| --- |
| tags: |
| - seismic |
| - blending-noise |
| - deblending |
| - unet |
| - resunet |
| - dncnn |
| - attention-unet |
| - pytorch |
| library_name: pytorch |
| --- |
| |
| # Blending Noise Suppression Benchmark |
|
|
| This task performs supervised deblending on paired common-receiver gathers. |
|
|
| ## Task |
|
|
| The model directly learns a mapping from pseudo-deblended input to the cleaner forwarding reference: |
|
|
| ```python |
| denoised = model(pseudo_deblended_input) |
| ``` |
|
|
| This is a paired regression task, not a synthetic noise injection task. |
|
|
| ## Dataset |
|
|
| Current paired SEG-Y inputs: |
|
|
| - input: `/root/Desktop/data/T02_pseudo_deblended_common_receiver_mod.sgy` |
| - target: `/root/Desktop/data/T02_forwarding_acoustic_common_receiver.sgy` |
|
|
| Logical volume shape: |
|
|
| - `(386, 270, 2000)` |
| - 386 common-receiver gathers |
| - 270 traces per common-receiver gather |
| - 2000 time samples per trace |
|
|
| Split policy: |
|
|
| - sequential receiver-gather split |
| - train: 300 |
| - val: 43 |
| - test: 43 |
|
|
| ## Models |
|
|
| - `unet` |
| - `res_unet` |
| - `dncnn` |
| - `atten_unet` |
|
|
| All model definitions are loaded from `model/blending_noise_suppression/`. |
|
|
| ## Preprocessing |
|
|
| - paired loading with shape consistency check |
| - shared normalization statistics for input and target |
| - overlapping 2D patches of size `128 x 256` |
| - overlap ratio `0.5` |
|
|
| ## Scripts |
|
|
| Training: |
|
|
| - `bash scripts/blending_noise_suppression/train_denoise_unet.sh` |
| - `bash scripts/blending_noise_suppression/train_denoise_res_unet.sh` |
| - `bash scripts/blending_noise_suppression/train_denoise_dncnn.sh` |
| - `bash scripts/blending_noise_suppression/train_denoise_atten_unet.sh` |
|
|
| Each training script now runs a fixed three-seed sweep: |
|
|
| - seeds: `42`, `43`, `44` |
| - run names: `<experiment.name>_<dataset_id>_<noise_tag>_seed<seed>` |
| For the current input file `T02_pseudo_deblended_common_receiver_mod.sgy`, this becomes `..._T02_mod_seed<seed>`. |
| - checkpoints: `/root/Desktop/data/results/blending_noise_suppression/<model>/<run_name>/checkpoints/` |
|
|
| Inference: |
|
|
| - `bash scripts/blending_noise_suppression/inference_denoise_unet.sh` |
| - `bash scripts/blending_noise_suppression/inference_denoise_res_unet.sh` |
| - `bash scripts/blending_noise_suppression/inference_denoise_dncnn.sh` |
| - `bash scripts/blending_noise_suppression/inference_denoise_atten_unet.sh` |
|
|
| Each inference script matches the same three seeds, writes per-seed outputs to: |
|
|
| - `/root/Desktop/data/results/blending_noise_suppression/<model>/<run_name>/inference` |
|
|
| and also saves a cross-seed aggregate summary to: |
|
|
| - `/root/Desktop/data/results/blending_noise_suppression/<model>/<experiment.name>_<dataset_id>_<noise_tag>_seed_stats/metrics_summary_mean_std.json` |
|
|
| Run all: |
|
|
| - `bash scripts/blending_noise_suppression/run_all_blending_models.sh` |
|
|
| ## Upload |
|
|
