def profile_projections(
self,
axis=None,
csv=False,
csv_dest_pattern="projections-annotation-{id}.csv"):
"""
Get profile projections (min, max, average) for the given annotation.
Parameters
----------
axis The axis along which the projections (min, max, average) are performed. By default last axis is used.
To project along spatial X, Y axes, use special value "xy" or "spatial".
csv True to return result in a CSV file.
csv_dest_pattern The CSV destination pattern.
"""
if self.id is None:
raise ValueError("Cannot review an annotation with no ID.")
uri = "{}/{}/profile/projections.{}".format(self.callback_identifier,
self.id,
"csv" if csv else "json")
if csv:
pattern = re.compile("{(.*?)}")
destination = re.sub(
pattern,
lambda m: str(getattr(self,
str(m.group(0))[1:-1], "_")),
csv_dest_pattern)
return Cytomine.get_instance().download_file(
uri, destination, payload={"axis": axis})
data = Cytomine.get_instance().get(uri, {"axis": axis})
return data['collection'] if "collection" in data else data
def update(self, id=None, **attributes):
Cytomine.get_instance().log(
"Job (id:{job_id}) status update: \"{statusComment}\" (status: {status}, progress: {progress}%)"
.format(job_id=self.id,
statusComment=attributes.get("statusComment",
self.statusComment),
status=_HUMAN_READABLE_JOB_STATUS[attributes.get(
"status", self.status)],
progress=attributes.get("progress", self.progress)))
return super(Job, self).update(id=id, **attributes)
def profile(self):
if self.id is None:
raise ValueError("Cannot review an annotation with no ID.")
data = Cytomine.get_instance().get("{}/{}/profile.json".format(
self.callback_identifier, self.id))
return data['collection'] if "collection" in data else data
def download(self, dest_pattern="{originalFilename}", override=True, parent=False):
"""
Download the original image.
Parameters
----------
dest_pattern : str, optional
Destination path for the downloaded image. "{X}" patterns are replaced by the value of X attribute
if it exists.
override : bool, optional
True if a file with same name can be overrided by the new file.
parent : bool, optional
True to download image parent if the abstract image is a part of a multidimensional file.
Returns
-------
downloaded : bool
True if everything happens correctly, False otherwise.
"""
if self.id is None:
raise ValueError("Cannot dump an annotation with no ID.")
pattern = re.compile("{(.*?)}")
dest_pattern = re.sub(pattern, lambda m: str(getattr(self, str(m.group(0))[1:-1], "_")), dest_pattern)
parameters = {"parent": parent}
destination = os.path.dirname(dest_pattern)
if not os.path.exists(destination):
os.makedirs(destination)
return Cytomine.get_instance().download_file("{}/{}/download".format(self.callback_identifier, self.id),
dest_pattern, override, parameters)
def rectangle(self, x, y, width, height):
uri = "imagegroupHDF5/{}/{}/{}/{}/{}/rectangle.json".format(self.id, x, y, width, height)
collection = Cytomine.get_instance().get(uri)["collection"]
spectrum = np.array([data["spectra"] for data in collection])
spectrum = np.expand_dims(spectrum, axis=1)
_, _, depth = spectrum.shape
return spectrum.reshape((width, height, depth))
def merge(self, id_other_annotation_group):
if self.id is None:
raise ValueError("Cannot merge an annotaiton group with no ID.")
return Cytomine.get_instance().post(
"annotationgroup/{}/annotationgroup/{}/merge.json".format(
self.id, id_other_annotation_group))
def connect(request):
c = Cytomine.connect(request.config.getoption("--host"),
request.config.getoption("--public_key"),
request.config.getoption("--private_key"),
logging.DEBUG)
c.open_admin_session()
return c
def fetch(self, id=None):
if self.id is None and id is None:
raise ValueError("Cannot fetch a model with no ID.")
if id is not None:
self.id = id
return Cytomine.get_instance().get_model(self, self.query_parameters)
def save(self, chunk=15, n_workers=0):
"""
chunk: int|None
Maximum number of object to send at once in a single HTTP request. None for sending them all at once.
n_workers: int
Number of threads to use for sending chunked requests (ignored if chunk is None). Value 0 for using as many threads as cpus on the machine.
