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Note

This documentation is for OMERO 5.2. This version is now in maintenance mode and will only be updated in the event of critical bugs or security concerns. OMERO 5.3 is expected in the first quarter of 2017.

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-5.2.8-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. 5.2.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

# Connect to the Python Blitz Gateway
# =============================================================
# Make a simple connection to OMERO, printing details of the
# connection. See OmeroPy/Gateway for more info
conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
connected = conn.connect()
# Check if you are connected.
# =============================================================
if not connected:
    import sys
    sys.stderr.write(
        "Error: Connection not available, please check your user name and"
        " password.\n")
    sys.exit(1)
# Using secure connection.
# =============================================================
# By default, once we have logged in, data transfer is not encrypted
# (faster)
# To use a secure connection, call setSecure(True):
# conn.setSecure(True)         # <--------- Uncomment this
# 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()
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:
# =================================================================
# When you are done, close the session to free up server resources.
conn._closeSession()

Read data

  • Create a connection
conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()
  • Configuration
imageId = 1
datasetId = 2
plateId = -1        # Don't need to set this
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:
# The only_owned=True parameter limits the Projects which are returned.
# If the parameter is omitted or the value is False, then all Projects
# visible in the current group are returned.
print "\nList Projects:"
print "=" * 50
my_expId = conn.getUser().getId()
for project in conn.listProjects(my_expId):
    print_obj(project)
    for dataset in project.listChildren():
        print_obj(dataset, 2)
        for image in dataset.listChildren():
            print_obj(image, 4)
  • Retrieve the datasets owned by the user currently logged in:
# Here we create an omero.sys.ParametersI instance which we
# can use to filter the results that are returned. If we did
# not pass the params argument to getObjects, then all Datasets
# in the current group would be returned.
print "\nList Datasets:"
print "=" * 50
params = omero.sys.ParametersI()
params.exp(conn.getUser().getId())  # only show current user's Datasets
datasets = conn.getObjects("Dataset", params=params)
for dataset in datasets:
    print_obj(dataset)
  • Retrieve the images contained in a dataset:
print "\nDataset:%s" % datasetId
print "=" * 50
dataset = conn.getObject("Dataset", datasetId)
print "\nImages in Dataset:", dataset.getName()
for image in dataset.listChildren():
    print_obj(image)
  • Retrieve an image by Image ID:
image = conn.getObject("Image", imageId)
print "\nImage:%s" % imageId
print "=" * 50
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()
# render the first timepoint, mid Z section
z = image.getSizeZ() / 2
t = 0
renderedImage = image.renderImage(z, t)
# renderedImage.show()               # popup (use for debug only)
# renderedImage.save("test.jpg")     # save in the current folder
  • Get Pixel Sizes for the above Image:
sizeX = image.getPixelSizeX()       # E.g. 0.132
print " Pixel Size X:", sizeX
# Units support, new in OMERO 5.1.0
sizeXobj = image.getPixelSizeX(units=True)
print " Pixel Size X:", sizeXobj.getValue(), "(%s)" % sizeXobj.getSymbol()
# To get the size with different units, E.g. Angstroms
sizeXang = image.getPixelSizeX(units="ANGSTROM")
print " Pixel Size X:", sizeXang.getValue(), "(%s)" % sizeXang.getSymbol()
  • Retrieve Screening data:
print "\nList Screens:"
print "=" * 50
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:
if plateId >= 0:
    print "\nPlate:%s" % plateId
    print "=" * 50
    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()
  • Close connection:
# When you are done, close the session to free up server resources.
conn._closeSession()

Groups and permissions

  • Create a connection
conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()
  • Configuration
imageId = 1
  • 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'}  # Not exposed in clients
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.details.group.id.val    # access groupId without loading group
  • To query only a single group (not necessarily your ‘current’ group)
groupId = image.details.group.id.val
# This is how we 'switch group' in webclient
conn.SERVICE_OPTS.setOmeroGroup(groupId)
projects = conn.listProjects()
image = conn.getObject("Image", imageId)
print "Image: ", image,
  • Close connection:
# When you are done, close the session to free up server resources.
conn._closeSession()