| Dataset upload helpers in this folder are: |
|
|
| - `bash scripts/blending_noise_suppression/upload_dataset_to_hf.sh` |
|
|
| This uploads: |
|
|
| - `input/T02_pseudo_deblended_common_receiver_mod.sgy` |
| - `target/T02_forwarding_acoustic_common_receiver.sgy` |
| - `assets/deblending/*.png` from `scripts/blending_noise_suppression/assets/` |
| - generated dataset card `README.md` |
|
|
| The current shell wrappers follow the same style as the random-noise uploader: |
|
|
| - edit the fixed options directly inside the `.sh` file |
| - then run the shell script |
|
|
| Model upload helper in this folder: |
|
|
| - `bash scripts/blending_noise_suppression/upload_blending_model_to_hf.sh` |
|
|
| This uploads: |
|
|
| - `models/<model>/<dataset_variant>_seed<seed>/best.pt` |
| - `models/<model>/<dataset_variant>_seed<seed>/config.yaml` |
| - generated model card `README.md` |
|
|
| ## Outputs |
|
|
| Each inference directory contains: |
|
|
| - `metrics_per_gather.csv` |
| - `metrics_per_sample.csv` |
| - `metrics_summary.json` |
| - `visualizations/` |
| - optional `npy/` |
|
|
| Inference defaults aligned with the random-noise workflow: |
|
|
| - `n_viz_gathers: 5` |
| - `save_npy: false` |
| - per-model inference `batch_size` matches the corresponding training config |
|
|
| Metrics are reported for: |
|
|
| - input vs target |
| - denoised vs target |
| - delta = denoised minus input |
|
|
| For naming consistency with the random-noise workflow: |
|
|
| - `metrics_summary.json` uses `input`, `denoised`, and `delta` |
| - the file also keeps a backward-compatible `restored` alias |
| - `metrics_per_sample.csv` provides a generic sample-level view, while `metrics_per_gather.csv` keeps the correct gather-specific naming |
|
|
| <!-- AUTO_RESULTS_BEGIN --> |
| ## Results |
|
|
| Mean +- std over available seeds, computed from `*_seed_stats/metrics_summary_mean_std.json`. |
| Metrics are reported on common-receiver gathers in the normalized domain. |
|
|
| ### Dataset Variant `T02_comp` |
| |
| | Method | Parameters (M) | SNR | PSNR | SSIM | MAE | MSE | RMSE | EB_WSE_MEDIUM_40_70_NE | EB_WSE_MEDIUM_40_70_SNR | EB_WSE_STRONG_70_100_NE | EB_WSE_STRONG_70_100_SNR | EB_WSE_VERY_WEAK_5_20_NE | EB_WSE_VERY_WEAK_5_20_SNR | EB_WSE_WEAK_20_40_NE | EB_WSE_WEAK_20_40_SNR | FB_FRE_HIGH_ENERGY_RATIO | FB_FRE_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_HIGH_NE | FB_FRE_HIGH_SNR | FB_FRE_LOW_ENERGY_RATIO | FB_FRE_LOW_FREQUENCY_RANGE_HZ | FB_FRE_LOW_NE | FB_FRE_LOW_SNR | FB_FRE_MID_ENERGY_RATIO | FB_FRE_MID_FREQUENCY_RANGE_HZ | FB_FRE_MID_NE | FB_FRE_MID_SNR | FB_FRE_VERY_HIGH_ENERGY_RATIO | FB_FRE_VERY_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_VERY_HIGH_NE | FB_FRE_VERY_HIGH_SNR | |
| |---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| |
