def read_images_via_bioformats(self, filenames_or_urls):
'''Uses Bioformats to load images.
filenames_or_urls -- list
returns a list of channels as numpy float32 arrays
'''
channels = []
for i, filename_or_url in enumerate(filenames_or_urls):
image = self._read_image_via_bioformats(filename_or_url)
channels += self._extract_channels(filename_or_url, image,
p.image_names[i],
int(p.channels_per_image[i]))
# Check if any images need to be rescaled, and if they are the same
# aspect ratio. If so, do the scaling.
from imagetools import check_image_shape_compatibility
check_image_shape_compatibility(channels)
if p.image_rescale:
from imagetools import rescale
for i in range(len(channels)):
if channels[i].shape != p.image_rescale:
channels[i] = rescale(channels[i], (p.image_rescale[1], p.image_rescale[0]))
return channels
def read_images_via_bioformats(self, filenames_or_urls):
'''Uses Bioformats to load images.
filenames_or_urls -- list
returns a list of channels as numpy float32 arrays
'''
channels = []
for i, filename_or_url in enumerate(filenames_or_urls):
image = self._read_image_via_bioformats(filename_or_url)
channels += self._extract_channels(filename_or_url, image,
p.image_names[i],
int(p.channels_per_image[i]))
# Check if any images need to be rescaled, and if they are the same
# aspect ratio. If so, do the scaling.
from imagetools import check_image_shape_compatibility
check_image_shape_compatibility(channels)
if p.image_rescale:
from imagetools import rescale
for i in range(len(channels)):
if channels[i].shape != p.image_rescale:
channels[i] = rescale(
channels[i], (p.image_rescale[1], p.image_rescale[0]))
return channels
def read_images_old_way(self, fds):
'''fds -- list of file descriptors (filenames or urls)
returns a list of channels as numpy float32 arrays
'''
channels = []
for i, fd in enumerate(fds):
format = fd.split('.')[-1]
if format.upper() in [
'TIF', 'TIFF', 'BMP', 'JPG', 'JPEG', 'PNG', 'GIF', 'C01'
]:
planes = self.ReadBitmap(fd)
elif format.upper() in ['DIB']:
planes = [self.ReadDIB(fd)]
else:
logging.error(
'Image format (%s) not supported. Skipping image "%s".' %
(format, fds))
# Got fewer channels than expected
if len(planes) < int(p.channels_per_image[i]):
raise Exception('CPA found %d channels in the "%s" image at '
'%s, but it was expecting %s as specified '
'by properties field channels_per_image. '
'Please update the channels_per_image field '
'in your properties file, or make sure your '
'images are in the right format.' %
(len(planes), p.image_names[i], fd,
p.channels_per_image[i]))
# Got more channels than expected (load the first ones & warn)
elif len(planes) > int(p.channels_per_image[i]):
logging.warn(
'WARNING: CPA found %d channels in the "%s" image '
'at %s, but it will only load the first %s as '
'specified by properties field channels_per_image.' %
(len(planes), p.image_names[i], fd,
p.channels_per_image[i]))
channels += planes[:int(p.channels_per_image[i])]
# Got as many channels as expected
else:
channels += planes
# Check if any images need to be rescaled, and if they are the same
# aspect ratio. If so, do the scaling.
from imagetools import check_image_shape_compatibility
check_image_shape_compatibility(channels)
if p.image_rescale:
from imagetools import rescale
for i in range(len(channels)):
if channels[i].shape != map(int, p.image_rescale):
channels[i] = rescale(
channels[i],
(int(p.image_rescale[1]), int(p.image_rescale[0])))
return channels
def read_images_old_way(self, fds):
'''fds -- list of file descriptors (filenames or urls)
returns a list of channels as numpy float32 arrays
'''
channels = []
for i, fd in enumerate(fds):
format = fd.split('.')[-1]
if format.upper() in ['TIF', 'TIFF', 'BMP', 'JPG', 'JPEG', 'PNG', 'GIF', 'C01']:
planes = self.ReadBitmap(fd)
elif format.upper() in ['DIB']:
planes = [self.ReadDIB(fd)]
else:
logging.error('Image format (%s) not supported. Skipping image "%s".'%(format, fds))
# Got fewer channels than expected
if len(planes) < int(p.channels_per_image[i]):
raise Exception('CPA found %d channels in the "%s" image at '
'%s, but it was expecting %s as specified '
'by properties field channels_per_image. '
'Please update the channels_per_image field '
'in your properties file, or make sure your '
'images are in the right format.'
%(len(planes),
p.image_names[i],
fd,
p.channels_per_image[i]))
# Got more channels than expected (load the first ones & warn)
elif len(planes) > int(p.channels_per_image[i]):
logging.warn('WARNING: CPA found %d channels in the "%s" image '
'at %s, but it will only load the first %s as '
'specified by properties field channels_per_image.'
