.

1 files changed, 47 insertions, 0 deletions

diff --git a/megapixels/commands/cv/cluster.py b/megapixels/commands/cv/cluster.py
new file mode 100644
index 00000000..419091a0
--- /dev/null
+++ b/megapixels/commands/cv/cluster.py
@@ -0,0 +1,47 @@
+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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