| | Input | - | 1.1666+-0.0000 | 24.1733+-0.0000 | 0.6475+-0.0000 | 0.020175+-0.000000 | 0.003923+-0.000000 | 0.062252+-0.000000 | 2.424931+-0.000000 | -7.5937+-0.0000 | 0.354534+-0.000000 | 9.0088+-0.0000 | 41.080699+-0.000000 | -32.1112+-0.0000 | 13.037582+-0.000000 | -22.1041+-0.0000 | 0.243824+-0.000000 | 28.75-41.8 | 0.873002+-0.000000 | 1.1802+-0.0000 | 0.023417+-0.000000 | 7-15.7 | 0.898679+-0.000000 | 0.9282+-0.0000 | 0.619438+-0.000000 | 15.7-28.75 | 0.871390+-0.000000 | 1.1961+-0.0000 | 0.006539+-0.000000 | 41.8-50.5 | 0.900242+-0.000000 | 0.9140+-0.0000 | |
| | UNet | 7.76 | 13.7153+-0.0285 | 36.7220+-0.0286 | 0.9659+-0.0011 | 0.005862+-0.000223 | 0.000217+-0.000001 | 0.014654+-0.000046 | 0.548360+-0.013994 | 5.2264+-0.2239 | 0.187143+-0.000813 | 14.5646+-0.0368 | 2.023152+-0.118065 | -6.0304+-0.5009 | 1.022692+-0.006941 | -0.1832+-0.0606 | 0.243824+-0.000000 | 28.75-41.8 | 0.191022+-0.000523 | 14.3887+-0.0221 | 0.023417+-0.000000 | 7-15.7 | 0.310998+-0.004445 | 10.1490+-0.1246 | 0.619438+-0.000000 | 15.7-28.75 | 0.195605+-0.001797 | 14.1894+-0.0790 | 0.006539+-0.000000 | 41.8-50.5 | 0.354464+-0.016425 | 9.0312+-0.3973 | |
| | DnCNN | 0.56 | 15.9093+-0.0329 | 38.9159+-0.0329 | 0.9747+-0.0005 | 0.004189+-0.000073 | 0.000131+-0.000001 | 0.011382+-0.000043 | 0.398803+-0.003495 | 7.9922+-0.0759 | 0.143179+-0.001064 | 16.8937+-0.0645 | 1.973087+-0.099471 | -5.8083+-0.4441 | 0.804399+-0.021533 | 1.9187+-0.2312 | 0.243824+-0.000000 | 28.75-41.8 | 0.149839+-0.001259 | 16.5090+-0.0723 | 0.023417+-0.000000 | 7-15.7 | 0.312591+-0.005099 | 10.1085+-0.1418 | 0.619438+-0.000000 | 15.7-28.75 | 0.143503+-0.000822 | 16.8827+-0.0485 | 0.006539+-0.000000 | 41.8-50.5 | 0.337944+-0.004222 | 9.4342+-0.1109 | |
| | ResUNet | 8.11 | 13.0502+-0.0999 | 36.0568+-0.0999 | 0.9630+-0.0007 | 0.005982+-0.000151 | 0.000253+-0.000006 | 0.015824+-0.000182 | 0.580493+-0.004514 | 4.7277+-0.0675 | 0.202740+-0.001825 | 13.8691+-0.0791 | 2.196548+-0.210000 | -6.7265+-0.8433 | 0.993230+-0.044053 | 0.0782+-0.3850 | 0.243824+-0.000000 | 28.75-41.8 | 0.203625+-0.003579 | 13.8350+-0.1530 | 0.023417+-0.000000 | 7-15.7 | 0.323164+-0.002858 | 9.8146+-0.0767 | 0.619438+-0.000000 | 15.7-28.75 | 0.215460+-0.001770 | 13.3486+-0.0718 | 0.006539+-0.000000 | 41.8-50.5 | 0.331564+-0.004233 | 9.6056+-0.1129 | |
| | Attention UNet | 7.85 | 13.4453+-0.1919 | 36.4519+-0.1918 | 0.9651+-0.0010 | 0.005995+-0.000201 | 0.000230+-0.000010 | 0.015111+-0.000333 | 0.550504+-0.008220 | 5.1888+-0.1297 | 0.194943+-0.004859 | 14.2127+-0.2146 | 1.883427+-0.132940 | -5.4135+-0.5909 | 0.968391+-0.028346 | 0.2907+-0.2566 | 0.243824+-0.000000 | 28.75-41.8 | 0.196462+-0.003245 | 14.1463+-0.1433 | 0.023417+-0.000000 | 7-15.7 | 0.317140+-0.003001 | 9.9775+-0.0823 | 0.619438+-0.000000 | 15.7-28.75 | 0.200722+-0.003868 | 13.9657+-0.1676 | 0.006539+-0.000000 | 41.8-50.5 | 0.376004+-0.009141 | 8.5124+-0.2100 | |
| |
| ### Dataset Variant `T02_mod` |
|
|
