geany mri errors #84

edmontz · 2022-05-17T01:30:54Z

edmontz
May 17, 2022

This most likely will make me rather unpopular on this discussion board.

After upgrading to Geany 1.38 for my Ubuntu 20.04 LTS distribution, setting Julia 1.7.2 for use from Geany and running the following code,
`

using Pkg

Pkg.add("MRIReco")
Pkg.add("PlutoUI")
Pkg.add("ImageUtils")
Pkg.add("FFTW")
Pkg.add("Wavelets")
Pkg.add("LinearOperators")

include("MRIRecoTutorial.jl")

`

I get these [ error ] messages.

Info: Bruker protocol name : T2_RARE
Direct Reconstruction... 100%|███████████████████████████| Time: 0:00:01
ERROR: LoadError: TaskFailedException

nested task error: WARNING: both Images and ColorVectorSpace export "complement"; uses of it in module ImageUtils must be qualified

WARNING: both Distributions and ImageUtils export "entropy"; uses of it in module MRIReco must be qualified
WARNING: both Distributions and MRIBase export "scale"; uses of it in module MRIReco must be qualified
MethodError: no method matching storage_type(::MRIReco.CompositeOp{ComplexF32})
Closest candidates are:
storage_type(::LinearOperator) at ~/.julia/packages/LinearOperators/ER4po/src/abstract.jl:168
storage_type(::AbstractMatrix{T}) where T at ~/.julia/packages/LinearOperators/ER4po/src/abstract.jl:169
storage_type(::Union{AdjointLinearOperator, TransposeLinearOperator}) at ~/.julia/packages/LinearOperators/ER4po/src/adjtrans.jl:77
...
Stacktrace:
[1] storage_type(A::AdjointLinearOperator{ComplexF32, MRIReco.CompositeOp{ComplexF32}})
@ LinearOperators ~/.julia/packages/LinearOperators/ER4po/src/adjtrans.jl:77
[2] *(op1::AdjointLinearOperator{ComplexF32, MRIReco.CompositeOp{ComplexF32}}, op2::MRIReco.CompositeOp{ComplexF32})
@ LinearOperators ~/.julia/packages/LinearOperators/ER4po/src/operations.jl:118
[3] RegularizedLeastSquares.ADMM(A::MRIReco.CompositeOp{ComplexF32}, x::Vector{ComplexF32}; reg::Vector{Regularization}, regName::Vector{String}, λ::Float64, regTrafo::Nothing, AᴴA::Nothing, precon::IterativeSolvers.Identity, ρ::Float64, iterations::Int64, iterationsInner::Int64, absTol::Float64, relTol::Float64, tolInner::Float64, normalizeReg::Bool, vary_ρ::Bool, verbose::Bool, kargs::Base.Pairs{Symbol, Any, NTuple{7, Symbol}, NamedTuple{(:sparseTrafo, :solver, :senseMaps, :regularization, :sparseTrafoName, :reco, :reconSize), Tuple{String, String, Array{ComplexF32, 4}, String, String, String, Tuple{Int64, Int64}}}})
@ RegularizedLeastSquares ~/.julia/packages/RegularizedLeastSquares/37BYe/src/ADMM.jl:106
[4] createLinearSolver(solver::String, A::MRIReco.CompositeOp{ComplexF32}, x::Vector{ComplexF32}; log::Bool, kargs::Base.Pairs{Symbol, Any, NTuple{15, Symbol}, NamedTuple{(:reg, :absTol, :normalizeReg, :sparseTrafo, :relTol, :tolInner, :solver, :senseMaps, :regularization, :sparseTrafoName, :λ, :reco, :ρ, :iterations, :reconSize), Tuple{Vector{Regularization}, Float64, Bool, String, Float64, Float64, String, Array{ComplexF32, 4}, String, String, Float64, String, Float64, Int64, Tuple{Int64, Int64}}}})
@ RegularizedLeastSquares ~/.julia/packages/RegularizedLeastSquares/37BYe/src/RegularizedLeastSquares.jl:110
[5] macro expansion
@ ~/.julia/packages/MRIReco/FJtw1/src/Reconstruction/IterativeReconstruction.jl:191 [inlined]
[6] (::MRIReco.var"#199#200"{AcquisitionData{Float32}, Tuple{Int64, Int64}, Vector{Regularization}, Vector{Vector{ComplexF32}}, String, Array{ComplexF32, 4}, Nothing, Dict{Symbol, Any}, Dict{Any, Any}, Int64, Int64, Int64})()
@ MRIReco ./threadingconstructs.jl:178
Stacktrace:
[1] sync_end(c::Channel{Any})
@ Base ./task.jl:381
[2] macro expansion
@ ./task.jl:400 [inlined]
[3] reconstruction_multiCoil(acqData::AcquisitionData{Float32}, reconSize::Tuple{Int64, Int64}, reg::Vector{Regularization}, sparseTrafo::LinearOperator{ComplexF64, Int64, SparsityOperators.var"#1#2"{SparsityOperators.var"#28#30"{Tuple{Int64, Int64}, OrthoFilter{Wavelets.WT.PerBoundary}}}, Nothing, SparsityOperators.var"#1#2"{SparsityOperators.var"#29#31"{Tuple{Int64, Int64}, OrthoFilter{Wavelets.WT.PerBoundary}}}, Vector{ComplexF64}}, weights::Vector{Vector{ComplexF32}}, solvername::String, senseMaps::Array{ComplexF32, 4}, normalize::Bool, encodingOps::Nothing, params::Dict{Symbol, Any})
@ MRIReco ~/.julia/packages/MRIReco/FJtw1/src/Reconstruction/IterativeReconstruction.jl:178
[4] reconstruction(acqData::AcquisitionData{Float32}, recoParams::Dict{Symbol, Any})
@ MRIReco ~/.julia/packages/MRIReco/FJtw1/src/Reconstruction/Reconstruction.jl:39
[5] top-level scope
@ ~/Downloads/DevJulia/MRIRecoTutorial.jl:518
in expression starting at /home/edward/Downloads/DevJulia/MRIRecoTutorial.jl:502