"""
if chunk is None:
return Cytomine.get_instance().post_collection(self)
elif isinstance(chunk, int):
def upload_fn(collection):
if not isinstance(collection, Collection):
_tmp = self.__class__(self._model)
_tmp.extend(collection)
collection = _tmp
return Cytomine.get_instance().post_collection(collection)
results = generic_chunk_parallel(self,
worker_fn=upload_fn,
chunk_size=chunk,
n_workers=n_workers)
added, failed = list(), list()
for (start, end), success in results:
(added if success else failed).extend(self[start:end])
if len(added) != len(self):
raise CollectionPartialUploadException(
"Some annotations could not be uploaded",
created=added,
failed=failed)
return True
else:
raise ValueError(
"Invalid value '{}' for chunk parameter.".format(chunk))
def delete(self, id=None):
if self.id is None and id is None:
raise ValueError("Cannot delete a model with no ID.")
if id is not None:
self.id = id
return Cytomine.get_instance().delete_model(self)
def upload(self, filename):
if self.is_new():
raise ValueError("Cannot upload file if not existing ID.")
return Cytomine.get_instance().upload_file(
self,
filename,
uri="{}/{}/upload".format(self.callback_identifier, self.id))
def image_servers(self):
if not self._image_servers:
data = Cytomine.get_instance().get(
"{}/{}/imageservers.json".format(self.callback_identifier,
self.id))
self._image_servers = data["imageServersURLs"]
return self._image_servers
def _fetch(self, append_mode=False):
if len(self._filters) == 0 and None not in self._allowed_filters:
raise ValueError(
"This collection cannot be fetched without a filter.")
return Cytomine.get_instance().get_collection(self, self.parameters,
append_mode)
def download(self, dest_pattern="{originalFilename}", override=True, parent=False):
"""
Download the original image.
Parameters
----------
dest_pattern : str, optional
Destination path for the downloaded image. "{X}" patterns are replaced by the value of X attribute
if it exists.
override : bool, optional
True if a file with same name can be overrided by the new file.
parent : bool, optional
True to download image parent if the abstract image is a part of a multidimensional file.
Returns
-------
downloaded : bool
True if everything happens correctly, False otherwise.
"""
if self.id is None:
raise ValueError("Cannot dump an annotation with no ID.")
pattern = re.compile("{(.*?)}")
dest_pattern = re.sub(pattern, lambda m: str(getattr(self, str(m.group(0))[1:-1], "_")), dest_pattern)
parameters = {"parent": parent}
destination = os.path.dirname(dest_pattern)
if not os.path.exists(destination):
os.makedirs(destination)
return Cytomine.get_instance().download_file("{}/{}/download".format(self.callback_identifier, self.id),
dest_pattern, override, parameters)
def review(self, id_terms=None):
if self.id is None:
raise ValueError("Cannot review an annotation with no ID.")
if not id_terms:
id_terms = []
data = {"id": self.id, "terms": id_terms}
return Cytomine.get_instance().post("{}/{}/review.json".format(self.callback_identifier, self.id), data)
def rectangle(self, x, y, width, height):
uri = "imagegroupHDF5/{}/{}/{}/{}/{}/rectangle.json".format(
self.id, x, y, width, height)
collection = Cytomine.get_instance().get(uri)["collection"]
spectrum = np.array([data["spectra"] for data in collection])
spectrum = np.expand_dims(spectrum, axis=1)
_, _, depth = spectrum.shape
return spectrum.reshape((width, height, depth))
def dump_crops(self,
dest_pattern,
n_workers=0,
override=True,
**dump_params):
"""Download the crops of the annotations
Parameters
----------
dest_pattern : str, optional
Destination path for the downloaded image. "{X}" patterns are replaced by the value of X attribute
if it exists.
override : bool, optional
True if a file with same name can be overrided by the new file.