| | Method | Parameters (M) | SNR | PSNR | SSIM | MAE | MSE | RMSE | EB_WSE_MEDIUM_40_70_NE | EB_WSE_MEDIUM_40_70_SNR | EB_WSE_STRONG_70_100_NE | EB_WSE_STRONG_70_100_SNR | EB_WSE_VERY_WEAK_5_20_NE | EB_WSE_VERY_WEAK_5_20_SNR | EB_WSE_WEAK_20_40_NE | EB_WSE_WEAK_20_40_SNR | FB_FRE_HIGH_ENERGY_RATIO | FB_FRE_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_HIGH_NE | FB_FRE_HIGH_SNR | FB_FRE_LOW_ENERGY_RATIO | FB_FRE_LOW_FREQUENCY_RANGE_HZ | FB_FRE_LOW_NE | FB_FRE_LOW_SNR | FB_FRE_MID_ENERGY_RATIO | FB_FRE_MID_FREQUENCY_RANGE_HZ | FB_FRE_MID_NE | FB_FRE_MID_SNR | FB_FRE_VERY_HIGH_ENERGY_RATIO | FB_FRE_VERY_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_VERY_HIGH_NE | FB_FRE_VERY_HIGH_SNR | |
| |---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| |
| | Input | - | 3.3315+-0.0000 | 26.6881+-0.0000 | 0.7654+-0.0000 | 0.012160+-0.000000 | 0.002216+-0.000000 | 0.046691+-0.000000 | 1.812672+-0.000000 | -5.0296+-0.0000 | 0.291407+-0.000000 | 10.7119+-0.0000 | 32.195003+-0.000000 | -30.0783+-0.0000 | 10.154543+-0.000000 | -19.9091+-0.0000 | 0.243824+-0.000000 | 28.75-41.8 | 0.683361+-0.000000 | 3.3090+-0.0000 | 0.023417+-0.000000 | 7-15.7 | 0.695802+-0.000000 | 3.1510+-0.0000 | 0.619438+-0.000000 | 15.7-28.75 | 0.678645+-0.000000 | 3.3687+-0.0000 | 0.006539+-0.000000 | 41.8-50.5 | 0.689609+-0.000000 | 3.2288+-0.0000 | |
| | UNet | 7.76 | 14.7039+-0.2431 | 38.0605+-0.2431 | 0.9748+-0.0005 | 0.004650+-0.000281 | 0.000164+-0.000009 | 0.012648+-0.000360 | 0.473852+-0.018317 | 6.5041+-0.3309 | 0.167761+-0.005444 | 15.5276+-0.2822 | 2.123491+-0.119411 | -6.5083+-0.4739 | 0.907897+-0.009668 | 0.8630+-0.0887 | 0.243824+-0.000000 | 28.75-41.8 | 0.168928+-0.004161 | 15.4765+-0.2150 | 0.023417+-0.000000 | 7-15.7 | 0.270377+-0.001948 | 11.3674+-0.0602 | 0.619438+-0.000000 | 15.7-28.75 | 0.177198+-0.010899 | 15.0684+-0.5435 | 0.006539+-0.000000 | 41.8-50.5 | 0.314485+-0.026862 | 10.0991+-0.7195 | |
| | DnCNN | 0.56 | 17.4002+-0.0460 | 40.7567+-0.0460 | 0.9847+-0.0002 | 0.002816+-0.000052 | 0.000088+-0.000001 | 0.009280+-0.000054 | 0.317468+-0.002446 | 9.9740+-0.0672 | 0.123480+-0.000698 | 18.1918+-0.0488 | 1.908495+-0.075431 | -5.5801+-0.3437 | 0.699431+-0.018116 | 3.1511+-0.2222 | 0.243824+-0.000000 | 28.75-41.8 | 0.127505+-0.000947 | 17.9398+-0.0564 | 0.023417+-0.000000 | 7-15.7 | 0.268126+-0.002124 | 11.4418+-0.0681 | 0.619438+-0.000000 | 15.7-28.75 | 0.119451+-0.000877 | 18.4804+-0.0641 | 0.006539+-0.000000 | 41.8-50.5 | 0.295901+-0.003349 | 10.5996+-0.0971 | |
| | ResUNet | 8.11 | 14.1138+-0.0794 | 37.4704+-0.0794 | 0.9749+-0.0005 | 0.004629+-0.000126 | 0.000187+-0.000004 | 0.013524+-0.000125 | 0.486774+-0.004043 | 6.2610+-0.0725 | 0.181058+-0.001342 | 14.8585+-0.0644 | 2.130174+-0.187739 | -6.5089+-0.7907 | 0.872875+-0.023638 | 1.2102+-0.2271 | 0.243824+-0.000000 | 28.75-41.8 | 0.180487+-0.003511 | 14.8949+-0.1682 | 0.023417+-0.000000 | 7-15.7 | 0.270266+-0.001293 | 11.3680+-0.0415 | 0.619438+-0.000000 | 15.7-28.75 | 0.192449+-0.001287 | 14.3336+-0.0586 | 0.006539+-0.000000 | 41.8-50.5 | 0.290352+-0.006327 | 10.7610+-0.1905 | |
| | Attention UNet | 7.85 | 14.5616+-0.1395 | 37.9182+-0.1395 | 0.9749+-0.0004 | 0.004868+-0.000111 | 0.000168+-0.000005 | 0.012843+-0.000208 | 0.455199+-0.003818 | 6.8466+-0.0745 | 0.172010+-0.003499 | 15.3022+-0.1770 | 2.171944+-0.038920 | -6.7162+-0.1614 | 0.884095+-0.010330 | 1.1019+-0.0963 | 0.243824+-0.000000 | 28.75-41.8 | 0.174245+-0.003430 | 15.1990+-0.1717 | 0.023417+-0.000000 | 7-15.7 | 0.270073+-0.005210 | 11.3789+-0.1665 | 0.619438+-0.000000 | 15.7-28.75 | 0.176185+-0.003015 | 15.0971+-0.1458 | 0.006539+-0.000000 | 41.8-50.5 | 0.334154+-0.012100 | 9.5456+-0.3116 | |
