fix

src/eval/verification.py

@@ -28,6 +28,7 @@ from __future__ import division
 from __future__ import print_function
 
 import os
+import argparse
 import numpy as np
 from scipy import misc
 from sklearn.model_selection import KFold
@@ -253,7 +254,7 @@ if __name__ == '__main__':
   parser.add_argument('--target', default='lfw,cfp_ff,cfp_fp', help='test targets.')
   parser.add_argument('--gpu', default=0, type=int, help='gpu id')
   parser.add_argument('--batch-size', default=128, type=int, help='')
-  args = parse_arguments(sys.argv[1:])
+  args = parser.parse_args()
 
   image_size = [int(x) for x in args.image_size.split(',')]
   ctx = mx.gpu(args.gpu)
@@ -263,6 +264,8 @@ if __name__ == '__main__':
     epoch = int(epoch)
     print('loading',prefix, epoch)
     model = mx.mod.Module.load(prefix, epoch, context = ctx)
+    model.bind(data_shapes=[('data', (args.batch_size, 3, image_size[0], image_size[1]))], label_shapes=[('softmax_label', (args.batch_size,))])
+    #model.init_params()
     nets.append(model)
 
   ver_list = []
@@ -270,7 +273,7 @@ if __name__ == '__main__':
   for name in args.target.split(','):
     path = os.path.join(args.data_dir,name+".bin")
     if os.path.exists(path):
-      print('ver', name)
+      print('loading.. ', name)
       data_set = load_bin(path, image_size)
       ver_list.append(data_set)
       ver_name_list.append(name)