Search is not available for this dataset
repo stringlengths 2 152 ⌀ | file stringlengths 15 239 | code stringlengths 0 58.4M | file_length int64 0 58.4M | avg_line_length float64 0 1.81M | max_line_length int64 0 12.7M | extension_type stringclasses 364 values |
|---|---|---|---|---|---|---|
null | OpenOOD-main/configs/datasets/osr_cifar6/cifar6_seed2_osr.yml | ood_dataset:
name: cifar6_seed2_osr
num_classes: 6
pre_size: 32
image_size: 32
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/test/test_cifar10_6_id_seed2.txt
osr:
datasets: [cifar4]
cifar4:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/test/test_cifar10_4_ood_seed2.txt
| 575 | 23 | 88 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar6/cifar6_seed3.yml | dataset:
name: cifar6_seed3
num_classes: 6
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/train/train_cifar10_6_seed3.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/val/val_cifar10_6_seed3.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/test/test_cifar10_6_id_seed3.txt
batch_size: 200
shuffle: False
| 870 | 24.617647 | 85 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar6/cifar6_seed3_osr.yml | ood_dataset:
name: cifar6_seed3_osr
num_classes: 6
pre_size: 32
image_size: 32
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/test/test_cifar10_6_id_seed3.txt
osr:
datasets: [cifar4]
cifar4:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/test/test_cifar10_4_ood_seed3.txt
| 575 | 23 | 88 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar6/cifar6_seed4.yml | dataset:
name: cifar6_seed4
num_classes: 6
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/train/train_cifar10_6_seed4.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/val/val_cifar10_6_seed4.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/test/test_cifar10_6_id_seed4.txt
batch_size: 200
shuffle: False
| 870 | 24.617647 | 85 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar6/cifar6_seed4_osr.yml | ood_dataset:
name: cifar6_seed4_osr
num_classes: 6
pre_size: 32
image_size: 32
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/test/test_cifar10_6_id_seed4.txt
osr:
datasets: [cifar4]
cifar4:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/test/test_cifar10_4_ood_seed4.txt
| 575 | 23 | 88 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar6/cifar6_seed5.yml | dataset:
name: cifar6_seed5
num_classes: 6
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/train/train_cifar10_6_seed5.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/val/val_cifar10_6_seed5.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/test/test_cifar10_6_id_seed5.txt
batch_size: 200
shuffle: False
| 870 | 24.617647 | 85 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar6/cifar6_seed5_osr.yml | ood_dataset:
name: cifar6_seed5_osr
num_classes: 6
pre_size: 32
image_size: 32
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/test/test_cifar10_6_id_seed5.txt
osr:
datasets: [cifar4]
cifar4:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_cifar6/test/test_cifar10_4_ood_seed5.txt
| 575 | 23 | 88 | yml |
null | OpenOOD-main/configs/datasets/osr_mnist6/mnist6_seed1.yml | dataset:
name: mnist6_seed1
num_classes: 6
pre_size: 28
image_size: 28
interpolation: bilinear
normalization_type: mnist
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/train/train_mnist_6_seed1.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/val/val_mnist_6_seed1.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_6_id_seed1.txt
batch_size: 200
shuffle: False
| 862 | 24.382353 | 83 | yml |
null | OpenOOD-main/configs/datasets/osr_mnist6/mnist6_seed1_osr.yml | ood_dataset:
name: mnist6_seed1_osr
num_classes: 6
pre_size: 28
image_size: 28
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_6_id_seed1.txt
osr:
datasets: [mnist4]
mnist4:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_4_ood_seed1.txt
| 571 | 22.833333 | 86 | yml |
null | OpenOOD-main/configs/datasets/osr_mnist6/mnist6_seed2.yml | dataset:
name: mnist6_seed2
num_classes: 6
pre_size: 28
image_size: 28
interpolation: bilinear
normalization_type: mnist
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/train/train_mnist_6_seed2.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/val/val_mnist_6_seed2.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_6_id_seed2.txt