|
|
| ### Dataset Variant `T02_simp` |
| |
| | Method | Parameters (M) | SNR | PSNR | SSIM | MAE | MSE | RMSE | EB_WSE_MEDIUM_40_70_NE | EB_WSE_MEDIUM_40_70_SNR | EB_WSE_STRONG_70_100_NE | EB_WSE_STRONG_70_100_SNR | EB_WSE_VERY_WEAK_5_20_NE | EB_WSE_VERY_WEAK_5_20_SNR | EB_WSE_WEAK_20_40_NE | EB_WSE_WEAK_20_40_SNR | FB_FRE_HIGH_ENERGY_RATIO | FB_FRE_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_HIGH_NE | FB_FRE_HIGH_SNR | FB_FRE_LOW_ENERGY_RATIO | FB_FRE_LOW_FREQUENCY_RANGE_HZ | FB_FRE_LOW_NE | FB_FRE_LOW_SNR | FB_FRE_MID_ENERGY_RATIO | FB_FRE_MID_FREQUENCY_RANGE_HZ | FB_FRE_MID_NE | FB_FRE_MID_SNR | FB_FRE_VERY_HIGH_ENERGY_RATIO | FB_FRE_VERY_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_VERY_HIGH_NE | FB_FRE_VERY_HIGH_SNR | |
| |---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| |
| | Input | - | 6.6896+-0.0000 | 29.5209+-0.0000 | 0.8797+-0.0000 | 0.006035+-0.000000 | 0.001162+-0.000000 | 0.033769+-0.000000 | 1.359040+-0.000000 | -2.5295+-0.0000 | 0.218058+-0.000000 | 13.2445+-0.0000 | 18.050747+-0.000000 | -24.8266+-0.0000 | 5.957535+-0.000000 | -15.2400+-0.0000 | 0.243824+-0.000000 | 28.75-41.8 | 0.465783+-0.000000 | 6.6411+-0.0000 | 0.023417+-0.000000 | 7-15.7 | 0.478424+-0.000000 | 6.4075+-0.0000 | 0.619438+-0.000000 | 15.7-28.75 | 0.461325+-0.000000 | 6.7222+-0.0000 | 0.006539+-0.000000 | 41.8-50.5 | 0.470025+-0.000000 | 6.5676+-0.0000 | |
| | UNet | 7.76 | 17.0387+-0.2113 | 39.8701+-0.2112 | 0.9844+-0.0008 | 0.003486+-0.000332 | 0.000108+-0.000005 | 0.010272+-0.000247 | 0.365571+-0.003555 | 8.7478+-0.0849 | 0.127483+-0.003382 | 17.9170+-0.2360 | 1.415779+-0.097544 | -2.9125+-0.5822 | 0.652592+-0.002307 | 3.7166+-0.0316 | 0.243824+-0.000000 | 28.75-41.8 | 0.124367+-0.002468 | 18.1415+-0.1829 | 0.023417+-0.000000 | 7-15.7 | 0.215077+-0.010455 | 13.3626+-0.4145 | 0.619438+-0.000000 | 15.7-28.75 | 0.133467+-0.001234 | 17.5222+-0.0794 | 0.006539+-0.000000 | 41.8-50.5 | 0.251275+-0.022851 | 12.0500+-0.7735 | |
| | DnCNN | 0.56 | 20.4091+-0.0326 | 43.2404+-0.0326 | 0.9925+-0.0000 | 0.001532+-0.000031 | 0.000049+-0.000000 | 0.006957+-0.000029 | 0.222201+-0.001296 | 13.0774+-0.0526 | 0.088844+-0.000339 | 21.0477+-0.0335 | 0.898625+-0.021335 | 1.0318+-0.2143 | 0.406727+-0.002426 | 7.8283+-0.0523 | 0.243824+-0.000000 | 28.75-41.8 | 0.086655+-0.000918 | 21.2753+-0.0958 | 0.023417+-0.000000 | 7-15.7 | 0.188400+-0.003696 | 14.5150+-0.1741 | 0.619438+-0.000000 | 15.7-28.75 | 0.086650+-0.000717 | 21.2743+-0.0735 | 0.006539+-0.000000 | 41.8-50.5 | 0.202190+-0.000115 | 13.8956+-0.0046 | |
