OMERO Python language bindings¶

MOVIE: introduction to Blitz Gateway

In addition to the auto-generated Python libraries of the core OMERO Application Programming Interface, we have developed a more user-friendly Python module ‘Blitz Gateway’ that facilitates several aspects of working with the Python API, such as connection handling, object graph traversal and lazy loading.

This page gives you a large number of code samples to get you started. Then we describe a bit more about Blitz Gateway documentation.

The Python libraries are part of the server build and can be found under OMERO_HOME/lib/python. These include the core omero.model objects and services as well as the Blitz Gateway code (at OMERO_HOME/lib/python/omero/gateway/__init__.py).

To use OmeroPy, you will need to download the libraries (e.g. as part of the server package) and setup your PYTHONPATH to include them:

export OMERO_PREFIX=~/Desktop/OMERO.server-5.5.1-ice3x-byy       # for example
export PYTHONPATH=$PYTHONPATH:$OMERO_PREFIX/lib/python

You will also need Ice libraries as described in the OMERO.server installation and an OMERO server to connect to, which must be the same major version, i.e. 5.5.x.

All the code examples below can be found at examples/Training/python.

If you want to run the examples, you will need to download and configure them to connect to your own server e.g. HOST = "localhost". You can edit HOST, PORT, USERNAME and PASSWORD in the Parse_OMERO_Properties.py file and these values will be imported into the other scripts.

Then you can run the scripts:

$ python Connect_To_OMERO.py

If all goes well, you should be connected to your OMERO server and see some details of your session printed out.

All the following code examples can be downloaded and run in the same way. Some scripts will also need editing of other parameters, usually IDs from Projects, Datasets, Images etc. You can use the OMERO.insight or OMERO.web client to choose suitable data IDs before editing and running the code samples.

Code samples¶

Connect to OMERO¶

Import OMERO and the BlitzGateway

import omero.clients
from omero.gateway import BlitzGateway

Create a connection

conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()

Create a secure-only connection

By default, once we have logged in, data transfer is not encrypted. To ensure all data is transferred securely pass the secure flag.

conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT, secure=True)
conn.connect()

Create a connection using a context manager

The BlitzGateway should be closed after use to free up server resources. This can be automatically done by using it as a context manager. This also automatically calls connect().

with BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT, secure=True) as conn:
    for p in conn.getObjects('Project'):
        print p.name
    ...
# conn.close() is automatically called

Create a connection using an existing session

The BlitzGateway can also be initialized from an existing omero.client object.

>>> client = omero.client(HOST, PORT)
>>> session = client.createSession(USERNAME, PASSWORD)
>>> conn = BlitzGateway(client_obj=client)

In this example the BlitzGateway and client will not be closed automatically. If nothing else is using the client object you could use with BlitzGateway(client_obj=client) as conn.

Current session details

# By default, you will have logged into your 'current' group in OMERO. This
# can be changed by switching group in the OMERO.insight or OMERO.web clients.

user = conn.getUser()
print "Current user:"
print "   ID:", user.getId()
print "   Username:", user.getName()
print "   Full Name:", user.getFullName()

# Check if you are an Administrator
print "   Is Admin:", conn.isAdmin()
if not conn.isFullAdmin():
    # If 'Restricted Administrator' show privileges
    print conn.getCurrentAdminPrivileges()

print "Member of:"
for g in conn.getGroupsMemberOf():
    print "   ID:", g.getName(), " Name:", g.getId()
group = conn.getGroupFromContext()
print "Current group: ", group.getName()

# List the group owners and other members
owners, members = group.groupSummary()
print "   Group owners:"
for o in owners:
    print "     ID: %s %s Name: %s" % (
        o.getId(), o.getOmeName(), o.getFullName())
    print "   Group members:"
for m in members:
    print "     ID: %s %s Name: %s" % (
        m.getId(), m.getOmeName(), m.getFullName())

print "Owner of:"
for g in conn.listOwnedGroups():
    print "   ID: ", g.getName(), " Name:", g.getId()

# Added in OMERO 5.0
print "Admins:"
for exp in conn.getAdministrators():
    print "   ID: %s %s Name: %s" % (
        exp.getId(), exp.getOmeName(), exp.getFullName())

# The 'context' of our current session
ctx = conn.getEventContext()
# print ctx     # for more info

Close connection

If you did not use the context manager close the session to free up server resources.