batch_size: 200
shuffle: False
| 862 | 24.382353 | 83 | yml |
null | OpenOOD-main/configs/datasets/osr_mnist6/mnist6_seed2_osr.yml | ood_dataset:
name: mnist6_seed2_osr
num_classes: 6
pre_size: 28
image_size: 28
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_6_id_seed2.txt
osr:
datasets: [mnist4]
mnist4:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_4_ood_seed2.txt
| 571 | 22.833333 | 86 | yml |
null | OpenOOD-main/configs/datasets/osr_mnist6/mnist6_seed3.yml | dataset:
name: mnist6_seed3
num_classes: 6
pre_size: 28
image_size: 28
interpolation: bilinear
normalization_type: mnist
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/train/train_mnist_6_seed3.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/val/val_mnist_6_seed3.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_6_id_seed3.txt
batch_size: 200
shuffle: False
| 862 | 24.382353 | 83 | yml |
null | OpenOOD-main/configs/datasets/osr_mnist6/mnist6_seed3_osr.yml | ood_dataset:
name: mnist6_seed3_osr
num_classes: 6
pre_size: 28
image_size: 28
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_6_id_seed3.txt
osr:
datasets: [mnist4]
mnist4:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_4_ood_seed3.txt
| 571 | 22.833333 | 86 | yml |
null | OpenOOD-main/configs/datasets/osr_mnist6/mnist6_seed4.yml | dataset:
name: mnist6_seed4
num_classes: 6
pre_size: 28
image_size: 28
interpolation: bilinear
normalization_type: mnist
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/train/train_mnist_6_seed4.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/val/val_mnist_6_seed4.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_6_id_seed4.txt
batch_size: 200
shuffle: False
| 862 | 24.382353 | 83 | yml |
null | OpenOOD-main/configs/datasets/osr_mnist6/mnist6_seed4_osr.yml | ood_dataset:
name: mnist6_seed4_osr
num_classes: 6
pre_size: 28
image_size: 28
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_6_id_seed4.txt
osr:
datasets: [mnist4]
mnist4:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_4_ood_seed4.txt
| 571 | 22.833333 | 86 | yml |
null | OpenOOD-main/configs/datasets/osr_mnist6/mnist6_seed5.yml | dataset:
name: mnist6_seed5
num_classes: 6
pre_size: 28
image_size: 28
interpolation: bilinear
normalization_type: mnist
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/train/train_mnist_6_seed5.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/val/val_mnist_6_seed5.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_6_id_seed5.txt
batch_size: 200
shuffle: False
| 862 | 24.382353 | 83 | yml |
null | OpenOOD-main/configs/datasets/osr_mnist6/mnist6_seed5_osr.yml | ood_dataset:
name: mnist6_seed5_osr
num_classes: 6
pre_size: 28
image_size: 28
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_6_id_seed5.txt
osr:
datasets: [mnist4]
mnist4:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_mnist6/test/test_mnist_4_ood_seed5.txt
| 571 | 22.833333 | 86 | yml |
null | OpenOOD-main/configs/datasets/osr_tin20/tin20_seed1.yml | dataset:
name: tin20_seed1
num_classes: 20
pre_size: 64
image_size: 64
interpolation: bilinear
normalization_type: imagenet
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/train/train_tin_20_seed1.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/val/val_tin_20_seed1.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_20_id_seed1.txt
batch_size: 200
shuffle: False
| 859 | 24.294118 | 81 | yml |
null | OpenOOD-main/configs/datasets/osr_tin20/tin20_seed1_osr.yml | ood_dataset:
name: tin20_seed1_osr
num_classes: 20
pre_size: 64
image_size: 64
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_20_id_seed1.txt
osr:
datasets: [tin180]
tin180:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_180_ood_seed1.txt
| 568 | 22.708333 | 85 | yml |
null | OpenOOD-main/configs/datasets/osr_tin20/tin20_seed2.yml | dataset:
name: tin20_seed2
num_classes: 20
pre_size: 64
image_size: 64
interpolation: bilinear
normalization_type: imagenet
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/train/train_tin_20_seed2.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/val/val_tin_20_seed2.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_20_id_seed2.txt
batch_size: 200
shuffle: False
| 859 | 24.294118 | 81 | yml |
null | OpenOOD-main/configs/datasets/osr_tin20/tin20_seed2_osr.yml | ood_dataset:
name: tin20_seed2_osr
num_classes: 20
pre_size: 64
image_size: 64
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_20_id_seed2.txt
osr:
datasets: [tin180]
tin180:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_180_ood_seed2.txt
| 568 | 22.708333 | 85 | yml |
null | OpenOOD-main/configs/datasets/osr_tin20/tin20_seed3.yml | dataset:
name: tin20_seed3
num_classes: 20
pre_size: 64
image_size: 64
interpolation: bilinear
normalization_type: imagenet
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/train/train_tin_20_seed3.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/val/val_tin_20_seed3.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_20_id_seed3.txt
batch_size: 200
shuffle: False
| 859 | 24.294118 | 81 | yml |
null | OpenOOD-main/configs/datasets/osr_tin20/tin20_seed3_osr.yml | ood_dataset:
name: tin20_seed3_osr
num_classes: 20
pre_size: 64
image_size: 64
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_20_id_seed3.txt
osr:
datasets: [tin180]
tin180:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_180_ood_seed3.txt
| 568 | 22.708333 | 85 | yml |
null | OpenOOD-main/configs/datasets/osr_tin20/tin20_seed4.yml | dataset:
name: tin20_seed4
num_classes: 20
pre_size: 64
image_size: 64
interpolation: bilinear
normalization_type: imagenet
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/train/train_tin_20_seed4.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/val/val_tin_20_seed4.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_20_id_seed4.txt
batch_size: 200
shuffle: False
| 859 | 24.294118 | 81 | yml |
null | OpenOOD-main/configs/datasets/osr_tin20/tin20_seed4_osr.yml | ood_dataset:
name: tin20_seed4_osr
num_classes: 20
pre_size: 64
image_size: 64
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_20_id_seed4.txt
osr:
datasets: [tin180]
tin180:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_180_ood_seed4.txt
| 568 | 22.708333 | 85 | yml |
null | OpenOOD-main/configs/datasets/osr_tin20/tin20_seed5.yml | dataset:
name: tin20_seed5
num_classes: 20
pre_size: 64
image_size: 64
interpolation: bilinear
normalization_type: imagenet
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/train/train_tin_20_seed5.txt
batch_size: 128
shuffle: True
val:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/val/val_tin_20_seed5.txt
batch_size: 200
shuffle: False
test:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_20_id_seed5.txt
batch_size: 200
shuffle: False
| 859 | 24.294118 | 81 | yml |
null | OpenOOD-main/configs/datasets/osr_tin20/tin20_seed5_osr.yml | ood_dataset:
name: tin20_seed5_osr
num_classes: 20
pre_size: 64
image_size: 64
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_20_id_seed5.txt
osr:
datasets: [tin180]
tin180:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/osr_tin20/test/test_tin_180_ood_seed5.txt
| 568 | 22.708333 | 85 | yml |
null | OpenOOD-main/configs/networks/arpl_gan.yml | network:
name: arpl_gan
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
# Number of channels in the training images. For color images this is 3
nc: 3
# Size of z latent vector (i.e. size of generator input)
nz: 100
# Size of feature maps in generator
ngf: 64
# Size of feature maps in discriminator
ndf : 64
ns: 1
weight_pl: 0.1
temp: 1.0
# network used for feature extraction
feat_extract_network:
name: resnet34ABN
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
num_gpus: '@{num_gpus}'
| 721 | 23.896552 | 73 | yml |
null | OpenOOD-main/configs/networks/arpl_net.yml | network:
name: arpl_net
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
weight_pl: 0.1
temp: 1.0
# network used for feature extraction
feat_extract_network:
name: lenet
num_classes: '@{dataset.num_classes}'
pretrained: False # set 'True' to load pretrained model
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
| 524 | 26.631579 | 68 | yml |
null | OpenOOD-main/configs/networks/bit.yml | network:
name: bit
model: BiT-S-R101x1
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: True # set 'True' to load pretrained model
checkpoint: ./bit_pretrained_models/BiT-S-R101x1.npz # ignore if pretrained is false
num_gpus: '@{num_gpus}'
dataset:
image_size: 480
ood_dataset:
image_size: 480
| 368 | 27.384615 | 96 | yml |
