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import tensorflow as tf
import tensorflow_io as tfio
import IPython.display as ipd
import matplotlib.pyplot as plt
import scipy as sp
import PIL.Image
import numpy as np
def wav_to_tf(filename):
bits = tf.io.read_file(filename)
x = tfio.audio.decode_wav(bits,dtype=tf.int16)[:,0]
x = tf.cast(x,tf.float32)
x = x - tf.math.reduce_mean(x);
x = x / tf.math.reduce_std(x)
return tf.Variable(x)
def play(x,rate=24000):
ipd.display(ipd.Audio(x,rate=rate,autoplay=False))
def slog(x):
return tf.sign(x) * tf.math.log(1+ tf.math.abs(x) )
def show(X,clim=(-3,3), xlim=(0,300), ylim=(0,100)):
plt.figure(figsize=(15,6),dpi=200)
plt.imshow(tf.transpose(X),origin='lower',cmap='RdBu')
plt.colorbar()
plt.clim(clim)
plt.xlim(xlim)
plt.ylim(ylim)
def mdct(x,L=624):
X = tf.signal.mdct(x,L);
return tf.Variable(X)
def imdct(X):
y = tf.signal.inverse_mdct(X)
return y
Γ = sp.special.gamma
def F(x,μ,σ,γ):
return sp.stats.gennorm.cdf(x, beta=γ, loc=μ, scale=σ)
def Finv(x,μ,σ,γ):
return sp.stats.gennorm.ppf(x, beta=γ, loc=μ, scale=σ)
def r(γ):
return Γ(1/γ)*Γ(3/γ)/Γ(2/γ)
def estimate_GGD(X):
μ = tf.math.reduce_mean(X)
σ = tf.math.reduce_std(X)
E = tf.math.reduce_mean(tf.abs(X - μ))
ρ = tf.square(σ/E)
γ = sp.optimize.bisect(lambda γ:r(γ)-ρ, 0.3, 1.5,maxiter=50)
return μ,σ,γ
def tf_to_pil(x):
x = np.array(x)
return PIL.Image.fromarray(x,mode="L")
def pil_to_tf(x):
x = np.array(x)
return tf.convert_to_tensor(x)
def σ_prior(band):
def sc(z,μ,σ,γ):
return sp.stats.skewcauchy.pdf(z, γ, loc=μ, scale=σ)
return 10000*(2*sc(band,20,100,0.9)+sc(band,22,12,0.5))
def img_to_mdct(img):
X = []
q = 256;
Y = pil_to_tf(img)
Y = tf.cast(Y,tf.float32)/q
for i_band in range(512):
band = Y[:,i_band]
σ = σ_prior(i_band)
X.append(Finv(band,0,σ,0.85))
X = tf.stack(X)
X = tf.transpose(X)
X = tf.where(tf.math.is_inf(X), tf.ones_like(X), X)
return tf.cast(X,tf.float32)
def mdct_to_img(X):
Y = []
q = 256;
for i_band in range(512):
band = X[:,i_band]
σ = σ_prior(i_band)
Y.append(F(band,0,σ,0.85))
Y = tf.stack(Y)
Y = tf.transpose(Y)
Y = tf.round(q*Y)
Y = tf.cast(Y,tf.uint8)
return tf_to_pil(Y) |