Skip to content

语义分割炼丹技巧：输入大小 #13

Open
Open
语义分割炼丹技巧：输入大小#13
@gemfield

Description

@gemfield
gemfield
opened on May 27, 2021

输入大小的pk

数据集

  • 训练集：clothes std 2.1
  • 验证集：LIP986

炼丹参数

  • config.core.cls_num = 4
  • config.aug.ImageWithMasksRandomRotateAug.max_angle = 45
  • config.core.batch_size = 8
  • config.core.mean = config.data['mean']
  • config.core.std = config.data['std']
  • config.core.model_path = "/opt/public/pretrain/ESPNetv2/imagenet/espnetv2_s_2.0.pth"
  • config.core.optimizer = torch.optim.SGD(config.core.net.parameters(), 5e-3, momentum=0.9)
  • config.core.scheduler = optim.lr_scheduler.MultiStepLR(config.core.optimizer, milestones=[20,40,55,70,80,90,100,110,120,130,140,150,160], gamma=0.27030)
  • config.core.train_loader_list = [scale1_train_loader, scale2_train_loader, scale4_train_loader, scale3_train_loader, last_train_loader] i.e. 2.0, 1.75, 1.5, 1.25, 1
  • config.core.criterion = torch.nn.CrossEntropyLoss(weight)
  • AugFactory('SpeckleAug@0.1 => GaussianAug@0.1 => HorlineAug@0.1 => VerlineAug@0.1 => LRmotionAug@0.1 =>UDmotionAug@0.1 => NoisyAug@0.1 => DarkAug@0.1 => ColorJitterAug@0.15 => BrightnessJitterAug@0.15 =>ContrastJitterAug@0.15 => ImageWithMasksRandomRotateAug@0.6 => ImageWithMasksNormalizeAug =>ImageWithMasksCenterCropAug => ImageWithMasksScaleAug => ImageWithMasksHFlipAug@0.5 =>ImageWithMasksToTensorAug', deepvac_config)