(program exited with code: 1)
Press return to continue

Answered by edmontz

May 28, 2022

Editor problems remain, shall attempt to include code as a text file attachment, you need to change the txt extension to jl.
mri_reco4.txt

I also tested this using Windows 10, 64 bit and the same versions of Geany and Julia as I did with Ubuntu 20.04, x86_64;
the results appear to be identical.

View full answer

aTrotier · 2022-05-17T08:57:45Z

aTrotier
May 17, 2022
Collaborator

It might be related to this issue : JuliaImageRecon/RegularizedLeastSquares.jl#39 and

Can you try to change the line https://github.com/MagneticResonanceImaging/MRIRecoTutorial/blob/99150d21a912fb6c10b9a5c3ea6499a44c4d4ff6/MRIRecoTutorial.jl#L509

to params[:λ] = Float32(2.e-1) and let us know if it works

1 reply

edmontz May 17, 2022
Author

Continues to produce errors similar to previous, maybe a more extensive problem with type casting ?

These [error] messages are now returned, after including your recommended code

ERROR: LoadError: TaskFailedException

nested task error: WARNING: both Images and ColorVectorSpace export "complement"; uses of it in module ImageUtils must be qualified

WARNING: both Distributions and ImageUtils export "entropy"; uses of it in module MRIReco must be qualified
WARNING: both Distributions and MRIBase export "scale"; uses of it in module MRIReco must be qualified
MethodError: no method matching storage_type(::MRIReco.CompositeOp{ComplexF32})
Closest candidates are:
storage_type(::LinearOperator) at ~/.julia/packages/LinearOperators/ER4po/src/abstract.jl:168
storage_type(::AbstractMatrix{T}) where T at ~/.julia/packages/LinearOperators/ER4po/src/abstract.jl:169
storage_type(::Union{AdjointLinearOperator, TransposeLinearOperator}) at ~/.julia/packages/LinearOperators/ER4po/src/adjtrans.jl:77
...
Stacktrace:
[1] storage_type(A::AdjointLinearOperator{ComplexF32, MRIReco.CompositeOp{ComplexF32}})
@ LinearOperators ~/.julia/packages/LinearOperators/ER4po/src/adjtrans.jl:77
[2] *(op1::AdjointLinearOperator{ComplexF32, MRIReco.CompositeOp{ComplexF32}}, op2::MRIReco.CompositeOp{ComplexF32})
@ LinearOperators ~/.julia/packages/LinearOperators/ER4po/src/operations.jl:118
[3] RegularizedLeastSquares.ADMM(A::MRIReco.CompositeOp{ComplexF32}, x::Vector{ComplexF32}; reg::Vector{Regularization}, regName::Vector{String}, λ::Float32, regTrafo::Nothing, AᴴA::Nothing, precon::IterativeSolvers.Identity, ρ::Float64, iterations::Int64, iterationsInner::Int64, absTol::Float64, relTol::Float64, tolInner::Float64, normalizeReg::Bool, vary_ρ::Bool, verbose::Bool, kargs::Base.Pairs{Symbol, Any, NTuple{7, Symbol}, NamedTuple{(:sparseTrafo, :solver, :senseMaps, :regularization, :sparseTrafoName, :reco, :reconSize), Tuple{String, String, Array{ComplexF32, 4}, String, String, String, Tuple{Int64, Int64}}}})
