diff --git a/dface/train_net/train.py b/dface/train_net/train.py index 129edd2..a2c2ac5 100644 --- a/dface/train_net/train.py +++ b/dface/train_net/train.py @@ -254,7 +254,7 @@ def train_onet(model_store_path, end_epoch,imdb, show4 = landmark_loss.data.tolist()[0] show5 = all_loss.data.tolist()[0] - print "%s : Epoch: %d, Step: %d, accuracy: %s, det loss: %s, bbox loss: %s, landmark loss: %s, all_loss: %s, lr:%s "%(datetime.datetime.now(),cur_epoch,batch_idx, show1,show2,show3,show4,show5,base_lr) + print("%s : Epoch: %d, Step: %d, accuracy: %s, det loss: %s, bbox loss: %s, landmark loss: %s, all_loss: %s, lr:%s "%(datetime.datetime.now(),cur_epoch,batch_idx, show1,show2,show3,show4,show5,base_lr)) accuracy_list.append(accuracy) cls_loss_list.append(cls_loss) bbox_loss_list.append(box_offset_loss) diff --git a/dface/train_net/train_o_net.py b/dface/train_net/train_o_net.py index 1e7c96c..51a31a8 100644 --- a/dface/train_net/train_o_net.py +++ b/dface/train_net/train_o_net.py @@ -43,7 +43,7 @@ def parse_args(): if __name__ == '__main__': args = parse_args() print('train ONet argument:') - print args + print(args) train_net(annotation_file=args.annotation_file, model_store_path=args.model_store_path, diff --git a/dface/train_net/train_p_net.py b/dface/train_net/train_p_net.py index 6e9f8a5..f13f876 100644 --- a/dface/train_net/train_p_net.py +++ b/dface/train_net/train_p_net.py @@ -43,7 +43,7 @@ def parse_args(): if __name__ == '__main__': args = parse_args() print('train Pnet argument:') - print args + print(args) train_net(annotation_file=args.annotation_file, model_store_path=args.model_store_path, end_epoch=args.end_epoch, frequent=args.frequent, lr=args.lr, batch_size=args.batch_size, use_cuda=args.use_cuda) diff --git a/dface/train_net/train_r_net.py b/dface/train_net/train_r_net.py index 97c5210..4424cd1 100644 --- a/dface/train_net/train_r_net.py +++ b/dface/train_net/train_r_net.py @@ -43,7 +43,7 @@ def parse_args(): if __name__ == '__main__': args = parse_args() print('train Rnet argument:') - print args + print(args) train_net(annotation_file=args.annotation_file, model_store_path=args.model_store_path,