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73 lines
2.5 KiB
73 lines
2.5 KiB
# -*- coding: utf-8 -*-
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from __future__ import print_function
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import click
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import os
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import re
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import face_recognition.api as face_recognition
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import multiprocessing
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import sys
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import itertools
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def print_result(filename, location):
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top, right, bottom, left = location
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print("{},{},{},{},{}".format(filename, top, right, bottom, left))
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def test_image(image_to_check, model, upsample):
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unknown_image = face_recognition.load_image_file(image_to_check)
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face_locations = face_recognition.face_locations(unknown_image, number_of_times_to_upsample=upsample, model=model)
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for face_location in face_locations:
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print_result(image_to_check, face_location)
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def image_files_in_folder(folder):
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return [os.path.join(folder, f) for f in os.listdir(folder) if re.match(r'.*\.(jpg|jpeg|png)', f, flags=re.I)]
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def process_images_in_process_pool(images_to_check, number_of_cpus, model, upsample):
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if number_of_cpus == -1:
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processes = None
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else:
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processes = number_of_cpus
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# macOS will crash due to a bug in libdispatch if you don't use 'forkserver'
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context = multiprocessing
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if "forkserver" in multiprocessing.get_all_start_methods():
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context = multiprocessing.get_context("forkserver")
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pool = context.Pool(processes=processes)
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function_parameters = zip(
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images_to_check,
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itertools.repeat(model),
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itertools.repeat(upsample),
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)
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pool.starmap(test_image, function_parameters)
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@click.command()
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@click.argument('image_to_check')
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@click.option('--cpus', default=1, help='number of CPU cores to use in parallel. -1 means "use all in system"')
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@click.option('--model', default="hog", help='Which face detection model to use. Options are "hog" or "cnn".')
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@click.option('--upsample', default=0, help='How many times to upsample the image looking for faces. Higher numbers find smaller faces.')
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def main(image_to_check, cpus, model, upsample):
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# Multi-core processing only supported on Python 3.4 or greater
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if (sys.version_info < (3, 4)) and cpus != 1:
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click.echo("WARNING: Multi-processing support requires Python 3.4 or greater. Falling back to single-threaded processing!")
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cpus = 1
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if os.path.isdir(image_to_check):
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if cpus == 1:
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[test_image(image_file, model, upsample) for image_file in image_files_in_folder(image_to_check)]
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else:
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process_images_in_process_pool(image_files_in_folder(image_to_check), cpus, model, upsample)
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else:
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test_image(image_to_check, model, upsample)
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if __name__ == "__main__":
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main()
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