def point():
o = PointI()
populate_shape(o)
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
o.id = rlong(3L)
return o
def point():
o = PointI()
populate_shape(o)
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
o.id = rlong(3L)
return o
def _parse_mnu_roi(self, columns):
"""Parses out ROI from OmeroTables columns for 'MNU' datasets."""
log.debug("Parsing %s MNU ROIs..." % (len(columns[0].values)))
image_ids = columns[self.IMAGE_COL].values
rois = list()
# Save our file annotation to the database so we can use an unloaded
# annotation for the saveAndReturnIds that will be triggered below.
self.file_annotation = self.update_service.saveAndReturnObject(self.file_annotation)
unloaded_file_annotation = FileAnnotationI(self.file_annotation.id.val, False)
batch_no = 1
batches = dict()
for i, image_id in enumerate(image_ids):
unloaded_image = ImageI(image_id, False)
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
values = columns[3].values
shape.cx = rdouble(float(values[i]))
values = columns[2].values
shape.cy = rdouble(float(values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
if len(rois) == self.ROI_UPDATE_LIMIT:
self.thread_pool.add_task(self.update_rois, rois, batches, batch_no)
rois = list()
batch_no += 1
self.thread_pool.add_task(self.update_rois, rois, batches, batch_no)
self.thread_pool.wait_completion()
batch_keys = batches.keys()
batch_keys.sort()
for k in batch_keys:
columns[self.ROI_COL].values += batches[k]
def to_rois(cx_column, cy_column, pixels):
unloaded_image = ImageI(pixels.image.id, False)
rois = list()
for index in range(len(cx_column.values)):
cx = rdouble(cx_column.values[index])
cy = rdouble(cy_column.values[index])
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
shape.cx = cx
shape.cy = cy
roi.addShape(shape)
roi.image = unloaded_image
rois.append(roi)
return rois
def create_omero_point(data, image):
point = PointI()
point.x = rdouble(get_x(data))
point.y = rdouble(get_y(data))
point.theZ = rint(get_z(data, image))
point.theT = rint(get_t(data, image))
point.textValue = rstring("point-from-napari")
return point
def shapes(self):
"""Create a bunch of unsaved Shapes."""
rect = RectangleI()
rect.x = rdouble(10)
rect.y = rdouble(20)
rect.width = rdouble(30)
rect.height = rdouble(40)
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))
ellipse = EllipseI()
ellipse.x = rdouble(33)
ellipse.y = rdouble(44)
ellipse.radiusX = rdouble(55)
ellipse.radiusY = rdouble(66)
ellipse.textValue = rstring("test-Ellipse")
line = LineI()
line.x1 = rdouble(20)
line.x2 = rdouble(30)
line.y1 = rdouble(40)
line.y2 = rdouble(50)
line.textValue = rstring("test-Line")
point = PointI()
point.x = rdouble(50)
point.y = rdouble(50)
point.textValue = rstring("test-Point")
polygon = PolygonI()
polygon.fillColor = rint(rgba_to_int(255, 0, 255, 50))
polygon.strokeColor = rint(rgba_to_int(255, 255, 0))
polygon.strokeWidth = LengthI(10, UnitsLength.PIXEL)
points = "10,20, 50,150, 100,100, 150,75"
polygon.points = rstring(points)
polyline = PolylineI()
polyline.points = rstring(points)
return [rect, ellipse, line, point, polygon, polyline]
def shapes(self):
"""Create a bunch of unsaved Shapes."""