Train

224 * 224

Epoch No.: 0    TRAIN Loss = 0.7503      TRAIN mIOU = 0.6238
Epoch No.: 1    TRAIN Loss = 0.6713      TRAIN mIOU = 0.6503
Epoch No.: 2    TRAIN Loss = 0.6205      TRAIN mIOU = 0.6682
Epoch No.: 3    TRAIN Loss = 0.5997      TRAIN mIOU = 0.6793
Epoch No.: 4    TRAIN Loss = 0.5516      TRAIN mIOU = 0.6917
Epoch No.: 5    TRAIN Loss = 0.5643      TRAIN mIOU = 0.6878
Epoch No.: 6    TRAIN Loss = 0.5286      TRAIN mIOU = 0.7039
Epoch No.: 7    TRAIN Loss = 0.4977      TRAIN mIOU = 0.7162
Epoch No.: 8    TRAIN Loss = 0.5040      TRAIN mIOU = 0.7120
Epoch No.: 9    TRAIN Loss = 0.4753      TRAIN mIOU = 0.7239
Epoch No.: 10   TRAIN Loss = 0.4736      TRAIN mIOU = 0.7276
Epoch No.: 11   TRAIN Loss = 0.4596      TRAIN mIOU = 0.7330
Epoch No.: 12   TRAIN Loss = 0.4824      TRAIN mIOU = 0.7219
Epoch No.: 13   TRAIN Loss = 0.4568      TRAIN mIOU = 0.7305
Epoch No.: 14   TRAIN Loss = 0.4334      TRAIN mIOU = 0.7418
Epoch No.: 15   TRAIN Loss = 0.4432      TRAIN mIOU = 0.7351
Epoch No.: 16   TRAIN Loss = 0.4297      TRAIN mIOU = 0.7424
Epoch No.: 17   TRAIN Loss = 0.4261      TRAIN mIOU = 0.7426
Epoch No.: 18   TRAIN Loss = 0.4251      TRAIN mIOU = 0.7488
Epoch No.: 19   TRAIN Loss = 0.3926      TRAIN mIOU = 0.7578
Epoch No.: 20   TRAIN Loss = 0.3765      TRAIN mIOU = 0.7647
Epoch No.: 21   TRAIN Loss = 0.3777      TRAIN mIOU = 0.7656
Epoch No.: 22   TRAIN Loss = 0.3639      TRAIN mIOU = 0.7720
Epoch No.: 23   TRAIN Loss = 0.3645      TRAIN mIOU = 0.7768
Epoch No.: 24   TRAIN Loss = 0.3711      TRAIN mIOU = 0.7663
Epoch No.: 25   TRAIN Loss = 0.3508      TRAIN mIOU = 0.7807
Epoch No.: 26   TRAIN Loss = 0.3660      TRAIN mIOU = 0.7690
Epoch No.: 27   TRAIN Loss = 0.3565      TRAIN mIOU = 0.7756
Epoch No.: 28   TRAIN Loss = 0.3547      TRAIN mIOU = 0.7764
Epoch No.: 29   TRAIN Loss = 0.3532      TRAIN mIOU = 0.7725
Epoch No.: 30   TRAIN Loss = 0.3574      TRAIN mIOU = 0.7767
Epoch No.: 31   TRAIN Loss = 0.3525      TRAIN mIOU = 0.7748
Epoch No.: 32   TRAIN Loss = 0.3480      TRAIN mIOU = 0.7758
Epoch No.: 33   TRAIN Loss = 0.3450      TRAIN mIOU = 0.7801
Epoch No.: 34   TRAIN Loss = 0.3431      TRAIN mIOU = 0.7828
Epoch No.: 35   TRAIN Loss = 0.3487      TRAIN mIOU = 0.7782
Epoch No.: 36   TRAIN Loss = 0.3499      TRAIN mIOU = 0.7783
Epoch No.: 37   TRAIN Loss = 0.3369      TRAIN mIOU = 0.7802
Epoch No.: 38   TRAIN Loss = 0.3433      TRAIN mIOU = 0.7827
Epoch No.: 39   TRAIN Loss = 0.3399      TRAIN mIOU = 0.7770
Epoch No.: 40   TRAIN Loss = 0.3399      TRAIN mIOU = 0.7875
Epoch No.: 41   TRAIN Loss = 0.3366      TRAIN mIOU = 0.7849
Epoch No.: 42   TRAIN Loss = 0.3324      TRAIN mIOU = 0.7891
Epoch No.: 43   TRAIN Loss = 0.3333      TRAIN mIOU = 0.7851
Epoch No.: 44   TRAIN Loss = 0.3370      TRAIN mIOU = 0.7825
Epoch No.: 45   TRAIN Loss = 0.3273      TRAIN mIOU = 0.7892
Epoch No.: 46   TRAIN Loss = 0.3370      TRAIN mIOU = 0.7839
Epoch No.: 47   TRAIN Loss = 0.3342      TRAIN mIOU = 0.7854
Epoch No.: 48   TRAIN Loss = 0.3284      TRAIN mIOU = 0.7912
Epoch No.: 49   TRAIN Loss = 0.3266      TRAIN mIOU = 0.7904

