Micro-Expression-with-Deep-Learning
Micro-Expression-with-Deep-Learning copied to clipboard
IcedDoggie
needs full trained model
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
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
=================================================================
Because each different fold has its own weight (cross validation), so in total there are 26 spatial and 26 temporal weights.
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 [email protected] 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 .