加载中 README.md +4 −4 原始行号 差异行号 差异行 加载中 @@ -8,19 +8,19 @@ SDFVAE is a robust and noisy-resilient anomaly detection method based on static ### Data preprocessing python data_preprocess.py --raw_data_file data/machine-1-1-data.csv --label_file data/machine-1-1-label.csv --train_data_path data_processed/machine-1-1-train --test_data_path data_processed/machine-1-1-test --test_start_time 20190923005800 **Please refer to "data_preprocessing_scripts.txt" for some details.** **Please refer to "data_preprocess/data_preprocessing_scripts.txt" for some details.** ### Training python trainer.py --dataset_path ../data_preprocess/data_processed/machine-1-1-train --data_nums 28253 --gpu_id 0 --log_path log_trainer/machine-1-1 --checkpoints_path model/machine-1-1 --n 38 **The detailed commands are given in "sdfvae_scripts.txt".** **The detailed commands are given in "sdfvae/sdfvae_scripts.txt".** ### Testing nohup python tester.py --dataset_path ../data_preprocess/data_processed/machine-1-1-test --data_nums 28469 --gpu_id 0 --log_path log_tester/machine-1-1 --checkpoints_path model/machine-1-1 --n 38 --start_epoch 30 2>&1 & **Refer to "sdfvae_scripts.txt" for details.** **Refer to "sdfvae/sdfvae_scripts.txt" for details.** ### Evaluation nohup python evaluation.py --llh_path log_tester/machine-1-1 --log_path log_evaluator/machine-1-1 --n 38 --start_epoch 30 2>&1 & **Please refer to "sdfvae_scripts.txt".** **Please refer to "sdfvae/sdfvae_scripts.txt".** ## Training Losses We give the example of SDFVAE training Losses on VoD1 dataset, the figure is in the directory named "training_losses". <br> 加载中 加载中
README.md +4 −4 原始行号 差异行号 差异行 加载中 @@ -8,19 +8,19 @@ SDFVAE is a robust and noisy-resilient anomaly detection method based on static ### Data preprocessing python data_preprocess.py --raw_data_file data/machine-1-1-data.csv --label_file data/machine-1-1-label.csv --train_data_path data_processed/machine-1-1-train --test_data_path data_processed/machine-1-1-test --test_start_time 20190923005800 **Please refer to "data_preprocessing_scripts.txt" for some details.** **Please refer to "data_preprocess/data_preprocessing_scripts.txt" for some details.** ### Training python trainer.py --dataset_path ../data_preprocess/data_processed/machine-1-1-train --data_nums 28253 --gpu_id 0 --log_path log_trainer/machine-1-1 --checkpoints_path model/machine-1-1 --n 38 **The detailed commands are given in "sdfvae_scripts.txt".** **The detailed commands are given in "sdfvae/sdfvae_scripts.txt".** ### Testing nohup python tester.py --dataset_path ../data_preprocess/data_processed/machine-1-1-test --data_nums 28469 --gpu_id 0 --log_path log_tester/machine-1-1 --checkpoints_path model/machine-1-1 --n 38 --start_epoch 30 2>&1 & **Refer to "sdfvae_scripts.txt" for details.** **Refer to "sdfvae/sdfvae_scripts.txt" for details.** ### Evaluation nohup python evaluation.py --llh_path log_tester/machine-1-1 --log_path log_evaluator/machine-1-1 --n 38 --start_epoch 30 2>&1 & **Please refer to "sdfvae_scripts.txt".** **Please refer to "sdfvae/sdfvae_scripts.txt".** ## Training Losses We give the example of SDFVAE training Losses on VoD1 dataset, the figure is in the directory named "training_losses". <br> 加载中