def test_catalog_from_classified():
"""Test the catalog_from_classified method."""
classified = dh.get_expected_morpheus_output()
h, _, _, _ = example.get_sample()
segmap = dh.get_expected_segmap()["segmap"]
expected_catalog = dh.get_expected_catalog()["catalog"]
actual_catalog = Classifier.catalog_from_classified(classified, h, segmap)
assert expected_catalog == actual_catalog
def main():
args = _parse_args(sys.argv[1:])
if args.action == "None":
Classifier.classify(
h=args.h,
j=args.j,
v=args.v,
z=args.z,
batch_size=args.batch_size,
out_dir=args.out_dir,
gpus=args.gpus,
cpus=args.cpus,
)
elif args.action == "catalog":
classified = Classifier.classify(
h=args.h,
j=args.j,
v=args.v,
z=args.z,
batch_size=args.batch_size,
out_dir=args.out_dir,
gpus=args.gpus,
cpus=args.cpus,
)
segmap = Classifier.segmap_from_classified(classified,
args.h,
out_dir=args.out_dir)
Classifier.catalog_from_classified(
classified,
args.h,
segmap,
out_file=os.path.join(args.out_dir, "colorized.png"),
)
elif args.action == "segmap":
classified = Classifier.classify(
h=args.h,
j=args.j,
v=args.v,
z=args.z,
batch_size=args.batch_size,
out_dir=args.out_dir,
gpus=args.gpus,
cpus=args.cpus,
)
Classifier.segmap_from_classified(classified,
args.h,
out_dir=args.out_dir)
elif args.action == "colorize":
classified = Classifier.classify(
h=args.h,
j=args.j,
v=args.v,
z=args.z,
batch_size=args.batch_size,
out_dir=args.out_dir,
gpus=args.gpus,
cpus=args.cpus,
)
Classifier.colorize_classified(classified, out_dir=args.out_dir)
elif args.action == "all":
classified = Classifier.classify(
h=args.h,
j=args.j,
v=args.v,
z=args.z,
batch_size=args.batch_size,
out_dir=args.out_dir,
gpus=args.gpus,
cpus=args.cpus,
)
segmap = Classifier.segmap_from_classified(classified,
args.h,
out_dir=args.out_dir)
Classifier.catalog_from_classified(
classified,
args.h,
segmap,
out_file=os.path.join(args.out_dir, "colorized.png"),
)
Classifier.colorize_classified(classified, out_dir=args.out_dir)
