def imsave_al(image, im, path):
dic = oib.image_info(im)
if dic['time_interval'] == None:
t = 0
else:
t = float(dic['time_interval'])
sx = (1 / float(dic['xsize']))
filename = [
os.path.splitext(filename)[0] for filename in os.listdir(path)
if filename.endswith(('.nd2'))
]
filename
i = 0
for img in image:
i += 1
filename_save = (path + '/' + ('%s%i' % (filename[0], i)) + '.tif')
filename_save
if os.path.isfile(filename_save) == True:
print 'the file already exist'
else:
tifffile.imsave(filename_save,
img.transpose(0, 1, 4, 2, 3),
imagej=True,
resolution=(sx, sx),
metadata={
'mode': 'color',
'finterval': t,
'unit': 'micron'
})
def align(im, warp_matrix):
dic = oib.image_info(im)
x = int(dic['frame_size_x'])
y = int(dic['frame_size_y'])
c = int(dic['channels'])
z = int(dic['z_steps'])
t = int(dic['time_frames'])
with bioformats.ImageReader(im, perform_init=True) as rdr:
image = np.empty([t, z, y, x, c], np.uint16)
for c in range(c):
image[:, :, :, :, c] = rdr.read(c=1, rescale=False)
image[:, :, :, :, c] = cv2.warpAffine(
(rdr.read(c=0, rescale=False)),
warp_matrix, (y, x),
flags=cv2.INTER_LINEAR + cv2.WARP_INVERSE_MAP)
for t in range(t):
image[t, :, :, :, c] = cv2.warpAffine(
(rdr.read(t=t, z=0, c=0, rescale=False)),
warp_matrix, (y, x),
flags=cv2.INTER_LINEAR + cv2.WARP_INVERSE_MAP)
for z in range(z):
image[:, z, :, :, c] = cv2.warpAffine(
(rdr.read(z=z, c=0, rescale=False)),
warp_matrix, (y, x),
flags=cv2.INTER_LINEAR + cv2.WARP_INVERSE_MAP)
return image
def align(im, warp_matrix):
dic = oib.image_info(im)
x = int(dic['frame_size_x'])
y = int(dic['frame_size_y'])
c = int(dic['channels'])
z = int(dic['z_steps'])
t = int(dic['time_frames'])
with bioformats.ImageReader(im, perform_init=True) as rdr:
image = np.empty([t,z,y,x,c], np.uint16)
for c in range(c):
image[:,:,:,:,c] = rdr.read(c=1, rescale=False)
image[:,:,:,:,c] = cv2.warpAffine((rdr.read(c=0, rescale=False)),
warp_matrix, (y,x), flags=cv2.INTER_LINEAR + cv2.WARP_INVERSE_MAP)
for t in range(t):
image[t,:,:,:,c] = cv2.warpAffine((rdr.read(t=t, z=0, c=0, rescale=False)),
warp_matrix, (y,x), flags=cv2.INTER_LINEAR + cv2.WARP_INVERSE_MAP)
for z in range(z):
image[:,z,:,:,c] = cv2.warpAffine((rdr.read(z=z, c=0, rescale=False)),
warp_matrix, (y,x), flags=cv2.INTER_LINEAR + cv2.WARP_INVERSE_MAP)
return image
def imsave_al(image, im, path):
dic = oib.image_info(im)
if dic['time_interval'] == None:
t = 0
else:
t = float(dic['time_interval'])
sx = (1/float(dic['xsize']))
filename = [os.path.splitext(filename)[0] for filename in os.listdir(path) if filename.endswith(('.nd2'))]
filename
i = 0
for img in image:
i+=1
filename_save = (path+ '/' + ('%s%i' %(filename[0], i)) + '.tif')
filename_save
if os.path.isfile(filename_save) == True:
print 'the file already exist'
else:
tifffile.imsave(filename_save, img.transpose(0,1,4,2,3), imagej=True, resolution = (sx,sx), metadata = {'mode' : 'color', 'finterval' : t, 'unit' : 'micron'})