384 * 384

Epoch No.: 0    TRAIN Loss = 0.7410      TRAIN mIOU = 0.6298
Epoch No.: 1    TRAIN Loss = 0.6346      TRAIN mIOU = 0.6695
Epoch No.: 2    TRAIN Loss = 0.5823      TRAIN mIOU = 0.6901
Epoch No.: 3    TRAIN Loss = 0.5556      TRAIN mIOU = 0.6985
Epoch No.: 4    TRAIN Loss = 0.5197      TRAIN mIOU = 0.7122
Epoch No.: 5    TRAIN Loss = 0.5197      TRAIN mIOU = 0.7111
Epoch No.: 6    TRAIN Loss = 0.4832      TRAIN mIOU = 0.7300
Epoch No.: 7    TRAIN Loss = 0.4737      TRAIN mIOU = 0.7334
Epoch No.: 8    TRAIN Loss = 0.4673      TRAIN mIOU = 0.7334
Epoch No.: 9    TRAIN Loss = 0.4544      TRAIN mIOU = 0.7406
Epoch No.: 10   TRAIN Loss = 0.4384      TRAIN mIOU = 0.7477
Epoch No.: 11   TRAIN Loss = 0.4404      TRAIN mIOU = 0.7451
Epoch No.: 12   TRAIN Loss = 0.4195      TRAIN mIOU = 0.7553
Epoch No.: 13   TRAIN Loss = 0.4145      TRAIN mIOU = 0.7527
Epoch No.: 14   TRAIN Loss = 0.4114      TRAIN mIOU = 0.7590
Epoch No.: 15   TRAIN Loss = 0.4026      TRAIN mIOU = 0.7625
Epoch No.: 16   TRAIN Loss = 0.3955      TRAIN mIOU = 0.7651
Epoch No.: 17   TRAIN Loss = 0.3965      TRAIN mIOU = 0.7600
Epoch No.: 18   TRAIN Loss = 0.3644      TRAIN mIOU = 0.7791
Epoch No.: 19   TRAIN Loss = 0.3848      TRAIN mIOU = 0.7707
Epoch No.: 20   TRAIN Loss = 0.3595      TRAIN mIOU = 0.7828
Epoch No.: 21   TRAIN Loss = 0.3410      TRAIN mIOU = 0.7878
Epoch No.: 22   TRAIN Loss = 0.3373      TRAIN mIOU = 0.7897
Epoch No.: 23   TRAIN Loss = 0.3347      TRAIN mIOU = 0.7900
Epoch No.: 24   TRAIN Loss = 0.3215      TRAIN mIOU = 0.7972
Epoch No.: 25   TRAIN Loss = 0.3285      TRAIN mIOU = 0.7950
Epoch No.: 26   TRAIN Loss = 0.3271      TRAIN mIOU = 0.7948
Epoch No.: 27   TRAIN Loss = 0.3280      TRAIN mIOU = 0.7967
Epoch No.: 28   TRAIN Loss = 0.3176      TRAIN mIOU = 0.7990
Epoch No.: 29   TRAIN Loss = 0.3174      TRAIN mIOU = 0.7997
Epoch No.: 30   TRAIN Loss = 0.3141      TRAIN mIOU = 0.7984
Epoch No.: 31   TRAIN Loss = 0.3192      TRAIN mIOU = 0.8005
Epoch No.: 32   TRAIN Loss = 0.3201      TRAIN mIOU = 0.8000
Epoch No.: 33   TRAIN Loss = 0.3105      TRAIN mIOU = 0.8026
Epoch No.: 34   TRAIN Loss = 0.3102      TRAIN mIOU = 0.8026
Epoch No.: 35   TRAIN Loss = 0.3039      TRAIN mIOU = 0.8049
Epoch No.: 36   TRAIN Loss = 0.3102      TRAIN mIOU = 0.8012
Epoch No.: 37   TRAIN Loss = 0.3084      TRAIN mIOU = 0.8028
Epoch No.: 38   TRAIN Loss = 0.3047      TRAIN mIOU = 0.8070
Epoch No.: 39   TRAIN Loss = 0.3096      TRAIN mIOU = 0.8071
Epoch No.: 40   TRAIN Loss = 0.3021      TRAIN mIOU = 0.8081
Epoch No.: 41   TRAIN Loss = 0.3000      TRAIN mIOU = 0.8061
Epoch No.: 42   TRAIN Loss = 0.2979      TRAIN mIOU = 0.8097
Epoch No.: 43   TRAIN Loss = 0.2945      TRAIN mIOU = 0.8095
Epoch No.: 44   TRAIN Loss = 0.2974      TRAIN mIOU = 0.8100
Epoch No.: 45   TRAIN Loss = 0.2967      TRAIN mIOU = 0.8093
Epoch No.: 46   TRAIN Loss = 0.2974      TRAIN mIOU = 0.8076
Epoch No.: 47   TRAIN Loss = 0.2954      TRAIN mIOU = 0.8126
Epoch No.: 48   TRAIN Loss = 0.2982      TRAIN mIOU = 0.8123
Epoch No.: 49   TRAIN Loss = 0.2986      TRAIN mIOU = 0.8078

