diff --git a/face_recognition_cli.py b/face_recognition_cli.py
new file mode 100644
index 0000000..218a0fb
--- /dev/null
+++ b/face_recognition_cli.py
@@ -0,0 +1,119 @@
+# -*- coding: utf-8 -*-
+from __future__ import print_function
+import click
+import os
+import re
+import face_recognition.api as face_recognition
+import multiprocessing
+import itertools
+import sys
+import PIL.Image
+import numpy as np
+
+
+def scan_known_people(known_people_folder):
+    known_names = []
+    known_face_encodings = []
+
+    for file in image_files_in_folder(known_people_folder):
+        basename = os.path.splitext(os.path.basename(file))[0]
+        img = face_recognition.load_image_file(file)
+        encodings = face_recognition.face_encodings(img)
+
+        if len(encodings) > 1:
+            click.echo("WARNING: More than one face found in {}. Only considering the first face.".format(file))
+
+        if len(encodings) == 0:
+            click.echo("WARNING: No faces found in {}. Ignoring file.".format(file))
+        else:
+            known_names.append(basename)
+            known_face_encodings.append(encodings[0])
+
+    return known_names, known_face_encodings
+
+
+def print_result(filename, name, distance, show_distance=False):
+    if show_distance:
+        print("{},{},{}".format(filename, name, distance))
+    else:
+        print("{},{}".format(filename, name))
+
+
+def test_image(image_to_check, known_names, known_face_encodings, tolerance=0.6, show_distance=False):
+    unknown_image = face_recognition.load_image_file(image_to_check)
+
+    # Scale down image if it's giant so things run a little faster
+    if max(unknown_image.shape) > 1600:
+        pil_img = PIL.Image.fromarray(unknown_image)
+        pil_img.thumbnail((1600, 1600), PIL.Image.LANCZOS)
+        unknown_image = np.array(pil_img)
+
+    unknown_encodings = face_recognition.face_encodings(unknown_image)
+
+    for unknown_encoding in unknown_encodings:
+        distances = face_recognition.face_distance(known_face_encodings, unknown_encoding)
+        result = list(distances <= tolerance)
+
+        if True in result:
+            [print_result(image_to_check, name, distance, show_distance) for is_match, name, distance in zip(result, known_names, distances) if is_match]
+        else:
+            print_result(image_to_check, "unknown_person", None, show_distance)
+
+    if not unknown_encodings:
+        # print out fact that no faces were found in image
+        print_result(image_to_check, "no_persons_found", None, show_distance)
+
+
+def image_files_in_folder(folder):
+    return [os.path.join(folder, f) for f in os.listdir(folder) if re.match(r'.*\.(jpg|jpeg|png)', f, flags=re.I)]
+
+
+def process_images_in_process_pool(images_to_check, known_names, known_face_encodings, number_of_cpus, tolerance, show_distance):
+    if number_of_cpus == -1:
+        processes = None
+    else:
+        processes = number_of_cpus
+
+    # macOS will crash due to a bug in libdispatch if you don't use 'forkserver'
+    context = multiprocessing
+    if "forkserver" in multiprocessing.get_all_start_methods():
+        context = multiprocessing.get_context("forkserver")
+
+    pool = context.Pool(processes=processes)
+
+    function_parameters = zip(
+        images_to_check,
+        itertools.repeat(known_names),
+        itertools.repeat(known_face_encodings),
+        itertools.repeat(tolerance),
+        itertools.repeat(show_distance)
+    )
+
+    pool.starmap(test_image, function_parameters)
+
+
+@click.command()
+@click.argument('known_people_folder')
+@click.argument('image_to_check')
+@click.option('--cpus', default=1, help='number of CPU cores to use in parallel (can speed up processing lots of images). -1 means "use all in system"')
+@click.option('--tolerance', default=0.6, help='Tolerance for face comparisons. Default is 0.6. Lower this if you get multiple matches for the same person.')
+@click.option('--show-distance', default=False, type=bool, help='Output face distance. Useful for tweaking tolerance setting.')
+def main(known_people_folder, image_to_check, cpus, tolerance, show_distance):
+    known_names, known_face_encodings = scan_known_people(known_people_folder)
+
+    # Multi-core processing only supported on Python 3.4 or greater
+    if (sys.version_info < (3, 4)) and cpus != 1:
+        click.echo("WARNING: Multi-processing support requires Python 3.4 or greater. Falling back to single-threaded processing!")
+        cpus = 1
+
+    if os.path.isdir(image_to_check):
+        if cpus == 1:
+            [test_image(image_file, known_names, known_face_encodings, tolerance, show_distance) for image_file in image_files_in_folder(image_to_check)]
+        else:
+            process_images_in_process_pool(image_files_in_folder(image_to_check), known_names, known_face_encodings, cpus, tolerance, show_distance)
+    else:
+        test_image(image_to_check, known_names, known_face_encodings, tolerance, show_distance)
+
+
+if __name__ == "__main__":
+    main()