results on the LEVIR-CD

[process852]

Thank you very much for your excellent work，

I found that I could not achieve the expected results of the paper when reproducing the code results. May I ask if there are any issues with my reproduction process？

args = {
    'train_batch_size': 4,
    'val_batch_size': 4,
    'lr': 0.1,
    'epochs': 50,
    'gpu': True,
    'dev_id': 0,
    'multi_gpu': None,  #"0,1,2,3",
    'weight_decay': 5e-4,
    'momentum': 0.9,
    'print_freq': 50,
    'predict_step': 5,
    'crop_size': 512,
    'pred_dir': os.path.join(working_path, 'results', DATA_NAME),
    'chkpt_dir': os.path.join(working_path, 'checkpoints', DATA_NAME),
    'log_dir': os.path.join(working_path, 'logs', DATA_NAME, NET_NAME),
    'load_path': os.path.join(working_path, 'checkpoints', DATA_NAME, 'xxx.pth')}

python train_SAM_CD.py

• reproduce results:
  

• paper results
  

[sijie-Xu]

me too

[DingLei14]

me too

This are the results on the validation set. The results in the paper are obtained on the test set.
Please first run 'Pred_CD.py', then using the evaluation codes to obtain the metrics.

[sijie-Xu]

me too

This are the results on the validation set. The results in the paper are obtained on the test set. Please first run 'Pred_CD.py', then using the evaluation codes to obtain the metrics.