def _get_ang_scale(ims, bgval, exponent='inf', constraints=None, reports=None):
"""
Given two images, return their scale and angle difference.
Args:
ims (2-tuple-like of 2D ndarrays): The images
bgval: We also pad here in the :func:`map_coordinates`
exponent (float or 'inf'): The exponent stuff, see :func:`similarity`
constraints (dict, optional)
reports (optional)
Returns:
tuple: Scale, angle. Describes the relationship of
the subject image to the first one.
"""
assert len(ims) == 2, \
"Only two images are supported as input"
shape = ims[0].shape
ims_apod = [utils._apodize(im) for im in ims]
dfts = [
fft.fftshift(
fft.fft2(im,
threads=4,
overwrite_input=True,
auto_align_input=True,
auto_contiguous=True,
planner_effort='FFTW_ESTIMATE')) for im in ims_apod
]
filt = _logpolar_filter(shape)
dfts = [dft * filt for dft in dfts]
# High-pass filtering used to be here, but we have moved it to a higher
# level interface
pcorr_shape = _get_pcorr_shape(shape)
log_base = _get_log_base(shape, pcorr_shape[1])
stuffs = [_logpolar(np.abs(dft), pcorr_shape, log_base) for dft in dfts]
(arg_ang, arg_rad), success = _phase_correlation(stuffs[0], stuffs[1],
utils.argmax_angscale,
log_base, exponent,
constraints, reports)
angle = -np.pi * arg_ang / float(pcorr_shape[0])
angle = np.rad2deg(angle)
angle = utils.wrap_angle(angle, 360)
scale = log_base**arg_rad
angle = -angle
scale = 1.0 / scale
if not 0.5 < scale < 2:
raise ValueError(
"Images are not compatible. Scale change %g too big to be true." %
scale)
return scale, angle
def _get_ang_scale(ims, bgval, exponent='inf', constraints=None, reports=None):
"""
Given two images, return their scale and angle difference.
Args:
ims (2-tuple-like of 2D ndarrays): The images
bgval: We also pad here in the :func:`map_coordinates`
exponent (float or 'inf'): The exponent stuff, see :func:`similarity`
constraints (dict, optional)
reports (optional)
Returns:
tuple: Scale, angle. Describes the relationship of
the subject image to the first one.
"""
assert len(ims) == 2, \
"Only two images are supported as input"
shape = ims[0].shape
ims_apod = [utils._apodize(im) for im in ims]
dfts = [fft.fftshift(fft.fft2(im)) for im in ims_apod]
filt = _logpolar_filter(shape)
dfts = [dft * filt for dft in dfts]
# High-pass filtering used to be here, but we have moved it to a higher
# level interface
pcorr_shape = _get_pcorr_shape(shape)
log_base = _get_log_base(shape, pcorr_shape[1])
stuffs = [_logpolar(np.abs(dft), pcorr_shape, log_base) for dft in dfts]
(arg_ang, arg_rad), success = _phase_correlation(stuffs[0], stuffs[1],
utils.argmax_angscale,
log_base, exponent,
constraints, reports)
angle = -np.pi * arg_ang / float(pcorr_shape[0])
angle = np.rad2deg(angle)
angle = utils.wrap_angle(angle, 360)
scale = log_base**arg_rad
angle = -angle
scale = 1.0 / scale
if reports is not None:
reports["shape"] = filt.shape
reports["base"] = log_base
if reports.show("spectra"):
reports["dfts_filt"] = dfts
if reports.show("inputs"):
reports["ims_filt"] = [
fft.ifft2(np.fft.ifftshift(dft)) for dft in dfts
]
if reports.show("logpolar"):
reports["logpolars"] = stuffs
if reports.show("scale_angle"):
reports["amas-result-raw"] = (arg_ang, arg_rad)
reports["amas-result"] = (scale, angle)
reports["amas-success"] = success
extent_el = pcorr_shape[1] / 2.0
reports["amas-extent"] = (log_base**(-extent_el),
log_base**extent_el, -90, 90)
if not 0.5 < scale < 2:
raise ValueError(
"Images are not compatible. Scale change %g too big to be true." %
scale)
return scale, angle
def _get_ang_scale(ims, bgval, exponent='inf', constraints=None, reports=None):
"""
Given two images, return their scale and angle difference.
Args:
ims (2-tuple-like of 2D ndarrays): The images
bgval: We also pad here in the :func:`map_coordinates`
exponent (float or 'inf'): The exponent stuff, see :func:`similarity`
constraints (dict, optional)
reports (optional)
Returns:
tuple: Scale, angle. Describes the relationship of
the subject image to the first one.
"""
assert len(ims) == 2, \
"Only two images are supported as input"
shape = ims[0].shape
ims_apod = [utils._apodize(im) for im in ims]
dfts = [fft.fftshift(fft.fft2(im)) for im in ims_apod]
filt = _logpolar_filter(shape)
dfts = [dft * filt for dft in dfts]
# High-pass filtering used to be here, but we have moved it to a higher
# level interface
pcorr_shape = _get_pcorr_shape(shape)
log_base = _get_log_base(shape, pcorr_shape[1])
stuffs = [_logpolar(np.abs(dft), pcorr_shape, log_base)
for dft in dfts]
(arg_ang, arg_rad), success = _phase_correlation(
stuffs[0], stuffs[1],
utils.argmax_angscale, log_base, exponent, constraints, reports)
angle = -np.pi * arg_ang / float(pcorr_shape[0])
angle = np.rad2deg(angle)
angle = utils.wrap_angle(angle, 360)
scale = log_base ** arg_rad
angle = - angle
scale = 1.0 / scale
if reports is not None:
reports["shape"] = filt.shape
reports["base"] = log_base
if reports.show("spectra"):
reports["dfts_filt"] = dfts
if reports.show("inputs"):
reports["ims_filt"] = [fft.ifft2(np.fft.ifftshift(dft))
for dft in dfts]
if reports.show("logpolar"):
reports["logpolars"] = stuffs
if reports.show("scale_angle"):
reports["amas-result-raw"] = (arg_ang, arg_rad)
reports["amas-result"] = (scale, angle)
reports["amas-success"] = success
extent_el = pcorr_shape[1] / 2.0
reports["amas-extent"] = (
log_base ** (-extent_el), log_base ** extent_el,
-90, 90
)
if not 0.5 < scale < 2:
raise ValueError(
"Images are not compatible. Scale change %g too big to be true."
% scale)
return scale, angle