n_workers: int
Number of workers to use (default: uses all the available processors)
dump_params: dict
Parameters for dumping the annotations (see Annotation.dump)
Returns
-------
annotations: AnnotationCollection
Annotations that have been successfully downloaded (containing a `filenames` attribute)
"""
def dump_crop(an):
if is_false(
an.dump(dest_pattern=dest_pattern,
override=override,
**dump_params)):
return False
else:
return an
results = generic_download(self,
download_instance_fn=dump_crop,
n_workers=n_workers)
# check errors
count_fail = 0
failed = list()
for in_annot, out_annot in results:
if is_false(out_annot):
count_fail += 1
failed.append(in_annot.id)
logger = Cytomine.get_instance().logger
if count_fail > 0:
n_annots = len(self)
ratio = 100 * count_fail / float(n_annots)
logger.info(
"Failed to download crops for {}/{} annotations ({:3.2f} %).".
format(count_fail, n_annots, ratio))
logger.debug(
"Annotation with crop download failure: {}".format(failed))
collection = AnnotationCollection()
collection.extend(
[an for _, an in results if not isinstance(an, bool) or an])
return collection
def download(self, destination="{filename}", override=False):
if self.is_new():
raise ValueError("Cannot download file if not existing ID.")
pattern = re.compile("{(.*?)}")
destination = re.sub(pattern, lambda m: str(getattr(self, str(m.group(0))[1:-1], "_")), destination)
return Cytomine.get_instance().download_file("{}/{}/download".format(self.callback_identifier, self.id),
destination, override)
def update(self, id=None, **attributes):
if self.id is None and id is None:
raise ValueError("Cannot update a model with no ID.")
if id is not None:
self.id = id
if attributes:
self.populate(attributes)
return Cytomine.get_instance().put_model(self)
def upload(self):
return Cytomine.get_instance().upload_file(self,
self.filename,
query_parameters={
"domainClassName":
self.domainClassName,
"domainIdent":
self.domainIdent
})
def execute(self):
if self.is_new():
raise ValueError("Cannot execute job if no ID was provided.")
response = Cytomine.get_instance().post(
uri="{}/{}/execute.json".format(self.callback_identifier, self.id),
data=self.to_json(),
query_parameters={id: self.id})
self.populate(response)
return self
def execute(self):
if self.is_new():
raise ValueError("Cannot execute job if no ID was provided.")
response = Cytomine.get_instance().post(uri="{}/{}/execute.json"
.format(self.callback_identifier, self.id),
data=self.to_json(),
query_parameters={id: self.id})
self.populate(response)
return self
def review(self, id_terms=None):
if self.id is None:
raise ValueError("Cannot review an annotation with no ID.")
if not id_terms:
id_terms = []
data = {"id": self.id, "terms": id_terms}
return Cytomine.get_instance().post(
"{}/{}/review.json".format(self.callback_identifier, self.id),
data)
def fetch(self, id=None, key=None):
if self.id is None and id is None and self.key is None and key is None:
raise ValueError("Cannot fetch a model with no ID and no key.")
if id is not None:
self.id = id
if key is not None:
self.key = key
self._by_key = True
model = Cytomine.get_instance().get_model(self, self.query_parameters)
self._by_key = False
return model
def fetch(self, id=None, key=None):
if self.id is None and id is None and self.key is None and key is None:
raise ValueError("Cannot fetch a model with no ID and no key.")
if id is not None:
self.id = id
if key is not None:
self.key = key
self._by_key = True
model = Cytomine.get_instance().get_model(self, self.query_parameters)
self._by_key = False
return model
def reference_slice(self):
if self.id is None:
raise ValueError(
"Cannot get the reference slice of an image with no ID.")
if not self._reference_slice:
data = Cytomine.get_instance().get(
"imageinstance/{}/sliceinstance/reference.json".format(
self.id))
self._reference_slice = SliceInstance().populate(
data) if data else False
return self._reference_slice
def fetch(self, id_term1=None, id_term2=None):
self.id = -1
if self.term1 is None and id_term1 is None:
raise ValueError("Cannot fetch a model with no term 1 ID.")
elif self.term2 is None and id_term2 is None:
raise ValueError("Cannot fetch a model with no term 2 ID.")
if id_term1 is not None:
self.term1 = id_term1
if id_term2 is not None:
self.term2 = id_term2
return Cytomine.get_instance().get_model(self, self.query_parameters)
def fetch(self, id_annotation=None, id_term=None):
self.id = -1
if self.annotation is None and id_annotation is None:
raise ValueError("Cannot fetch a model with no annotation ID.")
