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import click
from app.settings import types
from app.utils import click_utils
from app.settings import app_cfg as cfg
from app.utils.logger_utils import Logger
@click.command()
@click.option('--data_store', 'opt_data_store',
type=cfg.DataStoreVar,
default=click_utils.get_default(types.DataStore.NAS),
show_default=True,
help=click_utils.show_help(types.Dataset))
@click.option('--dataset', 'opt_dataset',
type=cfg.DatasetVar,
required=True,
show_default=True,
help=click_utils.show_help(types.Dataset))
@click.option('--metadata', 'opt_metadata', required=True,
type=cfg.MetadataVar,
show_default=True,
help=click_utils.show_help(types.Metadata))
@click.pass_context
def cli(ctx, opt_data_store, opt_dataset, opt_metadata):
"""Display image info"""
# cluster the embeddings
print("[INFO] clustering...")
clt = DBSCAN(metric="euclidean", n_jobs=args["jobs"])
clt.fit(encodings)
# determine the total number of unique faces found in the dataset
labelIDs = np.unique(clt.labels_)
numUniqueFaces = len(np.where(labelIDs > -1)[0])
print("[INFO] # unique faces: {}".format(numUniqueFaces))
# load and display image
im = cv.imread(fp_im)
cv.imshow('', im)
while True:
k = cv.waitKey(1) & 0xFF
if k == 27 or k == ord('q'): # ESC
cv.destroyAllWindows()
sys.exit()
elif k != 255:
# any key to continue
break
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