rect = RectangleI()
rect.x = rdouble(10)
rect.y = rdouble(20)
rect.width = rdouble(30)
rect.height = rdouble(40)
# Only save theT, not theZ
rect.theT = rint(0)
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))
# ellipse without saving theZ & theT
ellipse = EllipseI()
ellipse.x = rdouble(33)
ellipse.y = rdouble(44)
ellipse.radiusX = rdouble(55)
ellipse.radiusY = rdouble(66)
ellipse.textValue = rstring("test-Ellipse")
line = LineI()
line.x1 = rdouble(200)
line.x2 = rdouble(300)
line.y1 = rdouble(400)
line.y2 = rdouble(500)
line.textValue = rstring("test-Line")
point = PointI()
point.x = rdouble(1)
point.y = rdouble(1)
point.theZ = rint(1)
point.theT = rint(1)
point.textValue = rstring("test-Point")
polygon = PolygonI()
polygon.theZ = rint(5)
polygon.theT = rint(5)
polygon.fillColor = rint(rgba_to_int(255, 0, 255, 50))
polygon.strokeColor = rint(rgba_to_int(255, 255, 0))
polygon.strokeWidth = LengthI(10, UnitsLength.PIXEL)
points = "10,20, 50,150, 200,200, 250,75"
polygon.points = rstring(points)
mask = MaskI()
mask.setTheC(rint(0))
mask.setTheZ(rint(0))
mask.setTheT(rint(0))
mask.setX(rdouble(100))
mask.setY(rdouble(100))
mask.setWidth(rdouble(500))
mask.setHeight(rdouble(500))
mask.setTextValue(rstring("test-Mask"))
mask.setBytes(None)
return [rect, ellipse, line, point, polygon, mask]
def point(identity_transform):
o = PointI()
populate_shape(o, identity_transform)
if SCHEMA_VERSION == '2015-01':
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
else:
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.id = rlong(3)
return o
def point():
o = PointI()
populate_shape(o)
if SCHEMA_VERSION == '2015-01':
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
else:
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.id = rlong(3L)
return o
def parse(self):
provider = self.original_file_provider
data = provider.get_original_file_data(self.original_file)
try:
rows = list(csv.reader(data, delimiter=","))
finally:
data.close()
columns = [
ImageColumn("Image", "", list()),
RoiColumn("ROI", "", list()),
StringColumn("Type", "", 12, list()),
]
for row in rows[1:]:
wellnumber = self.well_name_to_number(row[0])
image = self.analysis_ctx.\
image_from_wellnumber(wellnumber)
# TODO: what to do with the field?!
# field = int(row[1])
# image = images[field]
roi = RoiI()
shape = PointI()
shape.cx = rdouble(float(row[2]))
shape.cy = rdouble(float(row[3]))
shape.textValue = rstring(row[4])
roi.addShape(shape)
roi.image = image.proxy()
rid = self.update_service\
.saveAndReturnIds([roi])[0]
columns[0].values.append(image.id.val)
columns[1].values.append(rid)
columns[2].values.append(row[4])
return MeasurementParsingResult([columns])
def parse(self):
provider = self.original_file_provider
data = provider.get_original_file_data(self.original_file)
try:
rows = list(csv.reader(data, delimiter=","))
finally:
data.close()
columns = [
ImageColumn("Image", "", list()),
RoiColumn("ROI", "", list()),
StringColumn("Type", "", 12, list()),
]
for row in rows[1:]:
wellnumber = self.well_name_to_number(row[0])
image = self.analysis_ctx.\
image_from_wellnumber(wellnumber)
# TODO: what to do with the field?!
# field = int(row[1])
# image = images[field]
roi = RoiI()
shape = PointI()
shape.cx = rdouble(float(row[2]))
shape.cy = rdouble(float(row[3]))
shape.textValue = rstring(row[4])
roi.addShape(shape)
roi.image = image.proxy()
rid = self.update_service\
.saveAndReturnIds([roi])[0]
columns[0].values.append(image.id.val)
columns[1].values.append(rid)
columns[2].values.append(row[4])
return MeasurementParsingResult([columns])
def point():
o = PointI()
populate_shape(o)
if SCHEMA_VERSION == "2015-01":
o.cx = rdouble(1.0)
o.cy = rdouble(2.0)
else:
o.x = rdouble(1.0)
o.y = rdouble(2.0)
o.id = rlong(3L)
return o
def create_points(conn, df, image):
columns = [
"Sequence", "Tagged Protein", "Sequence is unique", "Location_X",
"Location_Y"
]
df2 = pandas.DataFrame(columns=(['Roi'] + columns))
index = df['Source Name'] == image.getName()
for (s, tp, u, x, y) in zip(*map(lambda x: df[index][x], columns)):
p = PointI()
p.x = rdouble(float(x))
p.y = rdouble(float(y))
p.setTextValue(rstring(tp))
roi = RoiI()
roi.addShape(p)
roi.setName(rstring(tp))
roi.setImage(ImageI(image.getId(), False))
roi = conn.getUpdateService().saveAndReturnObject(roi)
df2.loc[len(df2)] = (roi.getId().getValue(), s, tp, u, x, y)
return df2
def main(conn, argv):
parser = argparse.ArgumentParser()
parser.add_argument("image", help="Image ID")
args = parser.parse_args(argv)
image_id = args.image
data = swc.read(
"20200628-ftp/RL_35_guassian_4_4_80.tif_x94_y327_z241_app2_(GSBT).swc"
).data_block
# img_name = 'FADU_tumour_Lectin_substack_deconvolved_RL_35iters_guassian_psf_4_4_80.tif'
image = conn.getObject("Image", image_id)
# delete existing ROIs
roi_service = conn.getRoiService()
result = roi_service.findByImage(image.id, None)
roi_ids = [roi.id.val for roi in result.rois]
if roi_ids:
print("Deleting ROIs...")
