mirror of
https://github.com/deepinsight/insightface.git
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41 lines
1.1 KiB
Python
41 lines
1.1 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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import sys
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import mxnet as mx
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from mxnet import ndarray as nd
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import random
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import argparse
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import cv2
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import time
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import sklearn
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from sklearn.decomposition import PCA
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from easydict import EasyDict as edict
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from sklearn.cluster import DBSCAN
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import numpy as np
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sys.path.append(os.path.join(os.path.dirname(__file__),'..', 'common'))
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import face_image
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def main(args):
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path_imgrec = os.path.join(args.input, 'train.rec')
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path_imgidx = os.path.join(args.input, 'train.idx')
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imgrec = mx.recordio.MXIndexedRecordIO(path_imgidx, path_imgrec, 'r') # pylint: disable=redefined-variable-type
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s = imgrec.read_idx(0)
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header, _ = mx.recordio.unpack(s)
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assert header.flag>0
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print('header0 label', header.label)
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header0 = (int(header.label[0]), int(header.label[1]))
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print('identities', header0[1]-header0[0])
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print('images', header0[0])
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='')
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# general
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parser.add_argument('--input', default='', type=str, help='')
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args = parser.parse_args()
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main(args)
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