@ RegularizedLeastSquares ~/.julia/packages/RegularizedLeastSquares/37BYe/src/ADMM.jl:106
[4] createLinearSolver(solver::String, A::MRIReco.CompositeOp{ComplexF32}, x::Vector{ComplexF32}; log::Bool, kargs::Base.Pairs{Symbol, Any, NTuple{15, Symbol}, NamedTuple{(:reg, :absTol, :normalizeReg, :sparseTrafo, :relTol, :tolInner, :solver, :senseMaps, :regularization, :sparseTrafoName, :λ, :reco, :ρ, :iterations, :reconSize), Tuple{Vector{Regularization}, Float64, Bool, String, Float64, Float64, String, Array{ComplexF32, 4}, String, String, Float32, String, Float64, Int64, Tuple{Int64, Int64}}}})
@ RegularizedLeastSquares ~/.julia/packages/RegularizedLeastSquares/37BYe/src/RegularizedLeastSquares.jl:110
[5] macro expansion
@ ~/.julia/packages/MRIReco/FJtw1/src/Reconstruction/IterativeReconstruction.jl:191 [inlined]
[6] (::MRIReco.var"#199#200"{AcquisitionData{Float32}, Tuple{Int64, Int64}, Vector{Regularization}, Vector{Vector{ComplexF32}}, String, Array{ComplexF32, 4}, Nothing, Dict{Symbol, Any}, Dict{Any, Any}, Int64, Int64, Int64})()
@ MRIReco ./threadingconstructs.jl:178
Stacktrace:
[1] sync_end(c::Channel{Any})
@ Base ./task.jl:381
[2] macro expansion
@ ./task.jl:400 [inlined]
[3] reconstruction_multiCoil(acqData::AcquisitionData{Float32}, reconSize::Tuple{Int64, Int64}, reg::Vector{Regularization}, sparseTrafo::LinearOperator{ComplexF64, Int64, SparsityOperators.var"#1#2"{SparsityOperators.var"#28#30"{Tuple{Int64, Int64}, OrthoFilter{Wavelets.WT.PerBoundary}}}, Nothing, SparsityOperators.var"#1#2"{SparsityOperators.var"#29#31"{Tuple{Int64, Int64}, OrthoFilter{Wavelets.WT.PerBoundary}}}, Vector{ComplexF64}}, weights::Vector{Vector{ComplexF32}}, solvername::String, senseMaps::Array{ComplexF32, 4}, normalize::Bool, encodingOps::Nothing, params::Dict{Symbol, Any})
@ MRIReco ~/.julia/packages/MRIReco/FJtw1/src/Reconstruction/IterativeReconstruction.jl:178
[4] reconstruction(acqData::AcquisitionData{Float32}, recoParams::Dict{Symbol, Any})
@ MRIReco ~/.julia/packages/MRIReco/FJtw1/src/Reconstruction/Reconstruction.jl:39
[5] top-level scope
@ ~/Downloads/DevJulia/MRIRecoTutorial.jl:518
in expression starting at /home/edward/Downloads/DevJulia/MRIRecoTutorial.jl:502

alexjaffray · 2022-05-17T20:19:29Z

alexjaffray
May 17, 2022
Collaborator

This issue is related to a discussion in LinearOperators and changes therein from the recent 2.3.x releases. There has been some investigation of this by myself and @migrosser and we are finding a solution hopefully. I will try your example on the master.