%(len(planes),
p.image_names[i],
fd,
p.channels_per_image[i]))
channels += planes[:int(p.channels_per_image[i])]
# Got as many channels as expected
else:
channels += planes
# Check if any images need to be rescaled, and if they are the same
# aspect ratio. If so, do the scaling.
from imagetools import check_image_shape_compatibility
check_image_shape_compatibility(channels)
if p.image_rescale:
from imagetools import rescale
for i in range(len(channels)):
if channels[i].shape != map(int, p.image_rescale):
channels[i] = rescale(channels[i], (int(p.image_rescale[1]), int(p.image_rescale[0])))
return channels
def read_images_via_cp(self, fds):
'''Uses CellProfiler's LoadImagesImageProvider to load images.
fds -- list of file descriptors (filenames or urls)
returns a list of channels as numpy float32 arrays
'''
assert self.load_using_bioformats is not None
channels = []
for i, fd in enumerate(fds):
if p.image_url_prepend and p.image_url_prepend.lower().startswith(
'http://'):
url, ignored_headers = urllib.urlretrieve(
'http://' + urllib2.quote(p.image_url_prepend[7:]) +
urllib2.quote(fd))
else:
url = fd
logging.info('Loading image from "%s"' % (url))
image = self.load_using_bioformats(url)
# Got 1 channel, expected more
if image.ndim == 2 and p.channels_per_image[i] != '1':
raise Exception(
'CPA found %d channels in the "%s" image at '
'%s, but it was expecting %s as specified '
'by properties field channels_per_image. '
'Please update the channels_per_image field '
'in your properties file, or make sure your '
'images are in the right format.' %
(1, p.image_names[i], fd, p.channels_per_image[i]))
# Got fewer channels than expected
elif image.ndim > 2 and image.shape[2] < int(
p.channels_per_image[i]):
raise Exception('CPA found %d channels in the "%s" image at '
'%s, but it was expecting %s as specified '
'by properties field channels_per_image. '
'Please update the channels_per_image field '
'in your properties file, or make sure your '
'images are in the right format.' %
(image.shape[2], p.image_names[i], fd,
p.channels_per_image[i]))
# Got more channels than expected (load the first ones & warn)
elif image.ndim > 2 and image.shape[2] > int(
p.channels_per_image[i]):
logging.warn(
'WARNING: CPA found %d channels in the "%s" image '
'at %s, but it will only load the first %s as '
'specified by properties field channels_per_image.' %
(image.shape[2], p.image_names[i], fd,
p.channels_per_image[i]))
channels += [
image[:, :, i] for i in range(int(p.channels_per_image[i]))
]
# Got as many channels as expected
else:
if image.ndim == 2:
channels += [image]
else:
channels += [image[:, :, i] for i in range(image.shape[2])]
# Check if any images need to be rescaled, and if they are the same
# aspect ratio. If so, do the scaling.
from imagetools import check_image_shape_compatibility
check_image_shape_compatibility(channels)
if p.image_rescale:
from imagetools import rescale
for i in range(len(channels)):
if channels[i].shape != p.image_rescale:
channels[i] = rescale(
channels[i], (p.image_rescale[1], p.image_rescale[0]))
return channels
def read_images_via_cp(self, fds):
'''Uses CellProfiler's LoadImagesImageProvider to load images.
fds -- list of file descriptors (filenames or urls)
returns a list of channels as numpy float32 arrays
'''
assert self.load_using_bioformats is not None
channels = []
for i, fd in enumerate(fds):
if p.image_url_prepend and p.image_url_prepend.lower().startswith('http://'):
url, ignored_headers = urllib.urlretrieve('http://' + urllib2.quote(p.image_url_prepend[7:]) + urllib2.quote(fd))
else:
url = fd
logging.info('Loading image from "%s"'%(url))
image = self.load_using_bioformats(url)
# Got 1 channel, expected more
if image.ndim == 2 and p.channels_per_image[i] != '1':
raise Exception('CPA found %d channels in the "%s" image at '
'%s, but it was expecting %s as specified '
'by properties field channels_per_image. '
'Please update the channels_per_image field '
'in your properties file, or make sure your '
'images are in the right format.'
%(1,
p.image_names[i],
fd,
p.channels_per_image[i]))
# Got fewer channels than expected
elif image.ndim > 2 and image.shape[2] < int(p.channels_per_image[i]):
raise Exception('CPA found %d channels in the "%s" image at '
'%s, but it was expecting %s as specified '
'by properties field channels_per_image. '
'Please update the channels_per_image field '
'in your properties file, or make sure your '
'images are in the right format.'
%(image.shape[2],
p.image_names[i],
fd,
p.channels_per_image[i]))
# Got more channels than expected (load the first ones & warn)
elif image.ndim > 2 and image.shape[2] > int(p.channels_per_image[i]):
logging.warn('WARNING: CPA found %d channels in the "%s" image '
'at %s, but it will only load the first %s as '
'specified by properties field channels_per_image.'
%(image.shape[2],
p.image_names[i],
fd,
p.channels_per_image[i]))
channels += [image[:,:,i] for i in range(int(p.channels_per_image[i]))]
# Got as many channels as expected
else:
if image.ndim == 2:
channels += [image]
else:
channels += [image[:,:,i] for i in range(image.shape[2])]
# Check if any images need to be rescaled, and if they are the same
# aspect ratio. If so, do the scaling.
from imagetools import check_image_shape_compatibility
check_image_shape_compatibility(channels)
if p.image_rescale:
from imagetools import rescale
for i in range(len(channels)):
if channels[i].shape != p.image_rescale:
channels[i] = rescale(channels[i], (p.image_rescale[1], p.image_rescale[0]))
return channels