| | ResUNet | 8.11 | 16.5535+-0.1634 | 39.3848+-0.1634 | 0.9847+-0.0004 | 0.003306+-0.000134 | 0.000121+-0.000004 | 0.010861+-0.000203 | 0.382057+-0.009326 | 8.3679+-0.2092 | 0.136025+-0.002203 | 17.3502+-0.1454 | 1.356662+-0.063744 | -2.5668+-0.3877 | 0.618934+-0.018298 | 4.1788+-0.2558 | 0.243824+-0.000000 | 28.75-41.8 | 0.131448+-0.003584 | 17.6564+-0.2426 | 0.023417+-0.000000 | 7-15.7 | 0.211059+-0.001684 | 13.5171+-0.0696 | 0.619438+-0.000000 | 15.7-28.75 | 0.144846+-0.002013 | 16.8097+-0.1269 | 0.006539+-0.000000 | 41.8-50.5 | 0.222782+-0.007011 | 13.0636+-0.2739 | |
| | Attention UNet | 7.85 | 16.6680+-0.1592 | 39.4993+-0.1592 | 0.9831+-0.0005 | 0.003818+-0.000183 | 0.000117+-0.000004 | 0.010712+-0.000193 | 0.345422+-0.001738 | 9.2426+-0.0445 | 0.132686+-0.002938 | 17.5634+-0.1929 | 1.558382+-0.103877 | -3.7426+-0.5584 | 0.655009+-0.031865 | 3.7075+-0.4077 | 0.243824+-0.000000 | 28.75-41.8 | 0.129747+-0.002258 | 17.7680+-0.1561 | 0.023417+-0.000000 | 7-15.7 | 0.227748+-0.006546 | 12.8649+-0.2507 | 0.619438+-0.000000 | 15.7-28.75 | 0.136028+-0.000966 | 17.3499+-0.0621 | 0.006539+-0.000000 | 41.8-50.5 | 0.282750+-0.011078 | 10.9940+-0.3458 | |
| |
| <!-- AUTO_RESULTS_DATA_BEGIN |
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| "mean": 0.006539, |
| "std": 0.0 |
| }, |
| "fb_fre_very_high_frequency_range_hz": [ |
| 41.8, |
| 50.5 |
| ], |
| "fb_fre_very_high_ne": { |
| "mean": 0.314485, |
| "std": 0.026862 |
| }, |
| "fb_fre_very_high_snr": { |
| "mean": 10.099075, |
| "std": 0.7195 |
| }, |
| "mae": { |
| "mean": 0.00465, |
| "std": 0.000281 |
| }, |
| "mse": { |
| "mean": 0.000164, |
| "std": 9e-06 |
| }, |
| "psnr": { |
| "mean": 38.0605, |
| "std": 0.243101 |
| }, |
| "rmse": { |
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| "std": 0.00036 |
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| "snr": { |
| "mean": 14.703933, |
| "std": 0.243086 |
| }, |
| "ssim": { |
| "mean": 0.974833, |
| "std": 0.000544 |
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| "dncnn": { |
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| "mean": 0.317468, |
| "std": 0.002446 |
| }, |
| "eb_wse_medium_40_70_snr": { |
| "mean": 9.97396, |
| "std": 0.067157 |
| }, |
| "eb_wse_strong_70_100_ne": { |
| "mean": 0.12348, |
| "std": 0.000698 |
| }, |
| "eb_wse_strong_70_100_snr": { |
| "mean": 18.191807, |
| "std": 0.048781 |
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| "eb_wse_very_weak_5_20_ne": { |
| "mean": 1.908495, |
| "std": 0.075431 |
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| "eb_wse_very_weak_5_20_snr": { |
| "mean": -5.580064, |
| "std": 0.343691 |
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| "eb_wse_weak_20_40_ne": { |
| "mean": 0.699431, |
| "std": 0.018116 |
| }, |
| "eb_wse_weak_20_40_snr": { |
| "mean": 3.151053, |
| "std": 0.22222 |
| }, |
| "fb_fre_high_energy_ratio": { |
| "mean": 0.243824, |
| "std": 0.0 |
| }, |
| "fb_fre_high_frequency_range_hz": [ |
| 28.75, |
| 41.8 |
| ], |
| "fb_fre_high_ne": { |
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| "std": 0.000947 |
| }, |
| "fb_fre_high_snr": { |
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| "std": 0.056444 |
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| "fb_fre_low_energy_ratio": { |