I would encourage you to try the example yourself on the master branch of the package. This can be done by switching the version of your MRIReco package in the REPL via the following:

]add MRIReco#master

3 replies

edmontz May 17, 2022
Author

After updating, as suggested, through REPL, then running Geany; the following is generated.
This is somewhat different than previous.
Installed StrideArraysCore ─ v0.3.6
Installed Polyester ──────── v0.6.9
Updating ~/.julia/environments/v1.7/Project.toml
[bdf86e05] ~ MRIReco v0.5.1 https://github.com/MagneticResonanceImaging/MRIReco.jl.git#master ⇒ v0.5.0
Updating ~/.julia/environments/v1.7/Manifest.toml
[fb6a15b2] + CloseOpenIntervals v0.1.6
[bdf86e05] ~ MRIReco v0.5.1 https://github.com/MagneticResonanceImaging/MRIReco.jl.git#master ⇒ v0.5.0
[f517fe37] + Polyester v0.6.9
[1d0040c9] + PolyesterWeave v0.1.5
[7792a7ef] + StrideArraysCore v0.3.6
[8290d209] + ThreadingUtilities v0.5.0
Precompiling project...
3 dependencies successfully precompiled in 20 seconds (312 already precompiled)
Resolving package versions...
No Changes to ~/.julia/environments/v1.7/Project.toml
No Changes to ~/.julia/environments/v1.7/Manifest.toml
Resolving package versions...
No Changes to ~/.julia/environments/v1.7/Project.toml
No Changes to ~/.julia/environments/v1.7/Manifest.toml
Resolving package versions...
No Changes to ~/.julia/environments/v1.7/Project.toml
No Changes to ~/.julia/environments/v1.7/Manifest.toml
Resolving package versions...
No Changes to ~/.julia/environments/v1.7/Project.toml
No Changes to ~/.julia/environments/v1.7/Manifest.toml
Resolving package versions...
No Changes to ~/.julia/environments/v1.7/Project.toml
No Changes to ~/.julia/environments/v1.7/Manifest.toml
Resolving package versions...
No Changes to ~/.julia/environments/v1.7/Project.toml
No Changes to ~/.julia/environments/v1.7/Manifest.toml
[ Info: Bruker protocol name : T2_RARE
Direct Reconstruction... 100%|███████████████████████████| Time: 0:00:01
ERROR: LoadError: MethodError: no method matching LinearOperator(::Int64, ::Int64, ::Bool, ::Bool, ::var"#10#12"{Matrix{ComplexF64}, Tuple{Int64, Int64}, Tuple{Int64, Int64}, Float64, Int64}, ::Nothing, ::var"#11#13"{Matrix{ComplexF64}, Tuple{Int64, Int64}, Tuple{Int64, Int64}})
Closest candidates are:
LinearOperator(::Type{T}, ::I, ::I, ::Bool, ::Bool, ::Any, ::Any) where {T, I<:Integer} at ~/.julia/packages/LinearOperators/rejMT/src/constructors.jl:96
LinearOperator(::Type{T}, ::I, ::I, ::Bool, ::Bool, ::Any, ::Any, ::Any) where {T, I<:Integer} at ~/.julia/packages/LinearOperators/rejMT/src/constructors.jl:96
LinearOperator(::Type{T}, ::I, ::I, ::Bool, ::Bool, ::Any) where {T, I<:Integer} at ~/.julia/packages/LinearOperators/rejMT/src/constructors.jl:96
Stacktrace:
[1] dictOp(D::Matrix{ComplexF64}, xsize::Tuple{Int64, Int64}, psize::Tuple{Int64, Int64}, tol::Float64, nmax::Int64)
@ Main ~/Downloads/DevJulia/MRIRecoTutorial.jl:583
[2] top-level scope
@ ~/Downloads/DevJulia/MRIRecoTutorial.jl:604
[3] include(fname::String)
@ Base.MainInclude ./client.jl:451
[4] top-level scope
@ ~/Downloads/DevJulia/MRI_reco2.jl:16
in expression starting at /home/edward/Downloads/DevJulia/MRIRecoTutorial.jl:593
in expression starting at /home/edward/Downloads/DevJulia/MRI_reco2.jl:16

(program exited with code: 1)
Press return to continue

edmontz May 19, 2022
Author

Function parameter types don't match, though the function names are the same.

