"If unset, all images in the project are used.",
default=None)
parser.add_argument('--cytomine_id_job')
params, _ = parser.parse_known_args(sys.argv[1:])
with Cytomine(params.cytomine_host, params.cytomine_public_key,
params.cytomine_private_key) as c:
id_tags_for_images = params.cytomine_id_tags_for_images
id_project = params.cytomine_id_project
image_tags = id_tags_for_images if id_tags_for_images else None
images = ImageInstanceCollection(tags=image_tags).fetch_with_filter(
"project", id_project)
image_ids = [image.id for image in images]
groundtruths = AnnotationCollection()
groundtruths.showTerm = True
groundtruths.showWKT = True
groundtruths.images = image_ids
groundtruths.fetch()
predictions = AnnotationCollection()
predictions.showTerm = True
predictions.showWKT = True
predictions.images = image_ids
predictions.job = params.cytomine_id_job
predictions.fetch()
print("There are {} groundtruths and {} predictions".format(
len(groundtruths), len(predictions)))
def main(argv):
with CytomineJob.from_cli(argv) as cj:
cj.job.update(progress=1, statusComment="Initialisation")
cj.log(str(cj.parameters))
term_ids = [int(term_id) for term_id in cj.parameters.cytomine_id_terms.split(",")]
terms = TermCollection().fetch_with_filter("project", cj.parameters.cytomine_id_project)
terms = [term for term in terms if term.id in term_ids]
image_ids = [int(image_id) for image_id in cj.parameters.cytomine_id_images.split(",")]
images = ImageInstanceCollection(light=True).fetch_with_filter("project", cj.parameters.cytomine_id_project)
images = [image for image in images if image.id in image_ids]
if hasattr(cj.parameters, "cytomine_id_users") and cj.parameters.cytomine_id_users is not None:
user_ids = [int(user_id) for user_id in cj.parameters.cytomine_id_users.split(",")]
else:
user_ids = []
if hasattr(cj.parameters, "cytomine_id_jobs") and cj.parameters.cytomine_id_jobs is not None:
job_ids = [int(job_id) for job_id in cj.parameters.cytomine_id_jobs.split(",")]
jobs = JobCollection(project=cj.parameters.cytomine_id_project).fetch()
jobs = [job for job in jobs if job.id in job_ids]
else:
jobs = []
userjobs_ids = [job.userJob for job in jobs]
all_user_ids = user_ids + userjobs_ids
cj.job.update(progress=20, statusComment="Collect data")
ac = AnnotationCollection()
ac.terms = term_ids
ac.images = image_ids
ac.showMeta = True
ac.showGIS = True
ac.showTerm = True
ac.reviewed = True if cj.parameters.cytomine_reviewed_only else None
ac.users = all_user_ids if len(all_user_ids) > 0 else None
ac.fetch()
cj.job.update(progress=55, statusComment="Compute statistics")
data = dict()
for image in images:
d = dict()
areas = [a.area for a in ac if a.image == image.id]
total_area = np.sum(areas)
d['total'] = total_area
d['count'] = len(areas)
d['ratio'] = 1.0
for term in terms:
annotations = [a for a in ac if a.image == image.id and term.id in a.term]
areas = [a.area for a in annotations]
d[term.name] = dict()
d[term.name]['total'] = np.sum(areas)
d[term.name]['count'] = len(annotations)
d[term.name]['ratio'] = d[term.name]['total'] / float(total_area) if total_area > 0 else 0
d[term.name]['mean'] = np.mean(areas)
d[term.name]['annotations'] = [{"created": a.created, "area": a.area} for a in annotations]
data[image.instanceFilename] = d
cj.job.update(progress=90, statusComment="Write CSV report")
with open("stat-area.csv", "w") as f:
for l in write_csv(data, terms):
f.write("{}\n".format(l))
job_data = JobData(id_job=cj.job.id, key="Area CSV report", filename="stat-area.csv")
job_data = job_data.save()
job_data.upload("stat-area.csv")
cj.job.update(statusComment="Finished.", progress=100)