Raw data access

  • Create a connection
conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()
  • Configuration
imageId = 27544
  • Retrieve a given plane
# Use the pixelswrapper to retrieve the plane as
# a 2D numpy array. See [http://www.scipy.org/Tentative_NumPy_Tutorial]
#
# Numpy array can be used for various analysis routines
#
image = conn.getObject("Image", imageId)
sizeZ = image.getSizeZ()
sizeC = image.getSizeC()
sizeT = 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))... ]
zctList = [(iz, c, t, tile) for iz in range(sizeZ)]
print "\nZ stack of tiles:"
planes = pixels.getTiles(zctList)
for i, p in enumerate(planes):
    print "Tile:", zctList[i], " min:", p.min(),\
        " max:", p.max(), " sum:", p.sum()
  • Retrieve a given hypercube
zctList = []
for z in range(sizeZ / 2, sizeZ):     # get the top half of the Z-stack
    for c in range(sizeC):          # all channels
        for t in range(sizeT):      # all time-points
            zctList.append((z, c, t))
print "\nHyper stack of planes:"
planes = pixels.getPlanes(zctList)
for i, p in enumerate(planes):
    print "plane zct:", zctList[i], " min:", p.min(), " max:", p.max()
  • Close connection:
# When you are done, close the session to free up server resources.
conn._closeSession()

Write data

  • Create a connection
conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()
  • Configuration
projectId = 2
# Specify a local file. E.g. could be result of some analysis
fileToUpload = "README.txt"   # This file should already exist
  • Create a new Dataset
datasetObj = omero.model.DatasetI()
datasetObj.setName(rstring("New Dataset"))
datasetObj = conn.getUpdateService().saveAndReturnObject(datasetObj)
datasetId = datasetObj.getId().getValue()
print "New dataset, Id:", datasetId
  • Link to Project
project = conn.getObject("Project", projectId)
if project is None:
    import sys
    sys.stderr.write("Error: Object does not exist.\n")
    sys.exit(1)
link = omero.model.ProjectDatasetLinkI()
link.setParent(omero.model.ProjectI(project.getId(), False))
link.setChild(datasetObj)
conn.getUpdateService().saveObject(link)
  • Annotate Project with a new ‘tag’
tagAnn = omero.gateway.TagAnnotationWrapper(conn)
tagAnn.setValue("New Tag")
tagAnn.save()
project = conn.getObject("Project", projectId)
project.linkAnnotation(tagAnn)
  • Added in OMERO 5.1: ‘Map’ annotations (list of key: value pairs)
keyValueData = [["Drug Name", "Monastrol"],
                ["Concentration", "5 mg/ml"]]
mapAnn = omero.gateway.MapAnnotationWrapper(conn)
# Use 'client' namespace to allow editing in Insight & web
namespace = omero.constants.metadata.NSCLIENTMAPANNOTATION
mapAnn.setNs(namespace)
mapAnn.setValue(keyValueData)
mapAnn.save()
project = conn.getObject("Project", projectId)
# NB: only link a client map annotation to a single object
project.linkAnnotation(mapAnn)
  • How to create a file annotation and link to a Dataset
dataset = conn.getObject("Dataset", datasetId)
# create the original file and file annotation (uploads the file etc.)
namespace = "imperial.training.demo"
print "\nCreating an OriginalFile and FileAnnotation"
fileAnn = conn.createFileAnnfromLocalFile(
    fileToUpload, mimetype="text/plain", ns=namespace, desc=None)
print "Attaching FileAnnotation to Dataset: ", "File ID:", fileAnn.getId(), \
    ",", fileAnn.getFile().getName(), "Size:", fileAnn.getFile().getSize()
dataset.linkAnnotation(fileAnn)     # 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())
f = open(str(file_path), 'w')
print "\nDownloading file to", file_path, "..."
try:
    for chunk in ann.getFileInChunks():
        f.write(chunk)
finally:
    f.close()
    print "File downloaded!"
  • Load all the file annotations with a given namespace
nsToInclude = [namespace]
nsToExclude = []
metadataService = conn.getMetadataService()
annotations = metadataService.loadSpecifiedAnnotations(
    'omero.model.FileAnnotation', nsToInclude, nsToExclude, None)
for ann in annotations:
    print ann.getId().getValue(), ann.file.name.val
  • Get first annotation with specified namespace
ann = dataset.getAnnotation(namespace)
print "Found Annotation with namespace: ", ann.getNs()
  • Close connection:
# When you are done, close the session to free up server resources.
conn._closeSession()

OMERO tables

  • Create a connection
conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()
  • Configuration
datasetId = 33
  • Create a name for the Original File (should be unique)
from random import random
tablename = "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.
repositoryId = 1
table = conn.c.sf.sharedResources().newTable(repositoryId, tablename)
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)
table.close()           # when we are done, close.
  • Get the table as an original file...
orig_file = table.getOriginalFile()
orig_file_id = orig_file.id.val
# ...so you can attach this data to an object. E.g. Dataset
fileAnn = omero.model.FileAnnotationI()
# use unloaded OriginalFileI
fileAnn.setFile(omero.model.OriginalFileI(orig_file_id, False))
fileAnn = conn.getUpdateService().saveAndReturnObject(fileAnn)
link = omero.model.DatasetAnnotationLinkI()
link.setParent(omero.model.DatasetI(datasetId, False))
link.setChild(omero.model.FileAnnotationI(fileAnn.id.val, False))
conn.getUpdateService().saveAndReturnObject(link)
  • Table API

