def rescaleImage(im,
imextent,
mvx=None,
mvy=None,
verbose=0,
interpolation=None,
fig=None):
""" Scale image to make pixels at specified resolution
Args:
im (array): input image
imextent (list of 4 floats): coordinates of image region (x0, x1, y0, y1)
mvx, mvy (float or None): number of units per pixel requested. If None then keep unchanged
Returns:
ims (array): transformed image
H (array): transformation matrix from units to pixels. H is the homogeneous transform from original to
scaled image
mvx (float): internal data
mvy (float): internal data
fx (float): internal data
dy (float): internal data
"""
if interpolation is None:
interpolation = cv2.INTER_AREA
dxmv = imextent[1] - imextent[0]
dymv = imextent[3] - imextent[2]
dx = im.shape[1]
dy = im.shape[0]
mvx0 = dxmv / float(dx - 1) # current unit/pixel
mvy0 = dymv / float(dy - 1)
if mvy is None:
mvy = mvy0
if mvx is None:
mvx = mvx0
if im.dtype == np.int64 or im.dtype == np.int32:
# opencv cannot handle int32 or int64 in resize
im = im.astype(np.float32)
# scale factors
fw = np.abs((float(mvx0) / mvx))
fh = np.abs((float(mvy0) / mvy))
if verbose:
print('rescaleImage: scale factorf x %.4f, factor y %.4f' % (fw, fh))
print('rescaleImage: result unit/pixel x %.4f y %.4f' % (mvx, mvy))
# scale in steps for the horizontal direction
if fw < .5:
fwx = fw
fac = 1
ims = im
while fwx < .5:
ims = cv2.resize(ims,
None,
fx=.5,
fy=1,
interpolation=cv2.INTER_LINEAR)
fwx *= 2
fac *= 2
# print('fw %f, fwx %f, fac %f' % (fw, fwx, fac))
ims = cv2.resize(ims,
None,
fx=fac * fw,
fy=fh,
interpolation=interpolation)
else:
ims = cv2.resize(im, None, fx=fw, fy=fh, interpolation=interpolation)
H = pgeometry.pg_transl2H([-.5, -.5]).dot(
np.diag([fw, fh, 1]).dot(pgeometry.pg_transl2H([.5, .5])))
if fig is not None:
plt.figure(fig)
plt.clf()
plt.subplot(1, 2, 1)
plt.imshow(im, interpolation='nearest')
plt.subplot(1, 2, 2)
plt.imshow(ims, interpolation='nearest')
plt.title('scaled')
return ims, H, (mvx, mvy, fw, fh)
def straightenImage(im,
imextent,
mvx=1,
mvy=None,
verbose=0,
interpolation=cv2_interpolation):
""" Scale image to make square pixels
Arguments
---------
im: array
input image
imextend: list of 4 floats
coordinates of image region (x0, x1, y0, y1)
mvx, mvy : float
number of mV per pixel requested
Returns
-------
ims: numpy array
transformed image
(fw, fh, mvx, mvy, H) : data
H is the homogeneous transform from original to straightened image
"""
if cv2 is None:
raise Exception(
'opencv is not installed, method straightenImage is not available')
dxmv = imextent[1] - imextent[0]
dymv = imextent[3] - imextent[2]
dx = im.shape[1]
dy = im.shape[0]
mvx0 = dxmv / float(dx - 1) # mv/pixel
mvy0 = dymv / float(dy - 1)
if mvy is None:
mvy = mvx
fw = np.abs((float(mvx0) / mvx))
fh = np.abs((float(mvy0) / mvy))
if fw < .5:
fwx = fw
fac = 1
ims = im
while (fwx < .5):
ims = cv2.resize(ims,
None,
fx=.5,
fy=1,
interpolation=cv2.INTER_LINEAR)
fwx *= 2
fac *= 2
ims = cv2.resize(ims,
None,
fx=fac * fw,
fy=fh,
interpolation=interpolation)
else:
ims = cv2.resize(im, None, fx=fw, fy=fh, interpolation=interpolation)
if verbose:
print('straightenImage: size %s fx %.4f fy %.4f' % (im.shape, fw, fh))
print('straightenImage: result size %s mvx %.4f mvy %.4f' %
(ims.shape, mvx, mvy))
H = pgeometry.pg_transl2H([-.5, -.5]).dot(
np.diag([fw, fh, 1]).dot(pgeometry.pg_transl2H([.5, .5])))
return ims, (fw, fh, mvx, mvy, H)