| "mean": 0.023417, |
| "std": 0.0 |
| }, |
| "fb_fre_low_frequency_range_hz": [ |
| 7.0, |
| 15.7 |
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| "std": 0.002124 |
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| "fb_fre_low_snr": { |
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| "std": 0.068135 |
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| "fb_fre_mid_energy_ratio": { |
| "mean": 0.619438, |
| "std": 0.0 |
| }, |
| "fb_fre_mid_frequency_range_hz": [ |
| 15.7, |
| 28.75 |
| ], |
| "fb_fre_mid_ne": { |
| "mean": 0.119451, |
| "std": 0.000877 |
| }, |
| "fb_fre_mid_snr": { |
| "mean": 18.48035, |
| "std": 0.064124 |
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| "fb_fre_very_high_energy_ratio": { |
| "mean": 0.006539, |
| "std": 0.0 |
| }, |
| "fb_fre_very_high_frequency_range_hz": [ |
| 41.8, |
| 50.5 |
| ], |
| "fb_fre_very_high_ne": { |
| "mean": 0.295901, |
| "std": 0.003349 |
| }, |
| "fb_fre_very_high_snr": { |
| "mean": 10.599602, |
| "std": 0.097134 |
| }, |
| "mae": { |
| "mean": 0.002816, |
| "std": 5.2e-05 |
| }, |
| "mse": { |
| "mean": 8.8e-05, |
| "std": 1e-06 |
| }, |
| "psnr": { |
| "mean": 40.756733, |
| "std": 0.046005 |
| }, |
| "rmse": { |
| "mean": 0.00928, |
| "std": 5.4e-05 |
| }, |
| "snr": { |
| "mean": 17.4002, |
| "std": 0.045971 |
| }, |
| "ssim": { |
| "mean": 0.984733, |
| "std": 0.000249 |
| } |
| }, |
| "res_unet": { |
| "eb_wse_medium_40_70_ne": { |
| "mean": 0.486774, |
| "std": 0.004043 |
| }, |
| "eb_wse_medium_40_70_snr": { |
| "mean": 6.261013, |
| "std": 0.072467 |
| }, |
| "eb_wse_strong_70_100_ne": { |
| "mean": 0.181058, |
| "std": 0.001342 |
| }, |
| "eb_wse_strong_70_100_snr": { |
| "mean": 14.858492, |
| "std": 0.064411 |
| }, |
| "eb_wse_very_weak_5_20_ne": { |
| "mean": 2.130174, |
| "std": 0.187739 |
| }, |
| "eb_wse_very_weak_5_20_snr": { |
| "mean": -6.508905, |
| "std": 0.790704 |
| }, |
| "eb_wse_weak_20_40_ne": { |
| "mean": 0.872875, |
| "std": 0.023638 |
| }, |
| "eb_wse_weak_20_40_snr": { |
| "mean": 1.210248, |
| "std": 0.227055 |
| }, |
| "fb_fre_high_energy_ratio": { |
| "mean": 0.243824, |
| "std": 0.0 |
| }, |
| "fb_fre_high_frequency_range_hz": [ |
| 28.75, |
| 41.8 |
| ], |
| "fb_fre_high_ne": { |
| "mean": 0.180487, |
| "std": 0.003511 |
| }, |
| "fb_fre_high_snr": { |
| "mean": 14.894911, |
| "std": 0.168242 |
| }, |
| "fb_fre_low_energy_ratio": { |
| "mean": 0.023417, |
| "std": 0.0 |
| }, |
| "fb_fre_low_frequency_range_hz": [ |
| 7.0, |
| 15.7 |
| ], |
| "fb_fre_low_ne": { |
| "mean": 0.270266, |
| "std": 0.001293 |
| }, |
| "fb_fre_low_snr": { |
| "mean": 11.367955, |
| "std": 0.041544 |
| }, |
| "fb_fre_mid_energy_ratio": { |
| "mean": 0.619438, |
| "std": 0.0 |
| }, |
| "fb_fre_mid_frequency_range_hz": [ |
| 15.7, |
| 28.75 |
| ], |
| "fb_fre_mid_ne": { |
| "mean": 0.192449, |
| "std": 0.001287 |
| }, |
| "fb_fre_mid_snr": { |
| "mean": 14.333623, |
| "std": 0.058559 |
| }, |
| "fb_fre_very_high_energy_ratio": { |
| "mean": 0.006539, |
| "std": 0.0 |