ERROR: LoadError: MethodError: no method matching

LinearOperator(::Int64, ::Int64, ::Bool, ::Bool, ::var"#10#12"{Matrix{ComplexF64}, Tuple{Int64, Int64}, Tuple{Int64, Int64}, Float64, Int64}, ::Nothing, ::var"#11#13"{Matrix{ComplexF64}, Tuple{Int64, Int64}, Tuple{Int64, Int64}})

Closest candidates are:

LinearOperator(::Type{T}, ::I, ::I, ::Bool, ::Bool, ::Any, ::Any) where {T, I<:Integer} at ~/.julia/packages/LinearOperators/rejMT/src/constructors.jl:96

Should I purge my system of MRIRreco, and reload as per your last instructions.

alexjaffray May 19, 2022
Collaborator

I will try to reproduce your error with a fresh MRIReco.jl.

alexjaffray · 2022-05-19T22:36:19Z

alexjaffray
May 19, 2022
Collaborator

@edmontz I have gone through the tutorial and have been able to reproduce your error(s). Unfortunately, the errors mostly stem from either active issues in the package which are being fixed, or from the fact that the package has evolved since the tutorial was written, and there are breaking changes in other packages such as LinearOperators and RegularizedLeastSquares which haven't been accounted for.

For now, I think the best thing to do in order to run the tutorial is to make sure that you are using the version of each package that was available when the tutorial was written. I think we will in the future make sure that changes don't break the tutorial.

For me, the package versions that work with the tutorial are as follows:

CUDA v3.10.0
FFTW v1.4.6
ImageUtils v0.2.6
Images v0.23.3
LinearOperators v1.3.1
MRIReco v0.3.5
NFFT v0.6.2
Plots v1.29.0
Pluto v0.14.9
PlutoUI v0.7.1
QuartzImageIO v0.7.3
Wavelets v0.9.4

You can add a specific package version by typing ]add <packagename>@<versionnumber> into the REPL

4 replies

alexjaffray May 19, 2022
Collaborator

If this doesn't work, I would also suggest deleting your manifest file and reverting the Project.toml file for MRIRecoTutorial.jl to how it is in the git repository. Then, instantiate the environment and resolve any package conflicts by updating the offending package. (for me it was CUDA which needed updating for example)

migrosser May 20, 2022
Maintainer

Thanks for pointing this out. The tutorial actually is quite old by now and there recently has been a lot of work in aforementioned packages including MRIReco iteslef. Once I have time, I will go through the tutorial and update it.

edmontz May 27, 2022
Author

After a completely new installation of Ubuntu 20.04, Geany 1.38, Julia 1.7.3;
I installed the mrireco packages.
These packages, along with many others, reside in my .julia directory at
the parent directory of the Documents and Downloads folders.

I used julia with root previledges, terminal -> sudo geany -> pw -> enter.

In Geany, Build, SetBuildCommands, first row, column 'Command' enter the
location of julia, something like this:

/home/edward/Downloads/julia-1.7.3-linux-x86_64/julia-1.7.3/bin/julia

Then for Execute Commands, Execute row, enter the location of julia again
and the command to run the compiled file, like this:

/home/edward/Downloads/julia-1.7.3-linux-x86_64/julia-1.7.3/bin/julia %f

I was eventually able to successfully run all of the tests, from a julia
folder; then elsewhere the following code was effective:

`

using PyPlot, MRIReco

simple example

N = 256

@time begin
I = shepp_logan(N)
end # 0.540256 seconds

simulation parameters

params = Dict{Symbol, Any}()
params[:simulation] = "fast"
params[:trajName] = "Radial"
params[:numProfiles] = floor(Int64, pi/2N)
params[:numSamplingPerProfile] = 2N

do simulation

print(" simulate ")
@time begin
acqData = simulation(I, params)
end # 42.097016 seconds

reco parameters

print(" recon ")
@time begin
params = Dict{Symbol, Any}()
params[:reco] = "direct"
params[:reconSize] = (N,N)
Ireco = reconstruction(acqData, params)
end # 16.087361

use PyPlot for interactive display

print("one")