elif self.term is None and id_term is None:
raise ValueError("Cannot fetch a model with no term ID.")
if id_annotation is not None:
self.annotation = id_annotation
if id_term is not None:
self.term = id_term
return Cytomine.get_instance().get_model(self, self.query_parameters)
def fetch(self, id_term1=None, id_term2=None):
self.id = -1
if self.term1 is None and id_term1 is None:
raise ValueError("Cannot fetch a model with no term 1 ID.")
elif self.term2 is None and id_term2 is None:
raise ValueError("Cannot fetch a model with no term 2 ID.")
if id_term1 is not None:
self.term1 = id_term1
if id_term2 is not None:
self.term2 = id_term2
return Cytomine.get_instance().get_model(self, self.query_parameters)
def fetch(self, id_annotation=None, id_track=None):
self.id = -1
if self.annotationIdent is None and id_annotation is None:
raise ValueError("Cannot fetch a model with no annotation ID.")
elif self.track is None and id_track is None:
raise ValueError("Cannot fetch a model with no term ID.")
if id_annotation is not None:
self.annotationIdent = id_annotation
if id_track is not None:
self.track = id_track
return Cytomine.get_instance().get_model(self, self.query_parameters)
def fetch(self, id_user=None, id_role=None):
self.id = -1
if self.user is None and id_user is None:
raise ValueError("Cannot fetch a model with no user ID.")
elif self.role is None and id_role is None:
raise ValueError("Cannot fetch a model with no role ID.")
if id_user is not None:
self.user = id_user
if id_role is not None:
self.role = id_role
return Cytomine.get_instance().get_model(self, self.query_parameters)
def fetch(self, id_user=None, id_role=None):
self.id = -1
if self.user is None and id_user is None:
raise ValueError("Cannot fetch a model with no user ID.")
elif self.role is None and id_role is None:
raise ValueError("Cannot fetch a model with no role ID.")
if id_user is not None:
self.user = id_user
if id_role is not None:
self.role = id_role
return Cytomine.get_instance().get_model(self, self.query_parameters)
def profile(self, x, y, width=None, height=None):
import numpy as np
from shapely.geometry import Point, box
geometry = box(x, y, x + width, y +
height) if (width and height) else Point(x, y)
uri = "{}/{}/profile.json".format(self.callback_identifier, self.id)
data = Cytomine.get_instance().get(uri, {"geometry": geometry})
if width and height:
data = data["collection"]
depth = len(data[0]["profile"])
profile = np.empty((height, width, depth), dtype=np.uint)
for p in data:
row = p["point"][1] - y
col = p["point"][0] - x
profile[row, col, :] = p["profile"]
return profile
else:
return np.asarray([[data["profile"]]])
def dump(self, dest_pattern="{id}.jpg", override=True, mask=False, alpha=False, bits=8,
zoom=None, max_size=None, increase_area=None, contrast=None, gamma=None, colormap=None, inverse=None):
"""
Download the annotation crop, with optional image modifications.
Parameters
----------
dest_pattern : str, optional
Destination path for the downloaded image. "{X}" patterns are replaced by the value of X attribute
if it exists.
override : bool, optional
True if a file with same name can be overrided by the new file.
mask : bool, optional
True if a binary mask based on given annotations must be returned, False otherwise.
alpha : bool, optional
True if image background (outside annotations) must be transparent, False otherwise.
zoom : int, optional
Optional image zoom number
bits : int (8,16,32) or str ("max"), optional
Bit depth (bit per channel) of returned image. "max" returns the original image bit depth
max_size : int, tuple, optional
Maximum size (width or height) of returned image. None to get original size.
increase_area : float, optional
Increase the crop size. For example, an annotation whose bounding box size is (w,h) will have
a crop dimension of (w*increase_area, h*increase_area).
contrast : float, optional
Optional contrast applied on returned image.
gamma : float, optional
Optional gamma applied on returned image.
colormap : int, optional
Cytomine identifier of a colormap to apply on returned image.
inverse : bool, optional
True to inverse color mapping, False otherwise.