conn.deleteObjects("Roi", roi_ids, wait=True)
size_y = image.getSizeY()
paths = parse_swc(data, size_y)
red_int = int.from_bytes([255, 0, 0, 255], byteorder="big", signed=True)
for count, path in enumerate(paths):
points = []
for zyx in path:
z, y, x = zyx
point = PointI()
point.x = rdouble(x)
point.y = rdouble(y)
point.theZ = rint(round(z))
point.strokeColor = rint(red_int)
points.append(point)
print(f"{count}/{len(paths)} Creating ROI with {len(points)} points")
create_roi(image, points)
def _parse_mnu_roi(self, columns):
"""Parses out ROI from OmeroTables columns for 'MNU' datasets."""
log.debug("Parsing %s MNU ROIs..." % (len(columns[0].values)))
image_ids = columns[self.IMAGE_COL].values
rois = list()
# Save our file annotation to the database so we can use an unloaded
# annotation for the saveAndReturnIds that will be triggered below.
self.file_annotation = \
self.update_service.saveAndReturnObject(self.file_annotation)
unloaded_file_annotation = \
FileAnnotationI(self.file_annotation.id.val, False)
batch_no = 1
batches = dict()
for i, image_id in enumerate(image_ids):
unloaded_image = ImageI(image_id, False)
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
values = columns[3].values
shape.cx = rdouble(float(values[i]))
values = columns[2].values
shape.cy = rdouble(float(values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
if len(rois) == self.ROI_UPDATE_LIMIT:
self.thread_pool.add_task(
self.update_rois, rois, batches, batch_no)
rois = list()
batch_no += 1
self.thread_pool.add_task(self.update_rois, rois, batches, batch_no)
self.thread_pool.wait_completion()
batch_keys = batches.keys()
batch_keys.sort()
for k in batch_keys:
columns[self.ROI_COL].values += batches[k]
def parse_and_populate_roi(self, columns_as_list):
# First sanity check our provided columns
names = [column.name for column in columns_as_list]
log.debug('Parsing columns: %r' % names)
cells_expected = [name in names for name in self.CELLS_CG_EXPECTED]
nuclei_expected = [name in names for name in self.NUCLEI_CG_EXPECTED]
if (False in cells_expected) and (False in nuclei_expected):
log.warn("Missing CGs for InCell dataset: %r" % names)
log.warn('Removing resultant empty ROI column.')
for column in columns_as_list:
if RoiColumn == column.__class__:
columns_as_list.remove(column)
return
# Reconstruct a column name to column map
columns = dict()
for column in columns_as_list:
columns[column.name] = column
image_ids = columns['Image'].values
rois = list()
# Save our file annotation to the database so we can use an unloaded
# annotation for the saveAndReturnIds that will be triggered below.
self.file_annotation = \
self.update_service.saveAndReturnObject(self.file_annotation)
unloaded_file_annotation = \
FileAnnotationI(self.file_annotation.id.val, False)
# Parse and append ROI
batch_no = 1
batches = dict()
for i, image_id in enumerate(image_ids):
unloaded_image = ImageI(image_id, False)
if False in nuclei_expected:
# Cell centre of gravity
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
shape.cx = rdouble(float(columns['Cell: cgX'].values[i]))
shape.cy = rdouble(float(columns['Cell: cgY'].values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
elif False in cells_expected:
# Nucleus centre of gravity
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
shape.cx = rdouble(float(columns['Nucleus: cgX'].values[i]))
shape.cy = rdouble(float(columns['Nucleus: cgY'].values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
else:
raise MeasurementError('Not a nucleus or cell ROI')
if len(rois) == self.ROI_UPDATE_LIMIT:
self.thread_pool.add_task(
self.update_rois, rois, batches, batch_no)
rois = list()
batch_no += 1
self.thread_pool.add_task(self.update_rois, rois, batches, batch_no)
self.thread_pool.wait_completion()
batch_keys = batches.keys()
batch_keys.sort()
for k in batch_keys:
columns['ROI'].values += batches[k]
def parse_and_populate_roi(self, columns_as_list):
# First sanity check our provided columns
names = [column.name for column in columns_as_list]
log.debug('Parsing columns: %r' % names)
cells_expected = [name in names for name in self.CELLS_CG_EXPECTED]
nuclei_expected = [name in names for name in self.NUCLEI_CG_EXPECTED]
if (False in cells_expected) and (False in nuclei_expected):
log.warn("Missing CGs for InCell dataset: %r" % names)
log.warn('Removing resultant empty ROI column.')