PyPlot.figure(1)
PyPlot.clf()
@time begin
PyPlot.subplot(1,2,1)
PyPlot.title("Phantom")
PyPlot.imshow(abs.(I))
end # 0.442060 seconds
@time begin
PyPlot.subplot(1,2,2)
PyPlot.title("Reconstruction")
PyPlot.imshow(abs.(Ireco[:,:,1,1,1]))
end # 0.590571 seconds
PyPlot.show()

sleep(20)

export images

filename = joinpath(dirname(pathof(MRIReco)),"../docs/src/assets/simpleReco.png")

exportImage(filename, abs.(Ireco[:,:,1,1,1]))

filename = joinpath(dirname(pathof(MRIReco)),"../docs/src/assets/phantom.png")

exportImage(filename, abs.(I[:,:,1,1,1]))

`

I have yet to attempt the use of a GPU with this particular code.

edmontz May 27, 2022
Author

using PyPlot, MRIReco

N = 256

@time begin
I = shepp_logan(N)
end # 0.540256 seconds

params = Dict{Symbol, Any}()
params[:simulation] = "fast"
params[:trajName] = "Radial"
params[:numProfiles] = floor(Int64, pi/2N)
params[:numSamplingPerProfile] = 2N

do simulation
print(" simulate ")
@time begin
acqData = simulation(I, params)
end # 42.097016 seconds

print(" recon ")
@time begin
params = Dict{Symbol, Any}()
params[:reco] = "direct"
params[:reconSize] = (N,N)
Ireco = reconstruction(acqData, params)
end # 16.087361

use PyPlot for interactive display
print("one")
PyPlot.figure(1)
PyPlot.clf()
@time begin
PyPlot.subplot(1,2,1)
PyPlot.title("Phantom")
PyPlot.imshow(abs.(I))
end # 0.442060 seconds
@time begin
PyPlot.subplot(1,2,2)
PyPlot.title("Reconstruction")
PyPlot.imshow(abs.(Ireco[:,:,1,1,1]))
end # 0.590571 seconds
PyPlot.show()``

edmontz · 2022-05-27T23:05:55Z

edmontz
May 27, 2022
Author

I posted the code again, as comments within the code don't appear as expected.

0 replies

edmontz · 2022-05-28T00:31:16Z

edmontz
May 28, 2022
Author

Editor problems remain, shall attempt to include code as a text file attachment, you need to change the txt extension to jl.
mri_reco4.txt

I also tested this using Windows 10, 64 bit and the same versions of Geany and Julia as I did with Ubuntu 20.04, x86_64;
the results appear to be identical.

1 reply

edmontz May 28, 2022
Author

Runs okay when downloaded then used with either Ubuntu 20.04 x86_64, or Windows 10 64 bit.
Note, all versions of Geany and Julia, are 64 bit.

Provide feedback

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geany mri errors #84

edmontz May 17, 2022

Replies: 5 comments · 9 replies

aTrotier May 17, 2022 Collaborator

edmontz May 17, 2022 Author

alexjaffray May 17, 2022 Collaborator

edmontz May 17, 2022 Author

edmontz May 19, 2022 Author

alexjaffray May 19, 2022 Collaborator

alexjaffray May 19, 2022 Collaborator

alexjaffray May 19, 2022 Collaborator

migrosser May 20, 2022 Maintainer

edmontz May 27, 2022 Author

simple example

simulation parameters

do simulation

reco parameters

use PyPlot for interactive display

print("one")

sleep(20)

export images

filename = joinpath(dirname(pathof(MRIReco)),"../docs/src/assets/simpleReco.png")

exportImage(filename, abs.(Ireco[:,:,1,1,1]))

filename = joinpath(dirname(pathof(MRIReco)),"../docs/src/assets/phantom.png")

exportImage(filename, abs.(I[:,:,1,1,1]))

edmontz May 27, 2022 Author

edmontz May 27, 2022 Author

edmontz May 28, 2022 Author

edmontz May 28, 2022 Author

edmontz
May 17, 2022

Replies: 5 comments 9 replies

aTrotier
May 17, 2022
Collaborator

edmontz May 17, 2022
Author

alexjaffray
May 17, 2022
Collaborator

edmontz May 17, 2022
Author

edmontz May 19, 2022
Author

alexjaffray May 19, 2022
Collaborator

alexjaffray
May 19, 2022
Collaborator

alexjaffray May 19, 2022
Collaborator

migrosser May 20, 2022
Maintainer

edmontz May 27, 2022
Author

edmontz May 27, 2022
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edmontz
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edmontz
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edmontz May 28, 2022
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