needs full trained model

[dgai91]

Hi, due to the poor PC and GPU I can't train a full model using this param:

    parser = argparse.ArgumentParser()
    parser.add_argument('--train', type=str, default='./simple_train.py', help='Using which script to train.')
    parser.add_argument('--batch_size', type=int, default=32, help='Training Batch Size')
    parser.add_argument('--spatial_epochs', type=int, default=10, help='Epochs to train for Spatial Encoder')
    parser.add_argument('--temporal_epochs', type=int, default=40, help='Epochs to train for Temporal Encoder')
    parser.add_argument('--train_id', type=str, default="default_test", help='To name the weights of model')
    parser.add_argument('--dB', nargs="+", type=str, default='CASME2_Optical', help='Specify Database')
    parser.add_argument('--spatial_size', type=int, default=224, help='Size of image')
    parser.add_argument('--flag', type=str, default='st', help='Flags to control type of training')
    parser.add_argument('--objective_flag', type=int, default=1,
                        help='Flags to use either objective class or emotion class')
    parser.add_argument('--tensorboard', type=bool, default=False, help='tensorboard display')
    parser.add_argument('--root_db_path', type=str, default='E:/PycharmProjects/Micro-Expression-with-Deep-Learning-master/')
    args = parser.parse_args()
    print(args)

    main(args)

could you send me these weights which contains temporal_model, and VGG_model

[IcedDoggie]

I have, but thinking how to send to you because 20gb in size.

[dgai91]

This huge weight should be the CDE model. I just need single model which only contains optical and data_dim=4096, channel_flag=0

the structure of temporal_model is:

_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
lstm_1 (LSTM)                (None, 3000)             1678800   
_________________________________________________________________
dense_1 (Dense)              (None, 128)               12928     
_________________________________________________________________
dense_2 (Dense)              (None, 5)                 645       
=================================================================

[IcedDoggie]

Because each different fold has its own weight (cross validation), so in total there are 26 spatial and 26 temporal weights.

[dgai91]

oh, sorry I have forgotten this. could you send me the first sub weights?

[IcedDoggie]

weights for dige.rar https://drive.google.com/file/d/1Bf60k5EHfVbfPpUY7b0VrvFCz0MBzraL/view?usp=drive_web

-- Journey of thousand miles begins with a single step.

On Fri, 24 Aug 2018 at 15:01, Dige Ai notifications@github.com wrote:

oh, sorry I have forgotten this. could you send me the first sub weights?

— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/IcedDoggie/Micro-Expression-with-Deep-Learning/issues/14#issuecomment-415670737, or mute the thread https://github.com/notifications/unsubscribe-auth/AD-WkE58eu7-wup-KrZGNdUUxLjJ6ALXks5uT6TkgaJpZM4WIxyi .

[dgai91]

thank you very much