VAL

224 * 224

Epoch No.: 0    VAL Loss = 0.9486        VAL mIOU = 0.5981
Epoch No.: 1    VAL Loss = 1.0930        VAL mIOU = 0.6254
Epoch No.: 2    VAL Loss = 0.6092        VAL mIOU = 0.6251
Epoch No.: 3    VAL Loss = 0.8239        VAL mIOU = 0.6337
Epoch No.: 4    VAL Loss = 0.6866        VAL mIOU = 0.6363
Epoch No.: 5    VAL Loss = 0.6907        VAL mIOU = 0.6463
Epoch No.: 6    VAL Loss = 0.3703        VAL mIOU = 0.6474
Epoch No.: 7    VAL Loss = 0.1954        VAL mIOU = 0.6546
Epoch No.: 8    VAL Loss = 0.5008        VAL mIOU = 0.6579
Epoch No.: 9    VAL Loss = 0.9468        VAL mIOU = 0.6589
Epoch No.: 10   VAL Loss = 0.3087        VAL mIOU = 0.6500
Epoch No.: 11   VAL Loss = 0.7298        VAL mIOU = 0.6609
Epoch No.: 12   VAL Loss = 0.3829        VAL mIOU = 0.6683
Epoch No.: 13   VAL Loss = 0.7058        VAL mIOU = 0.6331
Epoch No.: 14   VAL Loss = 0.5151        VAL mIOU = 0.6597
Epoch No.: 15   VAL Loss = 0.7313        VAL mIOU = 0.6593
Epoch No.: 16   VAL Loss = 0.3872        VAL mIOU = 0.6708
Epoch No.: 17   VAL Loss = 1.1026        VAL mIOU = 0.6637
Epoch No.: 18   VAL Loss = 0.3062        VAL mIOU = 0.6568
Epoch No.: 19   VAL Loss = 0.2992        VAL mIOU = 0.6666
Epoch No.: 20   VAL Loss = 0.5475        VAL mIOU = 0.6712
Epoch No.: 21   VAL Loss = 1.5159        VAL mIOU = 0.6695
Epoch No.: 22   VAL Loss = 0.7398        VAL mIOU = 0.6710
Epoch No.: 23   VAL Loss = 0.5196        VAL mIOU = 0.6742
Epoch No.: 24   VAL Loss = 0.2721        VAL mIOU = 0.6775
Epoch No.: 25   VAL Loss = 0.5670        VAL mIOU = 0.6809
Epoch No.: 26   VAL Loss = 0.3878        VAL mIOU = 0.6815
Epoch No.: 27   VAL Loss = 0.3445        VAL mIOU = 0.6746
Epoch No.: 28   VAL Loss = 0.3857        VAL mIOU = 0.6773
Epoch No.: 29   VAL Loss = 0.2027        VAL mIOU = 0.6803
Epoch No.: 30   VAL Loss = 0.2369        VAL mIOU = 0.6787
Epoch No.: 31   VAL Loss = 0.3696        VAL mIOU = 0.6804
Epoch No.: 32   VAL Loss = 1.2621        VAL mIOU = 0.6733
Epoch No.: 33   VAL Loss = 0.3596        VAL mIOU = 0.6756
Epoch No.: 34   VAL Loss = 0.2536        VAL mIOU = 0.6796
Epoch No.: 35   VAL Loss = 0.6286        VAL mIOU = 0.6788
Epoch No.: 36   VAL Loss = 0.3019        VAL mIOU = 0.6833
Epoch No.: 37   VAL Loss = 0.5164        VAL mIOU = 0.6773
Epoch No.: 38   VAL Loss = 0.8890        VAL mIOU = 0.6810
Epoch No.: 39   VAL Loss = 0.4940        VAL mIOU = 0.6731
Epoch No.: 40   VAL Loss = 0.2817        VAL mIOU = 0.6795
Epoch No.: 41   VAL Loss = 0.5478        VAL mIOU = 0.6739
Epoch No.: 42   VAL Loss = 0.3053        VAL mIOU = 0.6780
Epoch No.: 43   VAL Loss = 0.3638        VAL mIOU = 0.6782
Epoch No.: 44   VAL Loss = 0.8372        VAL mIOU = 0.6816
Epoch No.: 45   VAL Loss = 0.3126        VAL mIOU = 0.6803
Epoch No.: 46   VAL Loss = 0.7972        VAL mIOU = 0.6771
Epoch No.: 47   VAL Loss = 0.3211        VAL mIOU = 0.6827
Epoch No.: 48   VAL Loss = 0.2223        VAL mIOU = 0.6810
Epoch No.: 49   VAL Loss = 0.8816        VAL mIOU = 0.6790

