Denoising ExampleΒΆ
using NBInclude
using Plots
@nbinclude("GPUFilterBanks.ipynb");
@nbinclude("AudioTools.ipynb");
tetris = load("korobeiniki.wav");
fs = round(Int,tetris.samplerate);
original = audio_to_float( truncate_audio(tetris.data,nextpow(2,10*fs)) );
noisy = original .+ Float32.(0.01*randn(size(original)));
float_to_audio(original,fs)
float_to_audio(noisy,fs)
num_octaves = 10;
filters = [
WT.makeqmfpair(wavelet(WT.haar)),
WT.makereverseqmfpair(wavelet(WT.haar))
];
LA = tensor(Float32.(filters[1][1]));
HA = tensor(Float32.(filters[1][2]));
LS = tensor(Float32.(filters[2][1]));
HS = tensor(Float32.(filters[2][2]));
x = [tensor(original)];
size.(x)
1-element Vector{NTuple{4, Int64}}:
(524288, 1, 1, 1)
y = analysis_filterbank(x, LA, HA)
size.(y)
11-element Vector{NTuple{4, Int64}}:
(8192, 32, 1, 1)
(4096, 32, 1, 1)
(2048, 32, 1, 1)
(1024, 32, 1, 1)
(512, 32, 1, 1)
(256, 32, 1, 1)
(128, 32, 1, 1)
(64, 32, 1, 1)
(32, 32, 1, 1)
(16, 32, 1, 1)
(16, 32, 1, 1)
S1 = [];
S2 = [];
for octave β 1:(num_octaves+1)
y_i = collect(y[octave]);
h = heatmap(abs.(y_i[:,:]'),
axis=nothing, colorbar=nothing, size=(1000,2000));
append!(S1,[h]);
threshold = CuArray(
fill(Float32(0.2*(2.0^-octave)),
size(y[octave])
)
);
y[octave] .= y[octave] .* Float32.( abs.(y[octave]) .> threshold)
y_i = collect(y[octave]);
h = heatmap(abs.(y_i[:,:]'),
axis=nothing, colorbar=nothing, size=(1000,2000));
append!(S2,[h]);
end
x = synthesis_filterbank(y, LS, HS)
size.(x)
1-element Vector{NTuple{4, Int64}}:
(524288, 1, 1, 1)
float_to_audio(collect(x[1][:]),fs)
l = @layout [p1;p2;p3;p4;p5;p6;p7;p8;p9;p10;p11];
plot(S1..., layout=l)
l = @layout [p1;p2;p3;p4;p5;p6;p7;p8;p9;p10;p11];
plot(S2..., layout=l)