from builtins import range
import pyfftw # See https://github.com/pyFFTW/pyFFTW/issues/40
import numpy as np
from sporco import util
from sporco import metric
from sporco import linalg
from sporco import plot
from sporco.admm import tvl2
from sporco.admm import cbpdn
from sporco import cuda
# If running in a notebook, try to use wurlitzer so that output from the CUDA
# code will be properly captured in the notebook.
sys_pipes = util.notebook_system_output()
"""
Load a reference image.
"""
img = util.ExampleImages().image('monarch.png',
zoom=0.5,
scaled=True,
gray=True,
idxexp=np.s_[:, 160:672])
"""
Create random mask and apply to reference image to obtain test image. (The call to ``numpy.random.seed`` ensures that the pseudo-random noise is reproducible.)
"""
np.random.seed(12345)
frc = 0.5
from builtins import input
from builtins import range
import pyfftw # See https://github.com/pyFFTW/pyFFTW/issues/40
import numpy as np
from sporco import util
from sporco import plot
from sporco import cuda
from sporco.admm import cbpdn
import sporco.linalg as spl
import sporco.metric as spm
# If running in a notebook, try to use wurlitzer so that output from the CUDA
# code will be properly captured in the notebook.
sys_pipes = util.notebook_system_output()
"""
Load example image.
"""
img = util.ExampleImages().image('barbara.png', scaled=True, gray=True,
idxexp=np.s_[10:522, 100:612])
"""
Load main dictionary and prepend an impulse filter for lowpass component representation.
"""
Db = util.convdicts()['G:12x12x36']
