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Face Data Zoo

Database Version #Identity #Image #Frame #Video Download Link
LFW Raw 5,749 13,233 - - Google Drive, Baidu Drive
LFW Align_250x250 5,749 13,233 - - Google Drive, Baidu Drive
LFW Align_112x112 5,749 13,233 - - Google Drive, Baidu Drive
CALFW Raw 4,025 12,174 - - Google Drive, Baidu Drive
CALFW Align_112x112 4,025 12,174 - - Google Drive, Baidu Drive
CPLFW Raw 3,884 11,652 - - Google Drive, Baidu Drive
CPLFW Align_112x112 3,884 11,652 - - Google Drive, Baidu Drive
CASIA-WebFace Raw_v1 10,575 494,414 - - Baidu Drive
CASIA-WebFace Raw_v2 10,575 494,414 - - Google Drive, Baidu Drive
CASIA-WebFace Clean 10,575 455,594 - - Google Drive, Baidu Drive
MS-Celeb-1M Clean 100,000 5,084,127 - - Google Drive
MS-Celeb-1M Align_112x112 85,742 5,822,653 - - Google Drive
Vggface2 Clean 8,631 3,086,894 - - Google Drive
Vggface2_FP Align_112x112 - - - - Google Drive, Baidu Drive
AgeDB Raw 570 16,488 - - Google Drive, Baidu Drive
AgeDB Align_112x112 570 16,488 - - Google Drive, Baidu Drive
IJB-A Clean 500 5,396 20,369 2,085 Google Drive, Baidu Drive
IJB-B Raw 1,845 21,798 55,026 7,011 Google Drive
CFP Raw 500 7,000 - - Google Drive, Baidu Drive
CFP Align_112x112 500 7,000 - - Google Drive, Baidu Drive
Umdfaces Align_112x112 8,277 367,888 - - Google Drive, Baidu Drive
CelebA Raw 10,177 202,599 - - Google Drive, Baidu Drive
CACD-VS Raw 2,000 163,446 - - Google Drive, Baidu Drive
YTF Align_344x344 1,595 - 3,425 621,127 Google Drive, Baidu Drive
DeepGlint Align_112x112 180,855 6,753,545 - - Google Drive
UTKFace Align_200x200 - 23,708 - - Google Drive, Baidu Drive
  • Remark: unzip CASIA-WebFace clean version with
    unzip casia-maxpy-clean.zip    
    cd casia-maxpy-clean    
    zip -F CASIA-maxpy-clean.zip --out CASIA-maxpy-clean_fix.zip    
    unzip CASIA-maxpy-clean_fix.zip
    
  • Remark: after unzip, get image data & pair ground truths from AgeDB, CFP, LFW and VGGFace2_FP align_112x112 versions with
    import numpy as np
    import bcolz
    import os
    
    def get_pair(root, name):
        carray = bcolz.carray(rootdir = os.path.join(root, name), mode='r')
        issame = np.load('{}/{}_list.npy'.format(root, name))
        return carray, issame
    
    def get_data(data_root):
        agedb_30, agedb_30_issame = get_pair(data_root, 'agedb_30')
        cfp_fp, cfp_fp_issame = get_pair(data_root, 'cfp_fp')
        lfw, lfw_issame = get_pair(data_root, 'lfw')
        vgg2_fp, vgg2_fp_issame = get_pair(data_root, 'vgg2_fp')
        return agedb_30, cfp_fp, lfw, vgg2_fp, agedb_30_issame, cfp_fp_issame, lfw_issame, vgg2_fp_issame
    
    agedb_30, cfp_fp, lfw, vgg2_fp, agedb_30_issame, cfp_fp_issame, lfw_issame, vgg2_fp_issame = get_data(DATA_ROOT)
  • Remark: We share MS-Celeb-1M_Top1M_MID2Name.tsv (Google Drive, Baidu Drive), VGGface2_ID2Name.csv (Google Drive, Baidu Drive), VGGface2_FaceScrub_Overlap.txt (Google Drive, Baidu Drive), VGGface2_LFW_Overlap.txt (Google Drive, Baidu Drive), CASIA-WebFace_ID2Name.txt (Google Drive, Baidu Drive), CASIA-WebFace_FaceScrub_Overlap.txt (Google Drive, Baidu Drive), CASIA-WebFace_LFW_Overlap.txt (Google Drive, Baidu Drive), FaceScrub_Name.txt (Google Drive, Baidu Drive), LFW_Name.txt (Google Drive, Baidu Drive), LFW_Log.txt (Google Drive, Baidu Drive) to help researchers/engineers quickly remove the overlapping parts between their own private datasets and the public datasets.
  • Due to release license issue, for other face related databases, please make contact with us in person for more details.