Классификация LPI-сигналов

function show_sample(data, n, hop, Fs, nfft)
    s = SignalAnalysis.spectrogram(data, n, hop; window=hanning(n), nfft=nfft, fs = Fs, onesided=false)
    t = time(s) .* 1e6

    f = freq(s)
    inds = sortperm(f)
    f = f[inds] .*1e-6   
    z = power(s)[inds, :]

    z = pow2db.(abs.(z))

    fig = heatmap(t, f, z;
        xlabel="Time (ms)",
        ylabel="Frequency (kHz)",
        colorbar_title="dB")
    return z, fig
end


function getImage(z)

    cmax = ceil(maximum(z)/5)*5
    cmin = cmax - 50
    clims = (cmin, cmax)

    zmin, zmax = minimum(z), maximum(z)
    zn = (z .- zmin) ./ (zmax .- zmin)
    img_rgb = similar(zn, RGB{Float32})
    for I in CartesianIndices(zn)
        i, j = Tuple(I)
        img_rgb[end-i+1, j] = ColorSchemes.alpine[zn[i,j]]
    end
    img_rgb = imresize(img_rgb, (224, 224))
    return img_rgb
end

function getBinary(img_rgb, threshold)
    gray_img = Gray.(img_rgb)
    binary_thresh = Gray.(gray_img .> threshold)
    return binary_thresh
end

function calcHoG(bnr)
    img_f = Float32.(bnr)
    features = create_descriptor(img_f, HOG())
    return features
end