def main(argv):
# 0. Initialize Cytomine client and job
with BiaflowsJob.from_cli(argv) as nj:
nj.job.update(status=Job.RUNNING,
progress=0,
statusComment="Initialisation...")
problem_cls = CLASS_TRETRC
is_2d = False
# 1. Create working directories on the machine
# 2. Download the images
in_images, gt_images, in_path, gt_path, out_path, tmp_path = prepare_data(
problem_cls, nj, is_2d=is_2d, **nj.flags)
# 3. Call the image analysis workflow using the run script
nj.job.update(progress=25, statusComment="Launching workflow...")
workflow(in_images, out_path)
#if return_code != 0:
# err_desc = "Failed to execute the Vaa3D (return code: {})".format(return_code)
#nj.job.update(progress=50, statusComment=err_desc)
# raise ValueError(err_desc)
print('files in out_path ' + out_path + ': ')
for file in glob.glob(out_path + '/*'):
print(file)
#files = (glob.glob(in_path+"/*.tif"))
#print('Removing flipped images...')
#for i in range(0,len(files)):
# files[i] = files[i].replace('/in/','/out/')
# print(files[i])
#for out_file in files:
# os.remove(out_file)
# 4. Upload the annotation and labels to Cytomine (annotations are extracted from the mask using
# the AnnotationExporter module
upload_data(problem_cls,
nj,
in_images,
out_path,
**nj.flags,
projection=-1,
is_2d=is_2d,
monitor_params={
"start": 60,
"end": 90,
"period": 0.1,
"prefix":
"Extracting and uploading polygons from masks"
})
#5. Compute and upload the metrics
nj.job.update(
progress=80,
statusComment="Computing and uploading metrics (if necessary)...")
upload_metrics(problem_cls, nj, in_images, gt_path, out_path, tmp_path,
**nj.flags)
nj.job.update(status=Job.TERMINATED,
progress=100,
statusComment="Finished.")
def run(query, sid):
start = datetime.now().microsecond
data = workflow(query, sid, sessions)
end = datetime.now().microsecond
data["sid"] = sid
delta = (end - start) / 1000
data["ms"] = delta
sessions[sid] = data
logging.info(f"Query {query} in {delta}ms")
import ROOT as r
from workflow import workflow
f = r.TFile("../tuples/bae-mc-11114003-2012-down.root")
t = f.Get("bar-muon-tuple/DecayTree")
fnew = r.TFile("newtree.root","RECREATE")
tnew = t.CloneTree(-1,'fast')
tnew.SetBranchStatus('*',0)
myworkflow = workflow()
myworkflow.module_names.append('addRestFrameVars')
myworkflow.run(tnew)
fnew.cd()
tnew.Write()
fnew.Close()
import ROOT as r
from workflow import workflow
fsig = r.TFile("../bae-mc-12215002-2012-down.root")
tsig = fsig.Get("bar-muon-tuple/DecayTree")
f = r.TFile("../BuKMuMuX.root")
t = f.Get("Bplus_Tuple/DecayTree")
fnew = r.TFile("newtree.root","RECREATE")
tnew = t.CloneTree(-1,'fast')
tnew.SetBranchStatus('*',0)
myworkflow = workflow()
myworkflow.module_names.append('addRestFrameVars')
myworkflow.run(tnew)
def main(argv):
# 0. Initialize Cytomine client and job
with CytomineJob.from_cli(argv) as cj:
cj.job.update(status=Job.RUNNING,
progress=0,
statusComment="Initialisation...")
# 1. Create working directories on the machine:
# - WORKING_PATH/in: input images
# - WORKING_PATH/out: output images
# - WORKING_PATH/ground_truth: ground truth images
base_path = "{}".format(os.getenv("HOME"))
gt_suffix = "_lbl"
working_path = os.path.join(base_path, str(cj.job.id))
in_path = os.path.join(working_path, "in")
out_path = os.path.join(working_path, "out")
gt_path = os.path.join(working_path, "ground_truth")
if not os.path.exists(working_path):
os.makedirs(working_path)
os.makedirs(in_path)
os.makedirs(out_path)
os.makedirs(gt_path)
# 2. Download the images (first input, then ground truth image)
cj.job.update(
progress=1,
statusComment="Downloading images (to {})...".format(in_path))
image_group = ImageGroupCollection().fetch_with_filter(
"project", cj.parameters.cytomine_id_project)
input_images = [i for i in image_group if gt_suffix not in i.name]
gt_images = [i for i in image_group if gt_suffix in i.name]
for input_image in input_images:
input_image.download(os.path.join(in_path, "{id}.tif"))
for gt_image in gt_images:
related_name = gt_image.name.replace(gt_suffix, '')
related_image = [i for i in input_images if related_name == i.name]
if len(related_image) == 1:
gt_image.download(
os.path.join(gt_path,
"{}.tif".format(related_image[0].id)))
# 3. Call the image analysis workflow using the run script
cj.job.update(progress=25, statusComment="Launching workflow...")
#TODO: error handling
workflow(in_path, out_path)
# if return_code != 0:
# err_desc = "Failed to execute the ImageJ macro (return code: {})".format(return_code)
# cj.job.update(progress=50, statusComment=err_desc)
# raise ValueError(err_desc)
# 4. Upload .swc and attach to correponding image
# ! not needed if we compute directly the metric
for image in cj.monitor(
input_images,
start=60,
end=80,
period=0.1,
prefix="Extracting and uploading polygons from masks"):
afile = "{}.swc".format(image.id)
path = os.path.join(out_path, afile)
AttachedFile(image, filename=path).upload()
# 4. Upload the annotation and labels to Cytomine (annotations are extracted from the mask using
# the AnnotationExporter module)
# for image in cj.monitor(input_images, start=60, end=80, period=0.1, prefix="Extracting and uploading polygons from masks"):
# file = "{}.tif".format(image.id)
# path = os.path.join(out_path, file)
# data = io.imread(path)
# extract objects
# slices = mask_to_objects_2d(data)
# print("Found {} polygons in this image {}.".format(len(slices), image.id))
# upload
# collection = AnnotationCollection()
# for obj_slice in slices:
# collection.append(Annotation(
# location=affine_transform(obj_slice.polygon, [1, 0, 0, -1, 0, image.height]).wkt,
# id_image=image.id, id_project=cj.parameters.cytomine_id_project, property=[
# {"key": "index", "value": str(obj_slice.label)}
# ]
# ))
# collection.save()
# 5. Compute the metrics
cj.job.update(progress=80, statusComment="Computing metrics...")
# TODO: compute metrics:
# in /out: output files {id}.tiff
# in /ground_truth: label files {id}.tiff
cj.job.update(progress=99, statusComment="Cleaning...")
for image in input_images:
os.remove(os.path.join(in_path, "{}.tif".format(image.id)))
cj.job.update(status=Job.TERMINATED,
progress=100,
statusComment="Finished.")
# type: ignore
# pylint: disable-all
# isort: skip
import sys
from workflow import run_workflow as workflow
sys.path.append('./tests/profiling')
if __name__ == '__main__':
workflow()