gen_wts.py

import struct
import sys
import argparse
import face_model
import cv2
import numpy as np

parser = argparse.ArgumentParser(description='face model test')
# general
parser.add_argument('--image-size', default='112,112', help='')
parser.add_argument('--model', default='model-r100-ii/model,0', help='path to load model.')
parser.add_argument('--ga-model', default='', help='path to load model.')
parser.add_argument('--gpu', default=0, type=int, help='gpu id')
parser.add_argument('--det', default=0, type=int, help='mtcnn option, 1 means using R+O, 0 means detect from begining')
parser.add_argument('--flip', default=0, type=int, help='whether do lr flip aug')
parser.add_argument('--threshold', default=1.24, type=float, help='ver dist threshold')
args = parser.parse_args()

model = face_model.FaceModel(args)

f = open('arcface-r100.wts', 'w')
f.write('{}\n'.format(len(model.model.get_params()[0].keys()) + len(model.model.get_params()[1].keys())))
for k, v in model.model.get_params()[0].items():
    vr = v.reshape(-1).asnumpy()
    f.write('{} {} '.format(k, len(vr)))
    for vv in vr:
        f.write(' ')
        f.write(struct.pack('>f',float(vv)).hex())
    f.write('\n')
for k, v in model.model.get_params()[1].items():
    vr = v.reshape(-1).asnumpy()
    f.write('{} {} '.format(k, len(vr)))
    for vv in vr:
        f.write(' ')
        f.write(struct.pack('>f',float(vv)).hex())
    f.write('\n')