384 * 384

Epoch No.: 0    VAL Loss = 0.4397        VAL mIOU = 0.6157
Epoch No.: 1    VAL Loss = 1.0275        VAL mIOU = 0.6647
Epoch No.: 2    VAL Loss = 1.0030        VAL mIOU = 0.6670
Epoch No.: 3    VAL Loss = 0.9768        VAL mIOU = 0.6272
Epoch No.: 4    VAL Loss = 0.9051        VAL mIOU = 0.6783
Epoch No.: 5    VAL Loss = 0.4021        VAL mIOU = 0.6695
Epoch No.: 6    VAL Loss = 0.1785        VAL mIOU = 0.6677
Epoch No.: 7    VAL Loss = 0.2535        VAL mIOU = 0.6786
Epoch No.: 8    VAL Loss = 0.2187        VAL mIOU = 0.6725
Epoch No.: 9    VAL Loss = 0.3153        VAL mIOU = 0.6861
Epoch No.: 10   VAL Loss = 0.3899        VAL mIOU = 0.6830
Epoch No.: 11   VAL Loss = 0.8716        VAL mIOU = 0.6870
Epoch No.: 12   VAL Loss = 0.3529        VAL mIOU = 0.6922
Epoch No.: 13   VAL Loss = 0.5868        VAL mIOU = 0.6852
Epoch No.: 14   VAL Loss = 0.6046        VAL mIOU = 0.6880
Epoch No.: 15   VAL Loss = 0.2905        VAL mIOU = 0.6948
Epoch No.: 16   VAL Loss = 0.1958        VAL mIOU = 0.6816
Epoch No.: 17   VAL Loss = 0.4475        VAL mIOU = 0.6891
Epoch No.: 18   VAL Loss = 0.1578        VAL mIOU = 0.6989
Epoch No.: 19   VAL Loss = 0.2862        VAL mIOU = 0.7041
Epoch No.: 20   VAL Loss = 0.4287        VAL mIOU = 0.7104
Epoch No.: 21   VAL Loss = 0.4995        VAL mIOU = 0.7036
Epoch No.: 22   VAL Loss = 0.4040        VAL mIOU = 0.7047
Epoch No.: 23   VAL Loss = 0.2101        VAL mIOU = 0.7023
Epoch No.: 24   VAL Loss = 0.4608        VAL mIOU = 0.7026
Epoch No.: 25   VAL Loss = 0.3806        VAL mIOU = 0.7033
Epoch No.: 26   VAL Loss = 0.3756        VAL mIOU = 0.7023
Epoch No.: 27   VAL Loss = 0.5805        VAL mIOU = 0.7032
Epoch No.: 28   VAL Loss = 0.3759        VAL mIOU = 0.7094
Epoch No.: 29   VAL Loss = 0.4081        VAL mIOU = 0.6970
Epoch No.: 30   VAL Loss = 0.1993        VAL mIOU = 0.7078
Epoch No.: 31   VAL Loss = 0.3640        VAL mIOU = 0.7071
Epoch No.: 32   VAL Loss = 0.3213        VAL mIOU = 0.7089
Epoch No.: 33   VAL Loss = 0.4832        VAL mIOU = 0.7085
Epoch No.: 34   VAL Loss = 0.2025        VAL mIOU = 0.7097
Epoch No.: 35   VAL Loss = 0.1654        VAL mIOU = 0.7108
Epoch No.: 36   VAL Loss = 0.4561        VAL mIOU = 0.7117
Epoch No.: 37   VAL Loss = 0.4685        VAL mIOU = 0.7139
Epoch No.: 38   VAL Loss = 0.6386        VAL mIOU = 0.7068
Epoch No.: 39   VAL Loss = 0.2288        VAL mIOU = 0.7123
Epoch No.: 40   VAL Loss = 0.1666        VAL mIOU = 0.7111
Epoch No.: 41   VAL Loss = 0.3827        VAL mIOU = 0.7101
Epoch No.: 42   VAL Loss = 0.3823        VAL mIOU = 0.7052
Epoch No.: 43   VAL Loss = 0.2659        VAL mIOU = 0.7132
Epoch No.: 44   VAL Loss = 0.4662        VAL mIOU = 0.7042
Epoch No.: 45   VAL Loss = 0.2377        VAL mIOU = 0.7075
Epoch No.: 46   VAL Loss = 0.4985        VAL mIOU = 0.7081
Epoch No.: 47   VAL Loss = 0.2234        VAL mIOU = 0.7029
Epoch No.: 48   VAL Loss = 0.1307        VAL mIOU = 0.7111
Epoch No.: 49   VAL Loss = 0.2732        VAL mIOU = 0.7076

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type

    Fields

    No fields configured for issues without a type.

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions