06075467523485482, -0.06073245675798231, -0.06078081616640227,
-0.06074754785132623, -0.0606879948481664, -0.06089198212719162,
-0.06071522666667255, -0.06076842109618678, -0.06083346023742937,
-0.06084805655000008, -0.0606931888685702, -0.06071558440082779,
-0.06073329803512636, -0.06078189449161094, -0.06080195858434526,
-0.06083228813425822, -0.06073695721101467]
e.g. 4x20 matrix (in this case there were 20 points). I want to convert this data to std::vector in order to use it in solvePnP. How to do it, what is the math here? Thanks!
OpenCV offers a triangulatePoints function, which has the same output:
points4D 4xN array of reconstructed points in homogeneous coordinates.
Which indicates that each column is a 3D point in homogeneous coordinate system. However your points looks quite not as I would expect. For instance your first point is:
[0.06596200907402348, -0.3474319603010109, -0.9334091581425227, -0.0607238817598344]
But I would expect the last component to be 1.0 already. You should double check if something is not wrong here. You can always remove the "scaling" of the point by dividing each dimension by the last component:
[ x, y z, w ] = w [x/w, y/w, z/w, 1]
And then use the first three parts for your PnP solution.
I hope this helps
I have some scientific project. There are vectors / square matrices of various lengths there. Obviously (for example) a vector of length 2 cannot be added to a vector of length 3 (and so on and so forth). There are several NET libraries, which deal with vectors / matrices. All of them either have generic vectors / matrices OR have some very specific vectors / matrices, which do not suite the needs.
Most, if not all, of these libraries can create a vector from a list or array. Unfortunately, If I mistakenly give an input array of the wrong length, then I will get a vector of the wrong length and then everything will blow up at run time!
I wonder if it is possible to check array length at compile time so that to get a compile error if, let’s say, I try to pass a 5-element array to a vector of length 2 “constructor”. After all, printfn does almost that!
F# type providers come to mind, but I am not sure how to apply them here.
Thanks a lot!
Thanks to the OP for an interesting question. My answer frequency has dropped not because of unwillingness to help but rather that there a few questions that tickles my interest.
We don't have dependent types in F# and F# doesn't support generics with numerical type arguments (like C++).
However we could create distinct types for different dimensions like Dim1, Dim2 and so on and provide them as type arguments.
This would allow us to have a type signature for apply that applies a vector a matrix like this:
let apply (m : Matrix<'R, 'C>) (v : Vector<'C>) : Vector<'R> = …
The code won't compile unless the columns of the matrix matches the length of the vector. In addition; the resulting vector has the length that is rows of the columns.
One way to do this is defining an interface IDimension and some concrete implementions representing the different dimensions.
type IDimension =
interface
abstract Size : int
end
type Dim1 () = class interface IDimension with member x.Size = 1 end end
type Dim2 () = class interface IDimension with member x.Size = 2 end end
The vector and the matrix can then be implemented like this
type Vector<'Dim when 'Dim :> IDimension
and 'Dim : (new : unit -> 'Dim)
> () =
class
let dim = new 'Dim()
let vs = Array.zeroCreate<float> dim.Size
member x.Dim = dim
member x.Values = vs
end
type Matrix<'RowDim, 'ColumnDim when 'RowDim :> IDimension
and 'RowDim : (new : unit -> 'RowDim)
and 'ColumnDim :> IDimension
and 'ColumnDim : (new : unit -> 'ColumnDim)
> () =
class
let rowDim = new 'RowDim()
let columnDim = new 'ColumnDim()
let vs = Array.zeroCreate<float> (rowDim.Size*columnDim.Size)
member x.RowDim = rowDim
member x.ColumnDim = columnDim
member x.Values = vs
end
Finally this allows us to write code like this:
let m76 = Matrix<Dim7, Dim6> ()
let v6 = Vector<Dim6> ()
let v7 = apply m76 v6 // Vector<Dim7>
// Doesn't compile because v7 has the wrong dimension
let vv = apply m76 v7
If you need a wide range of dimensions (because you have an algebra increments/decrements the dimensions of vectors/matrices) you could support that using some smart variant of church numerals.
If this is usable or not is entirely up the reader I think.
PS.
Perhaps unit of measures could have been used for this as well if they applied to more types than floats.
The general term for what you're looking for is dependent types, but F# does not support them.
I've seen an experiment in using type providers to mimic one particular flavor of dependent types (constraining the domain of a primitive type), but I wouldn't expect it to be possible to achieve what you want using type providers in their current form. They seem to be too whimsical for that.
Print format strings appear to be doing that (and in fact printers are a "Hello World" application for dependent types), but actually they work because they get special treatment by the compiler, and the mechanism for that is not extensible.
You're doomed to ensure correct lengths at runtime.
My best bet would be to use structs to encode actual vectors and ensure correctness on the API level that way, map them to arrays at the point where you're interacting with those matrix algebra libraries, then map the results back to structs with ample assertions when done.
The comment from #Justanothermetaprogrammer qualifies as an answer. Here is how it works in the real example. The matrix implementation in the example is based on MathNet.Numerics.LinearAlgebra:
open MathNet.Numerics.LinearAlgebra
type RealMatrix2x2 =
| RealMatrix2x2 of Matrix<double>
static member private createInternal (a : #seq<#seq<double>>) =
matrix a |> RealMatrix2x2
static member create
(
(a11, a12),
(a21, a22)
) =
RealMatrix2x2.createInternal
[|
[| a11; a12|]
[| a21; a22|]
|]
let m2 =
(
(1., 2.),
(3., 4.)
)
|> RealMatrix2x2.create
The tuple signatures and "re-mapping" into #seq<#seq<double>> can be easily code-generated using, for example, Excel or any other convenient tool for as many dimensions as necessary. In fact, the whole class along with any other necessary operator overrides (like multiplication of RealMatrix2x2 by RealMatrix2x2, ...) can be code generated for all necessary dimensions.
I want to apply a log function to images. But it fails showing this error: function is not defined on this type of argument.
uk=imread('image.jpg');
result=log(uk(:,:,1));
I think your problem is that imread returns a matrix of uint8 type. To apply log, you should convert it to double. There are at least 2 ways to do this, one built in, and one from SIVP:
clc;
clear;
im = imread("d:\Attila\PROJECTS\Scilab\Stackoverflow\mixer_crop.jpg");
//imshow(im);
disp(typeof(im(:,:,1)),"Original type:");
//use double
M = double(im(:,:,1));
disp(typeof(M),"Modified type:");
result=log(M);
//imshow(uint8(M));
//use im2double
M2 = im2double(im);
disp(typeof(M2(:,:,1)),"Modified type 2:");
result=log(M2(:,:,1));
//imshow(im2uint8(M2));
I am trying to learn how to use the Sparse Coding algorithm with the mlpack library. When I call Encode() on my instance of mlpack::sparse_coding:SparseCoding, I get the error
[WARN] There are 63 inactive atoms. They will be reinitialized randomly.
error: solve(): solution not found
Is it simply that the algorithm cannot learn a latent representation of the data. Or perhaps it is my usage? The relevant section follows
EDIT: One line was modified to fix an unrelated error, but the original error remains.
double* Application::GetSparseCodes(arma::mat* trainingExample, int atomCount)
{
double* latentRep = new double[atomCount];
mlpack::sparse_coding::SparseCoding<mlpack::sparse_coding::DataDependentRandomInitializer> sc(*trainingExample, Utils::ATOM_COUNT, 1.0);
sc.Encode(Utils::MAX_ITERATIONS);
arma::mat& latentRepMat = sc.Codes();
for (int i = 0; i < atomCount; i++)
latentRep[i] = latentRepMat.at(i, 0);
return latentRep;
}
Some relevant parameters
const static int IMAGE_WIDTH = 20;
const static int IMAGE_HEIGHT = 20;
const static int PIXEL_COUNT = IMAGE_WIDTH * IMAGE_HEIGHT;
const static int ATOM_COUNT = 64;
const static int MAX_ITERATIONS = 100000;
This could be one of a handful of issues but given the description it's a little difficult to tell which of these it is (or if it is something else entirely). However, these three ideas should provide a good place to start:
Matrices in mlpack are column-major. That means each observation should represent a column. If you use mlpack::data::Load() to load, e.g., a CSV file (which are generally one row per observation), it will automatically transpose the dataset. SparseCoding will act oddly if you pass it transposed data. See also http://www.mlpack.org/doxygen.php?doc=matrices.html.
If there are 63 inactive atoms, then only one atom is actually active (given that ATOM_COUNT is 64). This means that the algorithm has found that the best way to represent the dictionary (at a given step) uses only one atom. This could happen if the matrix you are passing consists of all zeros.
mlpack will provide verbose output, which may also be helpful for debugging. Usually this is used by using mlpack's CLI class to parse command-line input, but you can enable verbose output with mlpack::Log::Info.ignoreInput = false. You may obtain a lot of output that way, but it will give a better look at what is going on...
The mlpack project has its own mailing list where you may be likely to get a quicker or more comprehensive response, by the way.
I m currently working on a painting app on ios.
I use a directly draw into a NSMutableData buffer and apply blending with my brush like this:
- (void) combineColorDestination:(unsigned char*) dest source:(unsigned char*) src
{
const unsigned char sra = ((unsigned char *)src)[3];
const float oneminusalpha = 1.0f - (sra / 255.f);
int d[4];
for (int i=0;i<4;i++)
{
d[i] = oneminusalpha * ((unsigned char *)dest)[i] + ((unsigned char *)src)[i];
if (d[i]>255)
d[i] = 255;
((unsigned char *)dest)[i] = (unsigned char)d[i];
}
}
Any suggestions for optimisations ?
I previously tried to use neon , but i ve got a bug I wasnt able to fix (the bordering pixels was buggy)
I was iterating pixels 2 by 2 like this :
uint8x8_t va = vld1_u8(dest);
uint8x8_t vb = vld1_u8(src);
uint8x8_t res = vqadd_u8(va,vb);
vst1_u8(dest, res);
Suggestions? Alright. Note that these are valid whichever multimedia manipulation you are doing and is hardly restricted to your case.
First, before you even do NEON, you should change your code to have one function that changes a bunch of pixels (at least a row, a rectangle if you can) at once, instead of a function (or method - even worse) that changes one pixel and is called a bunch of times: somehow I doubt the brush is only 1x1 pixel.
Second, except for the column loop (and eventual row loop), there should be no branch (that is, flow control structures). No for (i=0;i<4;i++); just write the code for the four channels in sequence (use a macro if necessary). No if (d[i]>255); express that as an alternative: dest[i] = (temp>255?255:temp); at the very least, if not replacing it by a more efficient way to do saturation (tricks using subtractions, shifts, and masks exist).
Third, avoid any conversion between floating-point and integer; this is always valid advice, but float->int conversions are particularly devastating on ARM. Since you're manipulating integers, this means foregoing floating-point here.
And once you've done that, surprise, besides making your code faster you have in fact done the preparation work for NEON: NEON is only remotely useful if you process a bunch of pixels at once, if there is no branch, and if you don't convert between floating-point and integer all over the place. So only then will we talk about NEON, if it is even necessary at this point.