def display (image, palette_name = "grayscale", title = None , color_index_max = None) :
"""
"""
w = SlideViewer()
if not isinstance(image,SpatialImage):
image = SpatialImage(image)
if image.ndim < 3 :
image = image.reshape(image.shape + (1,))
if color_index_max is None :
cmax = image.max()
else :
cmax = color_index_max
palette = palette_factory(palette_name,cmax)
w.set_palette(palette,palette_name)
w.set_image(image)
w.set_title(title)
w.show()
return w
def display (image, palette_name = "grayscale", title = None , color_index_max = None) :
"""
"""
w = SlideViewer()
if not isinstance(image,SpatialImage):
image = SpatialImage(image)
if image.ndim < 3 :
image = image.reshape(image.shape + (1,))
if color_index_max is None :
cmax = image.max()
else :
cmax = color_index_max
palette = palette_factory(palette_name,cmax)
w.set_palette(palette,palette_name)
w.set_image(image)
w.set_title(title)
w.show()
return w
def point_selection (image, palette_name = "grayscale", color_index_max = None) :
if not isinstance(image,SpatialImage):
image = SpatialImage(image)
w = PointSelection()
w.set_image(image)
if color_index_max is None :
cmax = image.max()
else :
cmax = color_index_max
palette = palette_factory(palette_name,cmax)
w.set_palette(palette)
w.show()
return w
def point_selection(image, palette_name="grayscale", color_index_max=None):
if not isinstance(image, SpatialImage):
image = SpatialImage(image)
w = PointSelection()
w.set_image(image)
if color_index_max is None:
cmax = image.max()
else:
cmax = color_index_max
palette = palette_factory(palette_name, cmax)
w.set_palette(palette)
w.show()
return w
def imread(filename, channel_names=None):
javabridge.start_vm(class_path=bioformats.JARS)
reader = bioformats.get_image_reader(path=filename, key=0)
n_series = reader.rdr.getSeriesCount()
metadata_xml = bioformats.get_omexml_metadata(
path=filename).encode('utf-8')
img_metadata = bioformats.OMEXML(metadata_xml)
bit_dtypes = {}
bit_dtypes[8] = np.uint8
bit_dtypes[16] = np.uint16
img_series = {}
for s in range(n_series)[:1]:
reader.rdr.setSeries(s)
img = np.array([[
reader.read(c=None, z=z, t=t)
for z in xrange(reader.rdr.getSizeZ())
] for t in xrange(reader.rdr.getSizeT())])
if reader.rdr.getSizeC() == 1:
img = img[:, :, :, :, np.newaxis]
# img = np.transpose(img,(0,4,2,3,1))
img = np.transpose(img, (1, 4, 3, 2, 0))
series_name = img_metadata.image(s).Name
vx = get_float_attr(img_metadata.image(s).Pixels.node, "PhysicalSizeX")
vy = get_float_attr(img_metadata.image(s).Pixels.node, "PhysicalSizeY")
vz = get_float_attr(img_metadata.image(s).Pixels.node, "PhysicalSizeZ")
vx = 1 if vx is None else vx
vy = 1 if vy is None else vy
vz = 1 if vz is None else vz
print(vx, vy, vz)
bits = get_int_attr(
img_metadata.image(s).Pixels.node, "SignificantBits")
if img.shape[0] > 1:
for t in xrange(img.shape[0]):
img_series[series_name + "_T" + str(t).zfill(2)] = {}
for c in xrange(img.shape[1]):
image = SpatialImage(img[t, c], voxelsize=(vx, vy, vz))
if (image.max() <= 1.0):
image = image * (np.power(2, bits) - 1)
image = image.astype(bit_dtypes[bits])
if channel_names is not None and len(
channel_names) == img.shape[1]:
channel_id = channel_names[c]
else:
channel_id = img_metadata.image(s).Pixels.Channel(c).ID
if channel_id is None:
channel_id = "C" + str(c)
img_series[series_name + "_T" +
str(t).zfill(2)][channel_id] = image
if img.shape[1] == 1:
img_series[series_name + "_T" +
str(t).zfill(2)] = img_series[
series_name + "_T" +
str(t).zfill(2)].values()[0]
else:
img_series[series_name] = {}
for c in xrange(img.shape[1]):
image = np.copy(img[0, c])
if (image.max() <= 1.0):
image = image * (np.power(2, bits) - 1)
image = image.astype(bit_dtypes[bits])
image = SpatialImage(image, voxelsize=(vx, vy, vz))
if channel_names is not None and len(
channel_names) == img.shape[1]:
channel_id = channel_names[c]
else:
channel_id = img_metadata.image(s).Pixels.Channel(c).Name
if channel_id is None:
channel_id = img_metadata.image(s).Pixels.Channel(c).ID
if channel_id is None:
channel_id = "C" + str(c)
img_series[series_name][channel_id] = image
if img.shape[1] == 1:
img_series[series_name] = img_series[series_name].values()[0]
if n_series == 1:
return img_series.values()[0]
else:
return img_series