conn.close()

Read data¶

def print_obj(obj, indent=0):
    """
    Helper method to display info about OMERO objects.
    Not all objects will have a "name" or owner field.
    """
    print """%s%s:%s  Name:"%s" (owner=%s)""" % (
        " " * indent,
        obj.OMERO_CLASS,
        obj.getId(),
        obj.getName(),
        obj.getOwnerOmeName())

List all Projects available to me, and their Datasets and Images

# Load first 5 Projects, filtering by default group and owner
my_exp_id = conn.getUser().getId()
default_group_id = conn.getEventContext().groupId
for project in conn.getObjects("Project", opts={'owner': my_exp_id,
                                            'group': default_group_id,
                                            'order_by': 'lower(obj.name)',
                                            'limit': 5, 'offset': 0}):
    print_obj(project)
    # We can get Datasets with listChildren, since we have the Project already.
    # Or conn.getObjects("Dataset", opts={'project', id}) if we have Project ID
    for dataset in project.listChildren():
        print_obj(dataset, 2)
        for image in dataset.listChildren():
            print_obj(image, 4)

Retrieve ‘orphaned’ objects

# We can use the 'orphaned' filter to find Datasets, Images
# or Plates that are not in any parent container
print "\nList orphaned Datasets: \n", "=" * 50
datasets = conn.getObjects("Dataset", opts={'orphaned': True})
for dataset in datasets:
    print_obj(dataset)

Retrieve objects in a container

# We can filter Images by their parent Dataset
# We can also filter Datasets by 'project', Plates by 'screen',
# Wells by 'plate'
print "\nImages in Dataset:", datasetId, "\n", "=" * 50
for image in conn.getObjects('Image', opts={'dataset': datasetId}):
    print_obj(image)

Retrieve an image by Image ID

# Pixels and Channels will be loaded automatically as needed
image = conn.getObject("Image", imageId)
print image.getName(), image.getDescription()
# Retrieve information about an image.
print " X:", image.getSizeX()
print " Y:", image.getSizeY()
print " Z:", image.getSizeZ()
print " C:", image.getSizeC()
print " T:", image.getSizeT()
# List Channels (loads the Rendering settings to get channel colors)
for channel in image.getChannels():
    print 'Channel:', channel.getLabel(),
    print 'Color:', channel.getColor().getRGB()
    print 'Lookup table:', channel.getLut()
    print 'Is reverse intensity?', channel.isReverseIntensity()

# render the first timepoint, mid Z section
z = image.getSizeZ() / 2
t = 0
rendered_image = image.renderImage(z, t)
# rendered_image.show()               # popup (use for debug only)
# rendered_image.save("test.jpg")     # save in the current folder

Get Pixel Sizes for the above Image

size_x = image.getPixelSizeX()       # e.g. 0.132
print " Pixel Size X:", sizeX
# Units support, new in OMERO 5.1.0
size_x_obj = image.getPixelSizeX(units=True)
print " Pixel Size X:", size_x_obj.getValue(), "(%s)" % size_x_obj.getSymbol()
# To get the size with different units, e.g. Angstroms
size_x_ang = image.getPixelSizeX(units="ANGSTROM")
print " Pixel Size X:", size_x_ang.getValue(), "(%s)" % size_x_ang.getSymbol()

Retrieve Screening data

for screen in conn.getObjects("Screen"):
    print_obj(screen)
    for plate in screen.listChildren():
        print_obj(plate, 2)
        plateId = plate.getId()

Retrieve Wells and Images within a Plate

plate = conn.getObject("Plate", plateId)
print "\nNumber of fields:", plate.getNumberOfFields()
print "\nGrid size:", plate.getGridSize()
print "\nWells in Plate:", plate.getName()
for well in plate.listChildren():
    index = well.countWellSample()
    print "  Well: ", well.row, well.column, " Fields:", index
    for index in xrange(0, index):
        print "    Image: ", \
            well.getImage(index).getName(),\
            well.getImage(index).getId()

Groups and permissions¶

We are logged in to our ‘default’ group

group = conn.getGroupFromContext()
print "Current group: ", group.getName()

Each group has defined Permissions set

group_perms = group.getDetails().getPermissions()
perm_string = str(group_perms)
permission_names = {
    'rw----': 'PRIVATE',
    'rwr---': 'READ-ONLY',
    'rwra--': 'READ-ANNOTATE',
    'rwrw--': 'READ-WRITE'}
print "Permissions: %s (%s)" % (permission_names[perm_string], perm_string)

By default, any query applies to ALL data that we can access in our Current group.