null | OpenOOD-main/configs/networks/cider_net.yml | network:
name: cider_net
num_classes: '@{dataset.num_classes}'
pretrained: False # In training pipeline:"False"; In testing pipeline:"True"
num_gpus: '@{num_gpus}'
checkpoint: none
feat_dim: 128
head: mlp
backbone:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none
num_gpus: '@{num_gpus}'
| 411 | 21.888889 | 78 | yml |
null | OpenOOD-main/configs/networks/conf_branch.yml | network:
name: conf_branch_net
num_classes: '@{dataset.num_classes}'
pretrained: False # In training pipeline:"False"; In testing pipeline:"True"
num_gpus: '@{num_gpus}'
checkpoint: none
backbone:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: ./results/mnist_conf_net_conf_esti/best.pth
num_gpus: '@{num_gpus}'
| 426 | 29.5 | 78 | yml |
null | OpenOOD-main/configs/networks/csi_net.yml | network:
name: csi_net
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: ./results/cifar10_csinet_csi_step2_e100_lr0.1/best.ckpt
num_gpus: '@{num_gpus}'
simclr_dim: 128 # Dimension of simclr layer
shift_trans_type: rotation # choice ['rotation', 'cutperm', 'none']
backbone:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
num_gpus: '@{num_gpus}'
| 522 | 29.764706 | 72 | yml |
null | OpenOOD-main/configs/networks/cutpaste.yml | network:
name: projectionNet
num_classes: '@{dataset.num_classes}'
pretrained: False # set 'True' to load pretrained model
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
# network used for feature extraction
backbone:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: True
checkpoint: 'results/cifar100_resnet18_32x32_base_e100_lr0.1/best.ckpt'
num_gpus: '@{num_gpus}'
| 510 | 30.9375 | 75 | yml |
null | OpenOOD-main/configs/networks/dcae.yml | network:
name: dcae
type: cifar10_LeNet
num_classes: '@{dataset.num_classes}'
num_gpus: 1
pretrained: False
| 118 | 16 | 39 | yml |
null | OpenOOD-main/configs/networks/draem.yml | network:
name: draem
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False # set 'True' to load pretrained model
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
use_gt: False
image_auroc_only: True
| 293 | 25.727273 | 66 | yml |
null | OpenOOD-main/configs/networks/dropout_net.yml | network:
name: dropout_net
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
dropout_p: 0.5
# network used for feature extraction
backbone:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none
num_gpus: '@{num_gpus}'
| 462 | 24.722222 | 60 | yml |
null | OpenOOD-main/configs/networks/dsvdd.yml | network:
name: dsvdd
type: cifar10_LeNet
num_classes: '@{dataset.num_classes}'
num_gpus: 1
pretrained: True
checkpoint: './results/cifar10_dcae_dcae/AE_best_epoch1_roc_auc0.4976.pth'
| 195 | 23.5 | 76 | yml |
null | OpenOOD-main/configs/networks/godin_net.yml | network:
name: godin_net
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
similarity_measure: 'cosine' # value in ['cosine', 'inner', 'euclid']
# network used for feature extraction
backbone:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
num_gpus: '@{num_gpus}'
checkpoint: none
| 515 | 27.666667 | 71 | yml |
null | OpenOOD-main/configs/networks/lenet.yml | network:
name: lenet
num_classes: '@{dataset.num_classes}'
pretrained: False # set 'True' to load pretrained model
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
| 217 | 30.142857 | 66 | yml |
null | OpenOOD-main/configs/networks/mcd_net.yml | network:
name: mcd
num_classes: '@{dataset.num_classes}'
pretrained: False # set 'True' to load pretrained model
checkpoint: ''
num_gpus: '@{num_gpus}'
backbone:
name: lenet
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: ''
num_gpus: '@{num_gpus}'
| 351 | 22.466667 | 66 | yml |
null | OpenOOD-main/configs/networks/mos.yml | network:
name: bit
num_classes: '@{dataset.num_classes}'
model: BiT-S-R101x1
num_block_open: 0
bit_pretrained_dir: bit_pretrained_models
num_logits: 120 # total classes add num_group
pretrained: True # set 'True' to load pretrained model
normal_load: True # set True if it's load normal False if it load from the bit's own load_from
# if you want to load a pre trained model downloaded from bit github you should set normal_load to False
# otherwise if you want to load a pretrained model from this frame you should set normal_load to True
checkpoint: ./results/cifar100_double_label_resnet18_32x32_mos_e100_lr0.003/model_epoch100.ckpt