See also

 OMERO Tables

openTable = conn.c.sf.sharedResources().openTable(orig_file)
print "Table Columns:"
for col in openTable.getHeaders():
    print "   ", col.name
rowCount = openTable.getNumberOfRows()
print "Row count:", rowCount
  • Get data from every column of the specified rows
rowNumbers = [3, 5, 7]
print "\nGet All Data for rows: ", rowNumbers
data = openTable.readCoordinates(range(rowCount))
for col in data.columns:
    print "Data for Column: ", col.name
    for v in col.values:
        print "   ", v
  • Get data from specified columns of specified rows
colNumbers = [1]
start = 3
stop = 7
print "\nGet Data for cols: ", colNumbers,\
    " and between rows: ", start, "-", stop
data = openTable.read(colNumbers, start, stop)
for col in data.columns:
    print "Data for Column: ", col.name
    for v in col.values:
        print "   ", v
  • Query the table for rows where the ‘Uid’ is in a particular range
queryRows = openTable.getWhereList(
    "(Uid > 2) & (Uid <= 8)", variables={}, start=0, stop=rowCount, step=0)
data = openTable.readCoordinates(queryRows)
for col in data.columns:
    print "Query Results for Column: ", col.name
    for v in col.values:
        print "   ", v
openTable.close()           # we're done
  • In future, to get the table back from Original File
orig_table_file = conn.getObject(
    "OriginalFile", attributes={'name': tablename})    # if name is unique
savedTable = conn.c.sf.sharedResources().openTable(orig_table_file._obj)
print "Opened table with row-count:", savedTable.getNumberOfRows()
  • Close connection:
# When you are done, close the session to free up server resources.
conn._closeSession()

ROIs

  • Create a connection
conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()
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)
theZ = image.getSizeZ() / 2
theT = 0
# We have a helper function for creating an ROI and linking it to new shapes
def createROI(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)
    updateService.saveObject(roi)
# Another helper for generating the color integers for shapes
def rgbaToInt(red, green, blue, alpha=255):
    """ Convert an R,G,B,A value to an int """
    RGBAInt = (alpha << 24) + (red << 16) + (green << 8) + blue
    if (RGBAInt > (2**31-1)):       # convert to signed 32-bit int
        RGBAInt = RGBAInt - 2**32
    return int(RGBAInt)
# 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" % (theZ, theT, 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(theZ)
rect.theT = rint(theT)
rect.textValue = rstring("test-Rectangle")
# create an Ellipse shape (added to ROI below)
ellipse = omero.model.EllipseI()
ellipse.cx = rdouble(y)
ellipse.cy = rdouble(x)
ellipse.rx = rdouble(width)
ellipse.ry = rdouble(height)
ellipse.theZ = rint(theZ)
ellipse.theT = rint(theT)
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)
createROI(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(theZ)
line.theT = rint(theT)
line.textValue = rstring("test-Line")
createROI(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"  # Unsiged 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)
createROI(image, [mask])
# create an ROI with single point shape
point = omero.model.PointI()
point.cx = rdouble(x)
point.cy = rdouble(y)
point.theZ = rint(theZ)
point.theT = rint(theT)
point.textValue = rstring("test-Point")
createROI(image, [point])
def pointsToString(points):
    """ Returns legacy format supported by Insight """
    points = ["%s,%s" % (p[0], p[1]) for p in points]
    csv = ", ".join(points)
    return "points[%s] points1[%s] points2[%s]" % (csv, csv, csv)
# create an ROI with a single polygon, setting colors and lineWidth
polygon = omero.model.PolygonI()
polygon.theZ = rint(theZ)
polygon.theT = rint(theT)
polygon.fillColor = rint(rgbaToInt(255, 0, 255, 50))
polygon.strokeColor = rint(rgbaToInt(255, 255, 0))
polygon.strokeWidth = omero.model.LengthI(10, UnitsLength.PIXEL)
points = [[10, 20], [50, 150], [200, 200], [250, 75]]
polygon.points = rstring(pointsToString(points))
createROI(image, [polygon])
  • Retrieve ROIs linked to an Image.
roiService = conn.getRoiService()
result = roiService.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['cx'] = s.getCx().getValue()
            shape['cy'] = s.getCy().getValue()
            shape['rx'] = s.getRx().getValue()
            shape['ry'] = s.getRy().getValue()
        elif type(s) == omero.model.PointI:
            shape['type'] = 'Point'
            shape['cx'] = s.getCx().getValue()
            shape['cy'] = s.getCy().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 ""
  • Remove shape from ROI
result = roiService.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)
  • Close connection:
# When you are done, close the session to free up server resources.
conn._closeSession()