| }, |
| "fb_fre_very_high_frequency_range_hz": [ |
| 41.8, |
| 50.5 |
| ], |
| "fb_fre_very_high_ne": { |
| "mean": 0.290352, |
| "std": 0.006327 |
| }, |
| "fb_fre_very_high_snr": { |
| "mean": 10.761013, |
| "std": 0.190515 |
| }, |
| "mae": { |
| "mean": 0.004629, |
| "std": 0.000126 |
| }, |
| "mse": { |
| "mean": 0.000187, |
| "std": 4e-06 |
| }, |
| "psnr": { |
| "mean": 37.4704, |
| "std": 0.079422 |
| }, |
| "rmse": { |
| "mean": 0.013524, |
| "std": 0.000125 |
| }, |
| "snr": { |
| "mean": 14.1138, |
| "std": 0.079422 |
| }, |
| "ssim": { |
| "mean": 0.974867, |
| "std": 0.000478 |
| } |
| }, |
| "atten_unet": { |
| "eb_wse_medium_40_70_ne": { |
| "mean": 0.455199, |
| "std": 0.003818 |
| }, |
| "eb_wse_medium_40_70_snr": { |
| "mean": 6.846589, |
| "std": 0.074503 |
| }, |
| "eb_wse_strong_70_100_ne": { |
| "mean": 0.17201, |
| "std": 0.003499 |
| }, |
| "eb_wse_strong_70_100_snr": { |
| "mean": 15.302219, |
| "std": 0.176979 |
| }, |
| "eb_wse_very_weak_5_20_ne": { |
| "mean": 2.171944, |
| "std": 0.03892 |
| }, |
| "eb_wse_very_weak_5_20_snr": { |
| "mean": -6.716188, |
| "std": 0.161394 |
| }, |
| "eb_wse_weak_20_40_ne": { |
| "mean": 0.884095, |
| "std": 0.01033 |
| }, |
| "eb_wse_weak_20_40_snr": { |
| "mean": 1.101884, |
| "std": 0.096279 |
| }, |
| "fb_fre_high_energy_ratio": { |
| "mean": 0.243824, |
| "std": 0.0 |
| }, |
| "fb_fre_high_frequency_range_hz": [ |
| 28.75, |
| 41.8 |
| ], |
| "fb_fre_high_ne": { |
| "mean": 0.174245, |
| "std": 0.00343 |
| }, |
| "fb_fre_high_snr": { |
| "mean": 15.199046, |
| "std": 0.171722 |
| }, |
| "fb_fre_low_energy_ratio": { |
| "mean": 0.023417, |
| "std": 0.0 |
| }, |
| "fb_fre_low_frequency_range_hz": [ |
| 7.0, |
| 15.7 |
| ], |
| "fb_fre_low_ne": { |
| "mean": 0.270073, |
| "std": 0.00521 |
| }, |
| "fb_fre_low_snr": { |
| "mean": 11.37886, |
| "std": 0.166497 |
| }, |
| "fb_fre_mid_energy_ratio": { |
| "mean": 0.619438, |
| "std": 0.0 |
| }, |
| "fb_fre_mid_frequency_range_hz": [ |
| 15.7, |
| 28.75 |
| ], |
| "fb_fre_mid_ne": { |
| "mean": 0.176185, |
| "std": 0.003015 |
| }, |
| "fb_fre_mid_snr": { |
| "mean": 15.097063, |
| "std": 0.145822 |
| }, |
| "fb_fre_very_high_energy_ratio": { |
| "mean": 0.006539, |
| "std": 0.0 |
| }, |
| "fb_fre_very_high_frequency_range_hz": [ |
| 41.8, |
| 50.5 |
| ], |
| "fb_fre_very_high_ne": { |
| "mean": 0.334154, |
| "std": 0.0121 |
| }, |
| "fb_fre_very_high_snr": { |
| "mean": 9.545639, |
| "std": 0.311643 |
| }, |
| "mae": { |
| "mean": 0.004868, |
| "std": 0.000111 |
| }, |
| "mse": { |
| "mean": 0.000168, |
| "std": 5e-06 |
| }, |
| "psnr": { |
| "mean": 37.9182, |
| "std": 0.139451 |
| }, |
| "rmse": { |
| "mean": 0.012843, |
| "std": 0.000208 |
| }, |
| "snr": { |
| "mean": 14.561633, |
| "std": 0.139496 |
| }, |
| "ssim": { |
| "mean": 0.974933, |
| "std": 0.000386 |
| } |
| } |
| } |
| } |
| }, |
| "num_params": { |
| "unet": 7760000, |
| "dncnn": 560000, |
| "res_unet": 8110000, |
| "atten_unet": 7850000 |
| } |
| } |
| AUTO_RESULTS_DATA_END --> |
| <!-- AUTO_RESULTS_END --> |