# checkpoint: ./bit_pretrained_models/BiT-S-R101x1.npz # download from https://github.com/google-research/big_transfer
num_gpus: '@{num_gpus}'
| 822 | 53.866667 | 123 | yml |
null | OpenOOD-main/configs/networks/npos_net.yml | network:
name: npos_net
num_classes: '@{dataset.num_classes}'
pretrained: False # In training pipeline:"False"; In testing pipeline:"True"
num_gpus: '@{num_gpus}'
checkpoint: none
feat_dim: 128
head: mlp
backbone:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none
num_gpus: '@{num_gpus}'
| 410 | 21.833333 | 78 | yml |
null | OpenOOD-main/configs/networks/opengan.yml | network:
name: opengan
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
# Number of channels in the training images. For color images this is 3
nc: 512
# Size of z latent vector (i.e. size of generator input)
nz: 100
# Size of feature maps in generator
ngf: 64
# Size of feature maps in discriminator
ndf : 64
# network used for feature extraction
backbone:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none
num_gpus: '@{num_gpus}'
| 696 | 25.807692 | 73 | yml |
null | OpenOOD-main/configs/networks/openmax.yml | network:
name: openmax_network
num_classes: '@{dataset.num_classes}'
pretrained: False # set 'True' to load pretrained model
checkpoint: ./results/mvtec_openmax_network_OpenMax_e100_lr0.1/best.ckpt # ignore if pretrained is false
num_gpus: '@{num_gpus}'
backbone:
name: lenet
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: ''
num_gpus: '@{num_gpus}'
| 463 | 29.933333 | 116 | yml |
null | OpenOOD-main/configs/networks/patchcore_net.yml | network:
name: patchcore_net
num_classes: '@{dataset.num_classes}'
pretrained: False # set 'True' to load pretrained model
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
load_cached_faiss: True
# network used for feature extraction
backbone:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: True
checkpoint: 'results/checkpoints/cifar10_res18_acc94.30.ckpt'
num_gpus: '@{num_gpus}'
| 526 | 30 | 66 | yml |
null | OpenOOD-main/configs/networks/rd4ad_net.yml | network:
name: rd4ad_net
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
backbone:
name: resnet18_256x256
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: True # set 'True' to load pretrained model
checkpoint: 'results/resnet18_rd4ad_teacher/resnet18-f37072fd.pth' # ignore if pretrained is false
num_gpus: '@{num_gpus}'
| 534 | 32.4375 | 111 | yml |
null | OpenOOD-main/configs/networks/react_net.yml | network:
name: react_net
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
similarity_measure: 'cosine' # value in ['cosine', 'inner', 'euclid']
# network used for feature extraction
backbone:
name: resnet50
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: True
checkpoint: 'results/checkpoints/imagenet_res50_acc76.10.pth'
num_gpus: '@{num_gpus}'
| 553 | 29.777778 | 71 | yml |
null | OpenOOD-main/configs/networks/repvgg.yml | network:
name: repvgg_b3
model: repvgg_b3
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: True # set 'True' to load pretrained model
checkpoint: timm_load # ignore if pretrained is false
num_gpus: '@{num_gpus}'
dataset:
image_size: 224
ood_dataset:
image_size: 224
| 340 | 25.230769 | 65 | yml |
null | OpenOOD-main/configs/networks/resnet18_224x224.yml | network:
name: resnet18_224x224
num_classes: '@{dataset.num_classes}'
pretrained: False # set 'True' to load pretrained model
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
| 228 | 31.714286 | 66 | yml |
null | OpenOOD-main/configs/networks/resnet18_32x32.yml | network:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
pretrained: False # set 'True' to load pretrained model
checkpoint: ./results/cifar10_double_label_resnet18_32x32_mos_e100_lr0.003/best.ckpt # ignore if pretrained is false
num_gpus: '@{num_gpus}'
| 295 | 41.285714 | 129 | yml |
null | OpenOOD-main/configs/networks/resnet18_64x64.yml | network:
name: resnet18_64x64
num_classes: '@{dataset.num_classes}'
pretrained: False # set 'True' to load pretrained model
checkpoint: ./results/cifar10_resnet18_32x32_base_e200_lr_0.1/best.ckpt # ignore if pretrained is false
num_gpus: '@{num_gpus}'
| 282 | 39.428571 | 116 | yml |
null | OpenOOD-main/configs/networks/resnet50.yml | network:
name: resnet50
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: True # set 'True' to load pretrained model
# default pretrained model: https://download.pytorch.org/models/resnet50-0676ba61.pth
checkpoint: ./checkpoints/resnet50-0676ba61.pth # ignore if pretrained is false
num_gpus: '@{num_gpus}'
| 377 | 36.8 | 91 | yml |
null | OpenOOD-main/configs/networks/rot_net.yml | network:
name: rot_net
num_classes: '@{dataset.num_classes}'
pretrained: False # In training pipeline:"False"; In testing pipeline:"True"
num_gpus: '@{num_gpus}'
checkpoint: none
backbone:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none
num_gpus: '@{num_gpus}'
| 379 | 26.142857 | 78 | yml |
null | OpenOOD-main/configs/networks/rts_net.yml | network:
name: rts_net
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none # ignore if pretrained is false
num_gpus: '@{num_gpus}'
dof: 32
kl_scale: 0.1
# network used for feature extraction
backbone:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
num_gpus: '@{num_gpus}'
| 446 | 23.833333 | 60 | yml |
null | OpenOOD-main/configs/networks/simclr.yml | network:
name: simclr_net
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: True
checkpoint: 'results/checkpoints/SSD/last_new.pth' # ignore if pretrained is false
num_gpus: '@{num_gpus}'
# network used for feature extraction
backbone:
name: resnet50
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: none
num_gpus: '@{num_gpus}'
| 471 | 26.764706 | 94 | yml |
null | OpenOOD-main/configs/networks/train_mos.yml | network:
name: bit
num_classes: '@{dataset.num_classes}'
model: BiT-S-R101x1
num_block_open: 0
bit_pretrained_dir: bit_pretrained_models
num_logits: 120 # total classes add num_group
pretrained: True # set 'True' to load pretrained model
normal_load: False # set True if it's load normal False if it load from the bit's own load_from
# if you want to load a pre trained model downloaded from bit github you should set normal_load to False
# otherwise if you want to load a pretrained model from this frame you should set normal_load to True
# checkpoint: ./results/cifar100_double_label_bit_mos_e100_lr0.003/mos_epoch_latest.ckpt
checkpoint: ./bit_pretrained_models/BiT-S-R101x1.npz # download from https://github.com/google-research/big_transfer
num_gpus: '@{num_gpus}'
| 814 | 53.333333 | 121 | yml |
null | OpenOOD-main/configs/networks/udg_net.yml | network:
name: udg
num_classes: '@{dataset.num_classes}'
num_clusters: 1000
pretrained: False # set 'True' to load pretrained model
checkpoint: ''
num_gpus: '@{num_gpus}'
backbone:
name: resnet18_32x32
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: ''
num_gpus: '@{num_gpus}'
| 381 | 22.875 | 66 | yml |
null | OpenOOD-main/configs/networks/vit.yml | network:
name: vit
model: openood/networks/vit-base-p16-384.py
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: True # set 'True' to load pretrained model
checkpoint: ./checkpoints/vit-base-p16_in21k-pre-3rdparty_ft-64xb64_in1k-384_20210928-98e8652b.pth # ignore if pretrained is false
num_gpus: '@{num_gpus}'
dataset:
image_size: 384
ood_dataset:
image_size: 384
| 436 | 32.615385 | 140 | yml |
null | OpenOOD-main/configs/networks/vos_net.yml | network:
name: vos
num_classes: '@{dataset.num_classes}'
pretrained: False # In training pipeline:"False"; In testing pipeline:"True"
num_gpus: '@{num_gpus}'
num_layers: 40
widen_factor: 2
droprate: 0.3
backbone: #for network without feature_list
name: lenet
num_classes: '@{dataset.num_classes}'
image_size: '@{dataset.image_size}'
pretrained: False
checkpoint: None
num_gpus: '@{num_gpus}'
| 433 | 24.529412 | 78 | yml |
null | OpenOOD-main/configs/pipelines/test/feat_extract.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'"
output_dir: ./results/
save_output: True
merge_option: default # disabled if 'save_output' is False
mark: default
num_gpus: 1
num_workers: 4
num_machines: 1
machine_rank: 0
network:
pretrained: True
pipeline:
name: feat_extract
extract_target: test
evaluator:
name: base
| 350 | 15.714286 | 66 | yml |
null | OpenOOD-main/configs/pipelines/test/test_acc.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'"
output_dir: ./results/
save_output: False
merge_option: merge # disabled if 'save_output' is False choices: [default, pass, merge]