Returns
-------
downloaded : bool
True if everything happens correctly, False otherwise. As a side effect, object attribute "filename"
is filled with downloaded file path.
"""
if self.id is None:
raise ValueError("Cannot dump an annotation with no ID.")
pattern = re.compile("{(.*?)}")
dest_pattern = re.sub(pattern, lambda m: str(getattr(self, str(m.group(0))[1:-1], "_")), dest_pattern)
destination = os.path.dirname(dest_pattern)
filename, extension = os.path.splitext(os.path.basename(dest_pattern))
extension = extension[1:]
if extension not in ("jpg", "png", "tif", "tiff"):
extension = "jpg"
if not os.path.exists(destination):
os.makedirs(destination)
parameters = {
"zoom": zoom,
"maxSize": max_size,
"increaseArea": increase_area,
"contrast": contrast,
"gamma": gamma,
"colormap": colormap,
"inverse": inverse,
"bits": bits
}
if mask and alpha:
image = "alphamask"
if extension == "jpg":
extension = "png"
elif mask:
image = "mask"
else:
image = "crop"
file_path = os.path.join(destination, "{}.{}".format(filename, extension))
url = self.cropURL.replace("crop.jpg", "{}.{}".format(image, extension))
result = Cytomine.get_instance().download_file(url, file_path, override, parameters)
if result:
self.filename = file_path
return result
import time
job_id = 59008611 #job de colordec segmentation
image_id = 37167157
working_path = '/data/home/adeblire/tmp'
cell_max_area = 2000 #aire max en pixel, à changer en m
cell_min_area = 600 #aire min en pixel, à changer en m
cell_min_circularity = 0.7 #circularité min
cluster_min_cell_nb = 3 #nombre minimum de cellules pour constituer un cluster
start_time = time.time()
conn = Cytomine('beta.cytomine.be', 'd8bee9aa-4d6e-4cb4-a7e8-2d3100f0ba24', 'a3227ede-6ec5-4711-b621-6c14b2f8da45', working_path, base_path = "/api/", verbose = False)
print "Create Job and UserJob..."
image_instance = conn.getImageInstance(image_id)
software_id = 18104673
user_job = conn.addUserJob(software_id, image_instance.project)
#Switch to job Connection
conn.set_credentials(str(user_job.publicKey), str(user_job.privateKey))
job = conn.getJob(user_job.job)
job = conn.update_job_status(job, status_comment = "Create software parameters values...")
#job_parameters_values = conn.add_job_parameters(user_job.job, conn.getSoftware(id_software), pyxit_parameters)
job = conn.update_job_status(job, status = job.RUNNING, progress = 0, status_comment = "Loading data...")
print "downloading annotations ..."
def upload(self):
return Cytomine.get_instance().upload_file(self, self.filename,
query_parameters={"domainClassName": self.domainClassName,
"domainIdent": self.domainIdent})
def fetch(self, id=None):
if id is not None:
self.id = id
return Cytomine.get_instance().get_model(self, self.query_parameters)
def keys(self):
# Only works if you are superadmin.
if hasattr(self, "id") and self.id:
return Cytomine.get_instance().get("user/{}/keys.json".format(self.id))
def save(self):
return Cytomine.get_instance().post_collection(self)
def window(self, x, y, w, h, dest_pattern="{id}-{x}-{y}-{w}-{h}.jpg", override=True, mask=None, alpha=None,
bits=8, annotations=None, terms=None, users=None, reviewed=None):
"""
Extract a window (rectangle) from an image and download it.
Parameters
----------
x : int
The X position of window top-left corner. 0 is image left.
y : int
The Y position of window top-left corner. 0 is image top.
w : int
The window width
h : int
The window height
dest_pattern : str, optional
Destination path for the downloaded image. "{X}" patterns are replaced by the value of X attribute
if it exists.
override : bool, optional
True if a file with same name can be overrided by the new file.
mask : bool, optional
True if a binary mask based on given annotations must be returned, False otherwise.
alpha : bool, optional
True if image background (outside annotations) must be transparent, False otherwise.
bits : int (8/16/32), optional
Optional output bit depth of returned images
annotations : list of int, optional
If mask=True or alpha=True, annotation identifiers that must be taken into account for masking
terms : list of int, optional
If mask=True or alpha=True, term identifiers that must be taken into account for masking
users : list of int, optional
If mask=True or alpha=True, user identifiers that must be taken into account for masking
reviewed : bool, optional
If mask=True or alpha=True, indicate if only reviewed annotations mut be taken into account for masking
Returns
-------
downloaded : bool
True if everything happens correctly, False otherwise.
