From 25d1bea718d1acec0350760589a101ac93483a6b Mon Sep 17 00:00:00 2001 From: pfzpyac3f <344492480@qq.com> Date: Sat, 17 Dec 2022 09:36:49 +0800 Subject: [PATCH] ADD file via upload --- face_recognition_cli.py | 119 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 119 insertions(+) create mode 100644 face_recognition_cli.py 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()