num_gpus: 1
num_workers: 4
num_machines: 1
machine_rank: 0
network:
pretrained: True
pipeline:
name: test_acc
evaluator:
name: base
| 340 | 16.947368 | 88 | yml |
null | OpenOOD-main/configs/pipelines/test/test_arpl.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'_'@{evaluator.name}'_'@{postprocessor.name}'_'@{mark}'/s'@{seed}'/'@{evaluator.ood_scheme}'"
output_dir: ./results/
save_output: True
merge_option: default # disabled if 'save_output' is False
mark: default # to mark the version of experiment
seed: 0
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
network:
pretrained: True
checkpoint: ["results/imagenet200_arpl_net_arpl_e90_lr0.1/s0/best_NetF.ckpt",
"results/imagenet200_arpl_net_arpl_e90_lr0.1/s0/best_criterion.ckpt"]
pipeline:
name: test_ood
evaluator:
name: arpl
ood_scheme: ood # [ood, fsood]
recorder:
save_scores: True
save_csv: True
| 704 | 24.178571 | 157 | yml |
null | OpenOOD-main/configs/pipelines/test/test_arplgan.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'_'@{evaluator.name}'_'@{postprocessor.name}'_'@{mark}'"
output_dir: ./results/
save_output: True
merge_option: default # disabled if 'save_output' is False
mark: default # to mark the version of experiment
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
network:
pretrained: True
checkpoint: ["./results/mnist_arpl_gan_arpl_gan_e100_lr0.1/best_NetF.ckpt",
"./results/mnist_arpl_gan_arpl_gan_e100_lr0.1/best_criterion.ckpt",
null,
null]
pipeline:
name: test_ood
evaluator:
name: arpl
recorder:
save_scores: True
save_csv: True
| 667 | 22.857143 | 120 | yml |
null | OpenOOD-main/configs/pipelines/test/test_cutpaste.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'"
output_dir: ./results/
save_output: True
merge_option: merge # disabled if 'save_output' is False choices: [default, pass, merge]
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
network:
pretrained: True
checkpoint: results/bottle_projectionNet_cutpaste_e100_lr0.03/best_epoch15_auroc97.48015873015873.ckpt
pipeline:
name: test_ad
evaluator:
name: ood
recorder:
save_scores: True
save_csv: True
| 490 | 19.458333 | 104 | yml |
null | OpenOOD-main/configs/pipelines/test/test_draem.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'"
output_dir: ./results/
save_output: True
merge_option: merge # disabled if 'save_output' is False choices: [default, pass, merge]
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
network:
pretrained: True
checkpoint: ["results/osr_mnist6_seed1_draem_train_e100_lr0.0001/draem_test_0.0001_100_bs32_osr_mnist6_seed1_best_epoch1_loss0.5001.ckpt",
"results/osr_mnist6_seed1_draem_train_e100_lr0.0001/draem_test_0.0001_100_bs32_osr_mnist6_seed1_best_epoch1_loss0.5001_seg.ckpt"]
# ignore if pretrained is false
pipeline:
name: test_ad
evaluator:
name: ood
recorder:
save_scores: True
save_csv: True
| 712 | 26.423077 | 144 | yml |
null | OpenOOD-main/configs/pipelines/test/test_dsvdd.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'_'@{evaluator.name}'_'@{postprocessor.name}'_'@{mark}'"
output_dir: ./results/
save_output: True
merge_option: default # disabled if 'save_output' is False
mark: default # to mark the version of experiment
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
R: 0
c: None
objective: one-class
network:
pretrained: True
pipeline:
name: test_ad
evaluator:
name: ood
use_react: False
recorder:
save_scores: True
save_csv: True
| 514 | 16.166667 | 120 | yml |
null | OpenOOD-main/configs/pipelines/test/test_fsood.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'_'@{evaluator.name}'_'@{postprocessor.name}'_'@{mark}'"
output_dir: ./results/
save_output: True
merge_option: default # disabled if 'save_output' is False
mark: default # to mark the version of experiment
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
network:
pretrained: True
pipeline:
name: test_ood
evaluator:
name: fsood
recorder:
save_scores: True
save_csv: True
| 462 | 18.291667 | 120 | yml |
null | OpenOOD-main/configs/pipelines/test/test_kdad.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer_name}'"
output_dir: ./results/
save_output: False
merge_option: merge # disabled if 'save_output' is False choices: [default, pass, merge]
normal_class: 3 #use @ may let int -->str
lamda: 0.01
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