This will be determined by group permissions e.g. in Read-Only or Read-Annotate groups, this will include other users’ data - see Groups and permissions system.

projects = conn.listProjects()      # may include other users' data
for p in projects:
    print p.getName(), "Owner: ", p.getDetails().getOwner().getFullName()

# Will return None if Image is not in current group
image = conn.getObject("Image", imageId)
print "Image: ", image

In OMERO-4.4, we added ‘cross-group’ querying, use ‘-1’

conn.SERVICE_OPTS.setOmeroGroup('-1')
image = conn.getObject("Image", imageId)     # Will query across all my groups
print "Image: ", image,
if image is not None:
    print "Group: ", image.getDetails().getGroup().getName(),
    print image.getDetails().getGroup().getId()    # access groupId without loading group

To query only a single group (not necessarily your ‘current’ group)

group_id = image.getDetails().getGroup().getId()
# This is how we 'switch group' in webclient
conn.SERVICE_OPTS.setOmeroGroup(group_id)
projects = conn.listProjects()
image = conn.getObject("Image", imageId)
print "Image: ", image,

Raw data access¶

Retrieve a given plane

# Use the pixelswrapper to retrieve the plane as
# a 2D numpy array see [https://github.com/scipy/scipy]
#
# Numpy array can be used for various analysis routines
#
image = conn.getObject("Image", imageId)
size_z = image.getSizeZ()
size_c = image.getSizeC()
size_t = image.getSizeT()
z, t, c = 0, 0, 0                     # first plane of the image
pixels = image.getPrimaryPixels()
plane = pixels.getPlane(z, c, t)      # get a numpy array.
print "\nPlane at zct: ", z, c, t
print plane
print "shape: ", plane.shape
print "min:", plane.min(), " max:", plane.max(),\
    "pixel type:", plane.dtype.name

Retrieve a given stack

# Get a Z-stack of tiles. Using getTiles or getPlanes (see below) returns
# a generator of data (not all the data in hand) The RawPixelsStore is
# only opened once (not closed after each plane) Alternative is to use
# getPlane() or getTile() multiple times - slightly slower.
c, t = 0, 0                 # First channel and timepoint
tile = (50, 50, 10, 10)     # x, y, width, height of tile

# list of [ (0,0,0,(x,y,w,h)), (1,0,0,(x,y,w,h)), (2,0,0,(x,y,w,h))... ]
zct_list = [(iz, c, t, tile) for iz in range(size_z)]
print "\nZ stack of tiles:"
planes = pixels.getTiles(zct_list)
for i, p in enumerate(planes):
    print "Tile:", zct_list[i], " min:", p.min(),\
        " max:", p.max(), " sum:", p.sum()

Retrieve a given hypercube

zct_list = []
for z in range(size_z / 2, size_z):     # get the top half of the Z-stack
    for c in range(size_c):          # all channels
        for t in range(size_t):      # all time-points
            zct_list.append((z, c, t))
print "\nHyper stack of planes:"
planes = pixels.getPlanes(zct_list)
for i, p in enumerate(planes):
    print "plane zct:", zct_list[i], " min:", p.min(), " max:", p.max()

Retrieve a histogram

# Get a 256 bin histogram for channel 0 and plane z=0/t=0:
hist = image.getHistogram([0], 256, False, 0, 0)
print hist

Write data¶

Create a new Dataset

dataset_obj = omero.model.DatasetI()
dataset_obj.setName(rstring("New Dataset"))
dataset_obj = conn.getUpdateService().saveAndReturnObject(dataset_obj)
dataset_id = dataset_obj.getId().getValue()
print "New dataset, Id:", dataset_id

Link to Project

project = conn.getObject("Project", projectId)
link = omero.model.ProjectDatasetLinkI()
link.setParent(omero.model.ProjectI(project.getId(), False))
link.setChild(dataset_obj)
conn.getUpdateService().saveObject(link)

Annotate Project with a new ‘tag’

tag_ann = omero.gateway.TagAnnotationWrapper(conn)
tag_ann.setValue("New Tag")
tag_ann.save()
project = conn.getObject("Project", projectId)
project.linkAnnotation(tag_ann)

Added in OMERO 5.1: ‘Map’ annotations (list of key: value pairs)

key_value_data = [["Drug Name", "Monastrol"], ["Concentration", "5 mg/ml"]]
map_ann = omero.gateway.MapAnnotationWrapper(conn)
# Use 'client' namespace to allow editing in Insight & web
namespace = omero.constants.metadata.NSCLIENTMAPANNOTATION
map_ann.setNs(namespace)
map_ann.setValue(key_value_data)
map_ann.save()
project = conn.getObject("Project", projectId)
# NB: only link a client map annotation to a single object
project.linkAnnotation(map_ann)

Count the number of annotations on one or many objects

print conn.countAnnotations('Project', [projectId])

List all annotations on an object. Get text from tags

for ann in project.listAnnotations():
    print ann.getId(), ann.OMERO_TYPE,
    print " added by ", ann.link.getDetails().getOwner().getOmeName()
    if ann.OMERO_TYPE == omero.model.TagAnnotationI:
        print "Tag value:", ann.getTextValue()

How to create a file annotation and link to a Dataset

dataset = conn.getObject("Dataset", dataset_id)
# Specify a local file e.g. could be result of some analysis
file_to_upload = "README.txt"   # This file should already exist
with open(file_to_upload, 'w') as f:
    f.write('annotation test')
# create the original file and file annotation (uploads the file etc.)
namespace = "imperial.training.demo"
print "\nCreating an OriginalFile and FileAnnotation"
file_ann = conn.createFileAnnfromLocalFile(
    file_to_upload, mimetype="text/plain", ns=namespace, desc=None)
print "Attaching FileAnnotation to Dataset: ", "File ID:", file_ann.getId(), \
    ",", file_ann.getFile().getName(), "Size:", file_ann.getFile().getSize()
dataset.linkAnnotation(file_ann)     # link it to dataset.

Download a file annotation linked to a Dataset

# make a location to download the file. "download" folder.
path = os.path.join(os.path.dirname(__file__), "download")
if not os.path.exists(path):
    os.makedirs(path)
# Go through all the annotations on the Dataset. Download any file annotations
# we find.
print "\nAnnotations on Dataset:", dataset.getName()
for ann in dataset.listAnnotations():
    if isinstance(ann, omero.gateway.FileAnnotationWrapper):
        print "File ID:", ann.getFile().getId(), ann.getFile().getName(), \
            "Size:", ann.getFile().getSize()
        file_path = os.path.join(path, ann.getFile().getName())

        with open(str(file_path), 'w') as f:
            print "\nDownloading file to", file_path, "..."
            for chunk in ann.getFileInChunks():
                f.write(chunk)
        print "File downloaded!"

Load all the file annotations with a given namespace

ns_to_include = [namespace]
ns_to_exclude = []
metadataService = conn.getMetadataService()
annotations = metadataService.loadSpecifiedAnnotations(
    'omero.model.FileAnnotation', ns_to_include, ns_to_exclude, None)
for ann in annotations:
    print ann.getId().getValue(), ann.getFile().getName().getValue()

Get first annotation with specified namespace

ann = dataset.getAnnotation(namespace)
print "Found Annotation with namespace: ", ann.getNs()

OMERO tables¶

Create a name for the Original File (should be unique)

from random import random
table_name = "TablesDemo:%s" % str(random())
col1 = omero.grid.LongColumn('Uid', 'testLong', [])
col2 = omero.grid.StringColumn('MyStringColumnInit', '', 64, [])
columns = [col1, col2]

Create and initialize a new table.

resources = conn.c.sf.sharedResources()
repository_id = resources.repositories().descriptions[0].getId().getValue()
table = resources.newTable(repository_id, table_name)
table.initialize(columns)

Add data to the table

ids = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
strings = ["one", "two", "three", "four", "five",
           "six", "seven", "eight", "nine", "ten"]
data1 = omero.grid.LongColumn('Uid', 'test Long', ids)
data2 = omero.grid.StringColumn('MyStringColumn', '', 64, strings)
data = [data1, data2]
table.addData(data)
orig_file = table.getOriginalFile()
table.close()           # when we are done, close.

Load the table as an original file

orig_file_id = orig_file.id.val
# ...so you can attach this data to an object e.g. Dataset
file_ann = omero.model.FileAnnotationI()
# use unloaded OriginalFileI
file_ann.setFile(omero.model.OriginalFileI(orig_file_id, False))
file_ann = conn.getUpdateService().saveAndReturnObject(file_ann)
link = omero.model.DatasetAnnotationLinkI()
link.setParent(omero.model.DatasetI(datasetId, False))
link.setChild(omero.model.FileAnnotationI(file_ann.getId().getValue(), False))
conn.getUpdateService().saveAndReturnObject(link)

Table API

ROIs¶

Initialize service

updateService = conn.getUpdateService()

Create ROI

# We are using the core Python API and omero.model objects here, since ROIs
# are not yet supported in the Python Blitz Gateway.
#
# First we load our image and pick some parameters for shapes
x = 50
y = 200
width = 100
height = 50
image = conn.getObject("Image", imageId)
z = image.getSizeZ() / 2
t = 0

# We have a helper function for creating an ROI and linking it to new shapes
def create_roi(img, shapes):
    # create an ROI, link it to Image
    roi = omero.model.RoiI()
    # use the omero.model.ImageI that underlies the 'image' wrapper
    roi.setImage(img._obj)
    for shape in shapes:
        roi.addShape(shape)
    # Save the ROI (saves any linked shapes too)
    return updateService.saveAndReturnObject(roi)

# Another helper for generating the color integers for shapes
def rgba_to_int(red, green, blue, alpha=255):
    """ Return the color as an Integer in RGBA encoding """
    r = red << 24
    g = green << 16
    b = blue << 8
    a = alpha
    rgba_int = r+g+b+a
    if (rgba_int > (2**31-1)):       # convert to signed 32-bit int
        rgba_int = rgba_int - 2**32
    return rgba_int

# create a rectangle shape (added to ROI below)
print ("Adding a rectangle at theZ: %s, theT: %s, X: %s, Y: %s, width: %s,"
   " height: %s" % (z, t, x, y, width, height))
rect = omero.model.RectangleI()
rect.x = rdouble(x)
rect.y = rdouble(y)
rect.width = rdouble(width)
rect.height = rdouble(height)
rect.theZ = rint(z)
rect.theT = rint(t)
rect.textValue = rstring("test-Rectangle")
rect.fillColor = rint(rgba_to_int(255, 255, 255, 255))
rect.strokeColor = rint(rgba_to_int(255, 255, 0, 255))

# create an Ellipse shape (added to ROI below)
ellipse = omero.model.EllipseI()
ellipse.x = rdouble(y)
ellipse.y = rdouble(x)
ellipse.radiusX = rdouble(width)
ellipse.radiusY = rdouble(height)
ellipse.theZ = rint(z)
ellipse.theT = rint(t)
ellipse.textValue = rstring("test-Ellipse")

# Create an ROI containing 2 shapes on same plane
# NB: OMERO.insight client doesn't support display
# of multiple shapes on a single plane.
# Therefore the ellipse is removed later (see below)
create_roi(image, [rect, ellipse])

# create an ROI with single line shape
line = omero.model.LineI()
line.x1 = rdouble(x)
line.x2 = rdouble(x+width)
line.y1 = rdouble(y)
line.y2 = rdouble(y+height)
line.theZ = rint(z)
line.theT = rint(t)
line.textValue = rstring("test-Line")
create_roi(image, [line])

def create_mask(mask_bytes, bytes_per_pixel=1):
    if bytes_per_pixel == 2:
        divider = 16.0
        format_string = "H"  # Unsigned short
        byte_factor = 0.5
    elif bytes_per_pixel == 1:
        divider = 8.0
        format_string = "B"  # Unsigned char
        byte_factor = 1
    else:
        message = "Format %s not supported"
        raise ValueError(message)
    steps = math.ceil(len(mask_bytes) / divider)
    mask = []
    for i in range(long(steps)):
        binary = mask_bytes[
            i * int(divider):i * int(divider) + int(divider)]
        format = str(int(byte_factor * len(binary))) + format_string
        binary = struct.unpack(format, binary)
        s = ""
        for bit in binary:
            s += str(bit)
        mask.append(int(s, 2))
    return bytearray(mask)

mask_x = 50
mask_y = 50
mask_h = 100
mask_w = 100
# Create [0, 1] mask
mask_array = numpy.fromfunction(
    lambda x, y: (x * y) % 2, (mask_w, mask_h))
# Set correct number of bytes per value
mask_array = mask_array.astype(numpy.uint8)
# Convert the mask to bytes
mask_array = mask_array.tostring()
# Pack the bytes to a bit mask
mask_packed = create_mask(mask_array, 1)

# Define mask's fill color
mask_color = ColorHolder()
mask_color.setRed(255)
mask_color.setBlue(0)
mask_color.setGreen(0)
mask_color.setAlpha(100)

# create an ROI with a single mask
mask = omero.model.MaskI()
mask.setTheC(rint(0))
mask.setTheZ(rint(0))
mask.setTheT(rint(0))
mask.setX(rdouble(mask_x))
mask.setY(rdouble(mask_y))
mask.setWidth(rdouble(mask_w))
mask.setHeight(rdouble(mask_h))
mask.setFillColor(rint(mask_color.getInt()))
mask.setTextValue(rstring("test-Mask"))
mask.setBytes(mask_packed)
create_roi(image, [mask])

# create an ROI with single point shape
point = omero.model.PointI()
point.x = rdouble(x)
point.y = rdouble(y)
point.theZ = rint(z)
point.theT = rint(t)
point.textValue = rstring("test-Point")
create_roi(image, [point])

# create an ROI with a single polygon, setting colors and lineWidth
polygon = omero.model.PolygonI()
polygon.theZ = rint(z)
polygon.theT = rint(t)
polygon.fillColor = rint(rgba_to_int(255, 0, 255, 50))
polygon.strokeColor = rint(rgba_to_int(255, 255, 0))
polygon.strokeWidth = omero.model.LengthI(10, UnitsLength.PIXEL)
points = "10,20, 50,150, 200,200, 250,75"
polygon.points = rstring(points)
create_roi(image, [polygon])

Retrieve ROIs linked to an Image

roi_service = conn.getRoiService()
result = roi_service.findByImage(imageId, None)
for roi in result.rois:
    print "ROI:  ID:", roi.getId().getValue()
    for s in roi.copyShapes():
        shape = {}
        shape['id'] = s.getId().getValue()
        shape['theT'] = s.getTheT().getValue()
        shape['theZ'] = s.getTheZ().getValue()
        if s.getTextValue():
            shape['textValue'] = s.getTextValue().getValue()
        if type(s) == omero.model.RectangleI:
            shape['type'] = 'Rectangle'
            shape['x'] = s.getX().getValue()
            shape['y'] = s.getY().getValue()
            shape['width'] = s.getWidth().getValue()
            shape['height'] = s.getHeight().getValue()
        elif type(s) == omero.model.EllipseI:
            shape['type'] = 'Ellipse'
            shape['x'] = s.getX().getValue()
            shape['y'] = s.getY().getValue()
            shape['radiusX'] = s.getRadiusX().getValue()
            shape['radiusY'] = s.getRadiusY().getValue()
        elif type(s) == omero.model.PointI:
            shape['type'] = 'Point'
            shape['x'] = s.getX().getValue()
            shape['y'] = s.getY().getValue()
        elif type(s) == omero.model.LineI:
            shape['type'] = 'Line'
            shape['x1'] = s.getX1().getValue()
            shape['x2'] = s.getX2().getValue()
            shape['y1'] = s.getY1().getValue()
            shape['y2'] = s.getY2().getValue()
        elif type(s) == omero.model.MaskI:
            shape['type'] = 'Mask'
            shape['x'] = s.getX().getValue()
            shape['y'] = s.getY().getValue()
            shape['width'] = s.getWidth().getValue()
            shape['height'] = s.getHeight().getValue()
        elif type(s) in (
                omero.model.LabelI, omero.model.PolygonI):
            print type(s), " Not supported by this code"
        # Do some processing here, or just print:
        print "   Shape:",
        for key, value in shape.items():
            print "  ", key, value,
        print ""

Get Pixel Intensities for ROIs

result = roi_service.findByImage(imageId, None)
shape_ids = []
for roi in result.rois:
    for s in roi.copyShapes():
        shape_ids.append(s.id.val)
ch_index = 0
# Z/T will only be used if a shape doesn't have Z/T set
the_z = 0
the_t = 0
stats = roi_service.getShapeStatsRestricted(shape_ids, the_z, the_t, [ch_index])
for s in stats:
    print "Points", s.pointsCount[ch_index],
    print "Min", s.min[ch_index],
    print "Mean", s.mean[ch_index],
    print "Max", s.max[ch_index],
    print "Sum", s.max[ch_index],
    print "StdDev", s.stdDev[ch_index]

Remove shape from ROI

result = roi_service.findByImage(imageId, None)
for roi in result.rois:
    for s in roi.copyShapes():
        # Find and remove the Shape we added above
        if s.getTextValue() and s.getTextValue().getValue() == "test-Ellipse":
            print "Removing Shape from ROI..."
            roi.removeShape(s)
            roi = updateService.saveAndReturnObject(roi)

Delete data¶

Delete Project

# You can delete a number of objects of the same type at the same
# time. In this case 'Project'. Use deleteChildren=True if you are
# deleting a Project and you want to delete Datasets and Images.
obj_ids = [project_id]
delete_children = False
conn.deleteObjects(
    "Project", obj_ids, deleteAnns=True,
    deleteChildren=delete_children, wait=True)

Retrieve callback and wait until delete completes

# This is not necessary for the Delete to complete. Can be used
# if you want to know when delete is finished or if there were any errors
handle = conn.deleteObjects("Project", [project_id])
cb = omero.callbacks.CmdCallbackI(conn.c, handle)
print "Deleting, please wait."
while not cb.block(500):
    print "."
err = isinstance(cb.getResponse(), omero.cmd.ERR)
print "Error?", err
if err:
    print cb.getResponse()
cb.close(True)      # close handle too

Render Images¶

Get thumbnail

# Thumbnail is created using the current rendering settings on the image
image = conn.getObject("Image", imageId)
img_data = image.getThumbnail()
rendered_thumb = Image.open(StringIO(img_data))
# renderedThumb.show()           # shows a pop-up
rendered_thumb.save("thumbnail.jpg")

Get current settings

print "Channel rendering settings:"
for ch in image.getChannels():
    # if no name, get emission wavelength or index
    print "Name: ", ch.getLabel()
    print "  Color:", ch.getColor().getHtml()
    print "  Active:", ch.isActive()
    print "  Levels:", ch.getWindowStart(), "-", ch.getWindowEnd()
print "isGreyscaleRenderingModel:", image.isGreyscaleRenderingModel()
print "Default Z/T positions:"
print "    Z = %s, T = %s" % (image.getDefaultZ(), image.getDefaultT())

Show the saved rendering settings on this image

print "Rendering Defs on Image:"
for rdef in image.getAllRenderingDefs():
    img_data = image.getThumbnail(rdefId=rdef['id'])
    print "   ID: %s (owner: %s %s)" % (
        rdef['id'], rdef['owner']['firstName'], rdef['owner']['lastName'])

Render each channel as a separate grayscale image

image.setGreyscaleRenderingModel()
size_c = image.getSizeC()
z = image.getSizeZ() / 2
t = 0
for c in range(1, size_c + 1):       # Channel index starts at 1
    channels = [c]                  # Turn on a single channel at a time
    image.setActiveChannels(channels)
    rendered_image = image.renderImage(z, t)
    # renderedImage.show()                        # popup (use for debug only)
    rendered_image.save("channel%s.jpg" % c)     # save in the current folder

Turn 3 channels on, setting their colors

image.setColorRenderingModel()
channels = [1, 2, 3]
color_list = ['F00', None, 'FFFF00']  # do not change color of 2nd channel
image.setActiveChannels(channels, colors=color_list)
# max intensity projection 'intmean' for mean-intensity
image.setProjection('intmax')
rendered_image = image.renderImage(z, t)  # z and t are ignored for projections
# renderedImage.show()
rendered_image.save("all_channels.jpg")
image.setProjection('normal')               # turn off projection

Turn 2 channels on, setting levels of the first one

channels = [1, 2]
range_list = [[100.0, 120.2], [None, None]]
image.setActiveChannels(channels, windows=range_list)
# Set default Z and T. These will be used as defaults for further rendering
image.setDefaultZ(0)
image.setDefaultT(0)
# default compression is 0.9
rendered_image = image.renderImage(z=None, t=None, compression=0.5)
rendered_image.show()
rendered_image.save("two_channels.jpg")

Save the current rendering settings & default Z/T

image.saveDefaults()

Reset to settings at import time, and optionally save

image.resetDefaults(save=True)

Create Image¶

Create an image from scratch

# This example demonstrates the usage of the convenience method
# createImageFromNumpySeq() Here we create a multi-dimensional image from a
# hard-coded array of data.
from numpy import array, int8
import omero
size_x, size_y, size_z, size_c, size_t = 5, 4, 1, 2, 1
plane1 = array(
    [[0, 1, 2, 3, 4], [5, 6, 7, 8, 9], [0, 1, 2, 3, 4], [5, 6, 7, 8, 9]],
    dtype=int8)
plane2 = array(
    [[5, 6, 7, 8, 9], [0, 1, 2, 3, 4], [5, 6, 7, 8, 9], [0, 1, 2, 3, 4]],
    dtype=int8)
planes = [plane1, plane2]

def plane_gen():
    """generator will yield planes"""
    for p in planes:
        yield p

desc = "Image created from a hard-coded arrays"
i = conn.createImageFromNumpySeq(
    plane_gen(), "numpy image", size_z, size_c, size_t, description=desc,
    dataset=None)
print 'Created new Image:%s Name:"%s"' % (i.getId(), i.getName())

Set the pixel size using units (added in 5.1.0)

Lengths are specified by value and a unit enumeration Here we set the pixel size X and Y to be 9.8 Angstroms

from omero.model.enums import UnitsLength
# Re-load the image to avoid update conflicts
i = conn.getObject("Image", i.getId())
u = omero.model.LengthI(9.8, UnitsLength.ANGSTROM)
p = i.getPrimaryPixels()._obj
p.setPhysicalSizeX(u)
p.setPhysicalSizeY(u)
conn.getUpdateService().saveObject(p)

Create an Image from an existing image

# We are going to create a new image by passing the method a 'generator' of 2D
# planes This will come from an existing image, by taking the average of 2
# channels.
zct_list = []
image = conn.getObject('Image', imageId)
size_z, size_c, size_t = image.getSizeZ(), image.getSizeC(), image.getSizeT()
dataset = image.getParent()
pixels = image.getPrimaryPixels()
new_size_c = 1

def plane_gen():
    """
    set up a generator of 2D numpy arrays.

    The createImage method below expects planes in the order specified here
    (for z.. for c.. for t..)
    """
    for z in range(size_z):              # all Z sections
        # Illustrative purposes only, since we only have 1 channel
        for c in range(new_size_c):
            for t in range(size_t):      # all time-points
                channel0 = pixels.getPlane(z, 0, t)
                channel1 = pixels.getPlane(z, 1, t)
                # Here we can manipulate the data in many different ways. As
                # an example we are doing "average"
                # average of 2 channels
                new_plane = (channel0 + channel1) / 2
                print "newPlane for z,t:", z, t, new_plane.dtype, \
                    new_plane.min(), new_plane.max()
                yield new_plane

desc = ("Image created from Image ID: %s by averaging Channel 1 and Channel 2"
    % imageId)
i = conn.createImageFromNumpySeq(
    plane_gen(), "new image", size_z, new_size_c, size_t, description=desc,
    dataset=dataset)

Filesets - added in OMERO 5.0¶

Get the ‘Fileset’ for an Image

# A Fileset is a collection of the original files imported to
# create an image or set of images in OMERO.
image = conn.getObject("Image", imageId)
fileset = image.getFileset()       # will be None for pre-FS images
fs_id = fileset.getId()
# List all images that are in this fileset
for fs_image in fileset.copyImages():
    print fs_image.getId(), fs_image.getName()
# List original imported files
for orig_file in fileset.listFiles():
    name = orig_file.getName()
    path = orig_file.getPath()
    print path, name

Get Original Imported Files directly from the image

# this will include pre-FS data IF images were archived on import
print image.countImportedImageFiles()
# specifically count Fileset files
file_count = image.countFilesetFiles()
# list files
if file_count > 0:
    for orig_file in image.getImportedImageFiles():
        name = orig_file.getName()
        path = orig_file.getPath()
        print path, name

Can get the Fileset using conn.getObject()

fileset = conn.getObject("Fileset", fs_id)

Python OMERO.scripts¶

It is relatively straightforward to take the code samples above and re-use them in OMERO.scripts. This allows the code to be run on the OMERO server and called from either the OMERO.insight client or OMERO.web by any users of the server. See OMERO.scripts user guide.