"""
self.x = x
self.y = y
self.w = w
self.h = h
pattern = re.compile("{(.*?)}")
dest_pattern = re.sub(pattern, lambda m: str(getattr(self, str(m.group(0))[1:-1], "_")), dest_pattern)
del self.x
del self.y
del self.w
del self.h
destination = os.path.dirname(dest_pattern)
filename, extension = os.path.splitext(os.path.basename(dest_pattern))
extension = extension[1:]
if extension not in ("jpg", "png", "tif", "tiff"):
extension = "jpg"
if not os.path.exists(destination):
os.makedirs(destination)
if mask is None and alpha is None:
alphamask = None
elif mask and alpha:
alphamask = True
if extension == "jpg":
extension = "png"
else:
alphamask = False
# Temporary fix due to Cytomine-core
if mask is not None:
mask = str(mask).lower()
if alphamask is not None:
alphamask = str(alphamask).lower()
# ===
parameters = {
"annotations": ",".join(str(item) for item in annotations) if annotations else None,
"terms": ",".join(str(item) for item in terms) if terms else None,
"users": ",".join(str(item) for item in users) if users else None,
"reviewed": reviewed,
"bits": bits,
"mask": mask,
"alphaMask": alphamask
}
file_path = os.path.join(destination, "{}.{}".format(filename, extension))
return Cytomine.get_instance().download_file("{}/{}/window-{}-{}-{}-{}.{}".format(
self.callback_identifier, self.id, x, y, w, h, extension), file_path, override, parameters)
def characteristics(self):
uri = "imagegroup/{}/characteristics.json".format(self.id)
return Cytomine.get_instance().get(uri)
def window(self, x, y, w, h, dest_pattern="{id}-{x}-{y}-{w}-{h}.jpg", override=True, mask=None, alpha=None,
bits=8, annotations=None, terms=None, users=None, reviewed=None):
"""
Extract a window (rectangle) from an image and download it.
Parameters
----------
x : int
The X position of window top-left corner. 0 is image left.
y : int
The Y position of window top-left corner. 0 is image top.
w : int
The window width
h : int
The window height
dest_pattern : str, optional
Destination path for the downloaded image. "{X}" patterns are replaced by the value of X attribute
if it exists.
override : bool, optional
True if a file with same name can be overrided by the new file.
mask : bool, optional
True if a binary mask based on given annotations must be returned, False otherwise.
alpha : bool, optional
True if image background (outside annotations) must be transparent, False otherwise.
bits : int (8/16/32), optional
Optional output bit depth of returned images
annotations : list of int, optional
If mask=True or alpha=True, annotation identifiers that must be taken into account for masking
terms : list of int, optional
If mask=True or alpha=True, term identifiers that must be taken into account for masking
users : list of int, optional
If mask=True or alpha=True, user identifiers that must be taken into account for masking
reviewed : bool, optional
If mask=True or alpha=True, indicate if only reviewed annotations mut be taken into account for masking
Returns
-------
downloaded : bool
True if everything happens correctly, False otherwise.