Delete data

  • Create a connection
conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()
  • Configuration
projectId = 507        # NB: This will be deleted!
  • Load the Project
project = conn.getObject("Project", projectId)
if project is None:
    import sys
    sys.stderr.write("Error: Object does not exist.\n")
    sys.exit(1)
print "\nProject:", project.getName()
  • 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 = [projectId]
deleteChildren = False
handle = conn.deleteObjects(
    "Project", obj_ids, deleteAnns=True, deleteChildren=deleteChildren)
  • 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
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
  • Close connection:
# When you are done, close the session to free up server resources.
conn._closeSession()

Render Images

  • Create a connection
conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()
  • Configuration
imageId = 27544
  • Get thumbnail
# Thumbnail is created using the current rendering settings on the image
image = conn.getObject("Image", imageId)
img_data = image.getThumbnail()
renderedThumb = Image.open(StringIO(img_data))
# renderedThumb.show()           # shows a pop-up
renderedThumb.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 greyscale image
image.setGreyscaleRenderingModel()
sizeC = image.getSizeC()
z = image.getSizeZ() / 2
t = 0
for c in range(1, sizeC + 1):       # Channel index starts at 1
    channels = [c]                  # Turn on a single channel at a time
    image.setActiveChannels(channels)
    renderedImage = image.renderImage(z, t)
    # renderedImage.show()                        # popup (use for debug only)
    renderedImage.save("channel%s.jpg" % c)     # save in the current folder
  • Turn 3 channels on, setting their colors
image.setColorRenderingModel()
channels = [1, 2, 3]
colorList = ['F00', None, 'FFFF00']  # do not change color of 2nd channel
image.setActiveChannels(channels, colors=colorList)
# max intensity projection 'intmean' for mean-intensity
image.setProjection('intmax')
renderedImage = image.renderImage(z, t)  # z and t are ignored for projections
# renderedImage.show()
renderedImage.save("all_channels.jpg")
image.setProjection('normal')               # turn off projection
  • Turn 2 channels on, setting levels of the first one
channels = [1, 2]
rangeList = [[100.0, 120.2], [None, None]]
image.setActiveChannels(channels, windows=rangeList)
# Set default Z & T. These will be used as defaults for further rendering
image.setDefaultZ(0)
image.setDefaultT(0)
# default compression is 0.9
renderedImage = image.renderImage(z=None, t=None, compression=0.5)
renderedImage.show()
renderedImage.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)
  • Close connection:
# When you are done, close the session to free up server resources.
conn._closeSession()

Create Image

  • Create a connection
conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()
  • Configuration
imageId = 27544     # This image must have at least 2 channels
  • 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
sizeX, sizeY, sizeZ, sizeC, sizeT = 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 planeGen():
    """generator will yield planes"""
    for p in planes:
        yield p
desc = "Image created from a hard-coded arrays"
i = conn.createImageFromNumpySeq(
    planeGen(), "numpy image", sizeZ, sizeC, sizeT, 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.
zctList = []
image = conn.getObject('Image', imageId)
sizeZ, sizeC, sizeT = image.getSizeZ(), image.getSizeC(), image.getSizeT()
dataset = image.getParent()
pixels = image.getPrimaryPixels()
newSizeC = 1
def planeGen():
    """
    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(sizeZ):              # all Z sections
    # Illustrative purposes only, since we only have 1 channel
    for c in range(newSizeC):
        for t in range(sizeT):      # 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
            newPlane = (channel0 + channel1) / 2
            print "newPlane for z,t:", z, t, newPlane.dtype, \
                newPlane.min(), newPlane.max()
            yield newPlane
desc = ("Image created from Image ID: %s by averaging Channel 1 and Channel 2"
        % imageId)
i = conn.createImageFromNumpySeq(
    planeGen(), "new image", sizeZ, newSizeC, sizeT, description=desc,
    dataset=dataset)
  • Close connection:
# When you are done, close the session to free up server resources.
conn._closeSession()

Filesets - added in OMERO 5.0

  • Create a connection
conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()
  • Configuration
imageId = 101
  • 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
fsId = fileset.getId()
# List all images that are in this fileset
for fsImage in fileset.copyImages():
    print fsImage.getId(), fsImage.getName()
# List original imported files
for origFile in fileset.listFiles():
    name = origFile.getName()
    path = origFile.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
fileCount = image.countFilesetFiles()
# list files
if fileCount > 0:
    for origFile in image.getImportedImageFiles():
        name = origFile.getName()
        path = origFile.getPath()
        print path, name
  • Can get the Fileset using conn.getObject()
fileset = conn.getObject("Fileset", fsId)
  • Close connection:
# When you are done, close the session to free up server resources.
conn._closeSession()

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.