can you provide some hyper params in cvprw2020 single-model challenge?

[hust-kevin]

    parser = argparse.ArgumentParser(description="save quality using landmarkpose model")
    parser.add_argument('--gpu', type=int, default=3, help='the gpu id used for predict')
    parser.add_argument('--lr', type=float, default=0.00008, help='initial learning rate')  #default=0.0001
    parser.add_argument('--batchsize', type=int, default=9, help='initial batchsize')  #default=7  
    parser.add_argument('--step_size', type=int, default=20, help='how many epochs lr decays once')  # 500  | DPC = 400
    parser.add_argument('--gamma', type=float, default=0.5, help='gamma of optim.lr_scheduler.StepLR, decay of lr')
    parser.add_argument('--echo_batches', type=int, default=50, help='how many batches display once')  # 50
    parser.add_argument('--epochs', type=int, default=60, help='total training epochs')
    parser.add_argument('--log', type=str, default="CDCNpp_BinaryMask_P1_07", help='log and save model name')
    parser.add_argument('--finetune', action='store_true', default=False, help='whether finetune other models')
    parser.add_argument('--theta', type=float, default=0.7, help='hyper-parameters in CDCNpp')

according you parser, total epoch is 60 , lr is 8e-5 and bs is 9?

[ZitongYu]

You can try 'total epoch is 50, lr is 1e-4 and bs is 10'. I think the hyperparameters influence slightly.

[punitha-valli]

@ZitongYu @hust-kevin can you please explain to me about the map_dir, and the oulu_npu dataset has video, but as per the source code Train-images, Dev_images, Test_images are required. Can you please explain it to me?

I am also a student, so it will be greatly helpful for me to do my research work.

thanks in advance