"""
self.x = x
self.y = y
self.w = w
self.h = h
pattern = re.compile("{(.*?)}")
dest_pattern = re.sub(pattern, lambda m: str(getattr(self, str(m.group(0))[1:-1], "_")), dest_pattern)
del self.x
del self.y
del self.w
del self.h
destination = os.path.dirname(dest_pattern)
filename, extension = os.path.splitext(os.path.basename(dest_pattern))
extension = extension[1:]
if extension not in ("jpg", "png", "tif", "tiff"):
extension = "jpg"
if not os.path.exists(destination):
os.makedirs(destination)
if mask is None and alpha is None:
alphamask = None
elif mask and alpha:
alphamask = True
if extension == "jpg":
extension = "png"
else:
alphamask = False
# Temporary fix due to Cytomine-core
if mask is not None:
mask = str(mask).lower()
if alphamask is not None:
alphamask = str(alphamask).lower()
# ===
parameters = {
"annotations": ",".join(str(item) for item in annotations) if annotations else None,
"terms": ",".join(str(item) for item in terms) if terms else None,
"users": ",".join(str(item) for item in users) if users else None,
"reviewed": reviewed,
"bits": bits,
"mask": mask,
"alphaMask": alphamask
}
file_path = os.path.join(destination, "{}.{}".format(filename, extension))
return Cytomine.get_instance().download_file("{}/{}/window-{}-{}-{}-{}.{}".format(
self.callback_identifier, self.id, x, y, w, h, extension), file_path, override, parameters)
def dump(self, dest_pattern="{id}.jpg", override=True, max_size=None, bits=8, contrast=None, gamma=None,
colormap=None, inverse=None):
"""
Download the image with optional image modifications.
Parameters
----------
dest_pattern : str, optional
Destination path for the downloaded image. "{X}" patterns are replaced by the value of X attribute
if it exists.
override : bool, optional
True if a file with same name can be overrided by the new file.
max_size : int, tuple, optional
Maximum size (width or height) of returned image. None to get original size.
bits : int (8,16,32) or str ("max"), optional
Bit depth (bit per channel) of returned image. "max" returns the original image bit depth
contrast : float, optional
Optional contrast applied on returned image.
gamma : float, optional
Optional gamma applied on returned image.
colormap : int, optional
Cytomine identifier of a colormap to apply on returned image.
inverse : bool, optional
True to inverse color mapping, False otherwise.
Returns
-------
downloaded : bool
True if everything happens correctly, False otherwise. As a side effect, object attribute "filename"
is filled with downloaded file path.
"""
if self.id is None:
raise ValueError("Cannot dump an annotation with no ID.")
pattern = re.compile("{(.*?)}")
dest_pattern = re.sub(pattern, lambda m: str(getattr(self, str(m.group(0))[1:-1], "_")), dest_pattern)
destination = os.path.dirname(dest_pattern)
filename, extension = os.path.splitext(os.path.basename(dest_pattern))
extension = extension[1:]
if extension not in ("jpg", "png", "tif", "tiff"):
extension = "jpg"
if not os.path.exists(destination):
os.makedirs(destination)
if isinstance(max_size, tuple) or max_size is None:
max_size = max(self.width, self.height)
parameters = {
"maxSize": max_size,
"contrast": contrast,
"gamma": gamma,
"colormap": colormap,
"inverse": inverse,
"bits": bits
}
file_path = os.path.join(destination, "{}.{}".format(filename, extension))
url = self.preview[:self.preview.index("?")]
url = url.replace(".png", ".{}".format(extension))
result = Cytomine.get_instance().download_file(url, file_path, override, parameters)
if result:
self.filename = file_path
return result
def keys(self):
return Cytomine.get_instance().get("userkey/{}/keys.json".format(self.publicKey))
def upload(self, filename):
if self.is_new():
raise ValueError("Cannot upload file if not existing ID.")
return Cytomine.get_instance().upload_file(self, filename,
uri="{}/{}/upload".format(self.callback_identifier, self.id))
def pixel(self, x, y):
uri = "imagegroupHDF5/{}/{}/{}/pixel.json".format(self.id, x, y)
return np.asarray([[Cytomine.get_instance().get(uri)["spectra"]]])
def dump(self, dest_pattern="{id}.jpg", override=True, max_size=None, bits=8, contrast=None, gamma=None,
colormap=None, inverse=None):
"""
Download the image with optional image modifications.
Parameters
----------
dest_pattern : str, optional
Destination path for the downloaded image. "{X}" patterns are replaced by the value of X attribute
if it exists.
override : bool, optional
True if a file with same name can be overrided by the new file.
max_size : int, tuple, optional
Maximum size (width or height) of returned image. None to get original size.
bits : int (8,16,32) or str ("max"), optional
Bit depth (bit per channel) of returned image. "max" returns the original image bit depth
contrast : float, optional
Optional contrast applied on returned image.
gamma : float, optional
Optional gamma applied on returned image.
colormap : int, optional
Cytomine identifier of a colormap to apply on returned image.
inverse : bool, optional
True to inverse color mapping, False otherwise.
Returns
-------
downloaded : bool
True if everything happens correctly, False otherwise. As a side effect, object attribute "filename"
is filled with downloaded file path.
"""
if self.id is None:
raise ValueError("Cannot dump an annotation with no ID.")
pattern = re.compile("{(.*?)}")
dest_pattern = re.sub(pattern, lambda m: str(getattr(self, str(m.group(0))[1:-1], "_")), dest_pattern)
destination = os.path.dirname(dest_pattern)
filename, extension = os.path.splitext(os.path.basename(dest_pattern))
extension = extension[1:]
if extension not in ("jpg", "png", "tif", "tiff"):
extension = "jpg"
if not os.path.exists(destination):
os.makedirs(destination)
if isinstance(max_size, tuple) or max_size is None:
max_size = max(self.width, self.height)
parameters = {
"maxSize": max_size,
"contrast": contrast,
"gamma": gamma,
"colormap": colormap,
"inverse": inverse,
"bits": bits
}
file_path = os.path.join(destination, "{}.{}".format(filename, extension))
url = self.preview[:self.preview.index("?")]
url = url.replace(".png", ".{}".format(extension))
result = Cytomine.get_instance().download_file(url, file_path, override, parameters)
if result:
self.filename = file_path
return result
def _fetch(self, append_mode=False):
if len(self._filters) == 0 and None not in self._allowed_filters:
raise ValueError("This collection cannot be fetched without a filter.")
return Cytomine.get_instance().get_collection(self, self.parameters, append_mode)
def signature(self):
return Cytomine.get_instance().get("signature.json")
def characteristics(self):
uri = "imagegroup/{}/characteristics.json".format(self.id)
return Cytomine.get_instance().get(uri)
def image_servers(self):
if not self._image_servers:
data = Cytomine.get_instance().get("{}/{}/imageservers.json".format(self.callback_identifier, self.id))
self._image_servers = data["imageServersURLs"]
return self._image_servers
def save(self):
self.id = None
return Cytomine.get_instance().post_model(self)
#struct_elem = np.array( [[0, 1, 1, 1, 0],
# [1, 1, 1, 1, 1],
# [1, 1, 1, 1, 1],
# [1, 1, 1, 1, 1],
# [0, 1, 1, 1, 0]], dtype = np.uint8)
#struct_elem = np.array( [[0, 1, 0],
# [1, 1, 1],
# [0, 1, 0]], dtype = np.uint8)
#struct_elem = cv2.getStructuringElement(cv2.MORPH_CROSS,(9,9))
start_time = time.time()
conn = Cytomine('beta.cytomine.be', 'd8bee9aa-4d6e-4cb4-a7e8-2d3100f0ba24', 'a3227ede-6ec5-4711-b621-6c14b2f8da45', working_path, base_path = "/api/", verbose = True)
print "Create Job and UserJob..."
image_instance = conn.get_image_instance(image_id)
image_height = image_instance.height
image_width = image_instance.width
user_job = conn.add_user_job(software_id, image_instance.project)
#Switch to job Connection
conn.set_credentials(str(user_job.publicKey), str(user_job.privateKey))
job = conn.get_job(user_job.job)
job = conn.update_job_status(job, status_comment = "Create software parameters values...")
#job_parameters_values = conn.add_job_parameters(user_job.job, conn.getSoftware(id_software), pyxit_parameters)
job = conn.update_job_status(job, status = job.RUNNING, progress = 0, status_comment = "Loading data...")
def pixel(self, x, y):
uri = "imagegroupHDF5/{}/{}/{}/pixel.json".format(self.id, x, y)
return np.asarray([[Cytomine.get_instance().get(uri)["spectra"]]])
def image_servers(self):
if not self._image_servers:
data = Cytomine.get_instance().get("abstractimage/{}/imageservers.json".format(self.baseImage))
self._image_servers = data["imageServersURLs"]
return self._image_servers