for column in columns_as_list:
if RoiColumn == column.__class__:
columns_as_list.remove(column)
return
# Reconstruct a column name to column map
columns = dict()
for column in columns_as_list:
columns[column.name] = column
image_ids = columns['Image'].values
rois = list()
# Save our file annotation to the database so we can use an unloaded
# annotation for the saveAndReturnIds that will be triggered below.
self.file_annotation = \
self.update_service.saveAndReturnObject(self.file_annotation)
unloaded_file_annotation = \
FileAnnotationI(self.file_annotation.id.val, False)
# Parse and append ROI
batch_no = 1
batches = dict()
for i, image_id in enumerate(image_ids):
unloaded_image = ImageI(image_id, False)
if False in nuclei_expected:
# Cell centre of gravity
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
shape.cx = rdouble(float(columns['Cell: cgX'].values[i]))
shape.cy = rdouble(float(columns['Cell: cgY'].values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
elif False in cells_expected:
# Nucleus centre of gravity
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
shape.cx = rdouble(float(columns['Nucleus: cgX'].values[i]))
shape.cy = rdouble(float(columns['Nucleus: cgY'].values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
else:
raise MeasurementError('Not a nucleus or cell ROI')
if len(rois) == self.ROI_UPDATE_LIMIT:
thread_pool.add_task(self.update_rois, rois, batches, batch_no)
rois = list()
batch_no += 1
thread_pool.add_task(self.update_rois, rois, batches, batch_no)
thread_pool.wait_completion()
batch_keys = batches.keys()
batch_keys.sort()
for k in batch_keys:
columns['ROI'].values += batches[k]
def test_save_rois(self, conn, django_client):
"""Save new ROIs to an Image"""
image = self.make_image(client=conn.c)
roi = RoiI()
roi.name = rstring("roi_name")
roi.setImage(ImageI(image.id.val, False))
point = PointI()
point.x = rdouble(1)
point.y = rdouble(2)
encoder = get_encoder(point.__class__)
point_json = encoder.encode(point)
unsaved_id = "-1:-1"
point_json['oldId'] = unsaved_id
persist_url = reverse('omero_iviewer_persist_rois')
data = {
'imageId': image.id.val,
'rois': {
'count': 1,
'new': [point_json]
}
}
rsp = post_json(django_client, persist_url, data)
print('rsp', rsp)
# {"ids": {"-1:-1": "225504:416603"}}
assert "ids" in rsp
new_ids = rsp["ids"].values()
assert len(new_ids) == 1
new_id = rsp["ids"][unsaved_id]
roi_id = int(new_id.split(':')[0])
shape_id = int(new_id.split(':')[1])
# Add Tag to ROI and Shape
tag = TagAnnotationWrapper(conn)
tag.setValue("ROI/Shape Tag")
tag.save()
roi = conn.getObject("Roi", roi_id)
roi.linkAnnotation(tag)
shape = conn.getObject("Shape", shape_id)
shape.linkAnnotation(tag)
# check...
assert len(list(conn.getAnnotationLinks(
"Shape", parent_ids=[shape_id]))) == 1
# Load Shape
rois_url = reverse('api_rois', kwargs={'api_version': 0})
rois_url += '?image=%s' % image.id.val
rsp = get_json(django_client, rois_url)
assert len(rsp['data']) == 1
# Edit Shape
point_json = rsp['data'][0]['shapes'][0]
point_json["X"] = 100
point_json["Y"] = 200
# iviewer wants to know ROI:Shape ID
point_json["oldId"] = new_id
# Unload details
del point_json["omero:details"]
data = {
'imageId': image.id.val,
'rois': {
'count': 1,
'modified': [point_json]
}
}
rsp = post_json(django_client, persist_url, data)
# IDs shouldn't have changed, e.g.
# {"ids": {"225504:416603": "225504:416603"}}
print('post rsp', rsp)
assert rsp["ids"][new_id] == new_id
# Check annotations not lost
roi = conn.getObject("Roi", roi_id)
assert len(list(roi.listAnnotations())) == 1
assert len(list(conn.getAnnotationLinks(
"Shape", parent_ids=[shape_id]))) == 1
def createBaseType(self):
return PointI()
def createBaseType(self):
warnings.warn("This module is deprecated as of OMERO 5.3.0",
DeprecationWarning)
return PointI()