trainer_name: kdad
dataset_name: '@{dataset.name}'
direction_loss_only: False
last_checkpoint: 201
metrics: roc_auc
pipeline:
name: test_ad
evaluator:
name: kdad
| 478 | 20.772727 | 88 | yml |
null | OpenOOD-main/configs/pipelines/test/test_mos.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'_'@{evaluator.name}'/s'@{seed}'/'@{evaluator.ood_scheme}'"
output_dir: ./results/
save_output: True
merge_option: default
seed: 0
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
pipeline:
name: test_ood
trainer:
name: mos
# group_config: ./data/group_config/cifar100_group_config.txt
group_config: Auto # if set to none the program will auto re-compute it
# group_config is a list that the num of classes in each super classes
# It should be noted that the configuration of automatic calculation may be inconsistent with
# the category classification used in training, resulting in errors
evaluator:
name: mos
ood_scheme: ood # [ood, fsood]
optimizer:
name: sgd
num_epochs: 100
lr: 0.003
recorder:
name: base
save_scores: True
save_csv: True
save_all_models: True
| 878 | 22.756757 | 123 | yml |
null | OpenOOD-main/configs/pipelines/test/test_ood.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'_'@{evaluator.name}'_'@{postprocessor.name}'_'@{mark}'/s'@{seed}'/'@{evaluator.ood_scheme}'"
output_dir: ./results/
save_output: True
merge_option: default # disabled if 'save_output' is False
mark: default # to mark the version of experiment
seed: 0
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
network:
pretrained: True
pipeline:
name: test_ood
evaluator:
name: ood
ood_scheme: ood
recorder:
save_scores: True
save_csv: True
| 523 | 19.153846 | 157 | yml |
null | OpenOOD-main/configs/pipelines/test/test_ood_aps.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'_'@{evaluator.name}'_'@{postprocessor.name}'_'@{mark}'"
output_dir: ./results/
save_output: True
force_merge: False # disabled if 'save_output' is False
mark: default # to mark the version of experiment
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
network:
pretrained: True
pipeline:
name: test_ood_aps
evaluator:
name: ood
recorder:
save_scores: True
save_csv: True
| 461 | 18.25 | 120 | yml |
null | OpenOOD-main/configs/pipelines/test/test_opengan.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'_'@{evaluator.name}'_'@{postprocessor.name}'_'@{mark}'/s'@{seed}'/'@{evaluator.ood_scheme}'"
output_dir: ./results/
save_output: True
merge_option: default # disabled if 'save_output' is False choices: [default, pass, merge]
mark: default # to mark the version of experiment
seed: 0
num_gpus: 1
num_workers: 4
num_machines: 1
machine_rank: 0
network:
# checkpoint setting: first load generator then discriminator
pretrained: True
checkpoint: ["results/imagenet200_opengan_opengan_e90_lr0.0001_default/s0/best_GNet.ckpt",
"results/imagenet200_opengan_opengan_e90_lr0.0001_default/s0/best_DNet.ckpt",
null]
# load checkpoint for feature extraction network
backbone:
pretrained: True
checkpoint: "./results/cifar10_resnet18_32x32_base_e100_lr0.1_default/s0/best.ckpt"
pipeline:
name: test_ood
evaluator:
name: ood
ood_scheme: ood
recorder:
save_scores: True
save_csv: True
| 999 | 27.571429 | 157 | yml |
null | OpenOOD-main/configs/pipelines/test/test_osr.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'_'@{evaluator.name}'_'@{postprocessor.name}'_'@{mark}'"
output_dir: ./results/
save_output: True
merge_option: merge # disabled if 'save_output' is False choices: [default, pass, merge]
mark: default # to mark the version of experiment
num_gpus: 1
num_workers: 4
num_machines: 1
machine_rank: 0
network:
pretrained: True
pipeline:
name: test_ood
evaluator:
name: osr
recorder:
save_scores: True
save_csv: True
| 490 | 19.458333 | 120 | yml |
null | OpenOOD-main/configs/pipelines/test/test_patchcore.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'_'@{evaluator.name}'_'@{postprocessor.name}'"
output_dir: ./results/
save_output: True
merge_option: default # disabled if 'save_output' is False
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
network:
pretrained: False
pipeline:
name: test_ad
evaluator:
name: ad
test_pix: True
recorder:
save_scores: True
save_csv: True
| 416 | 16.375 | 110 | yml |
null | OpenOOD-main/configs/pipelines/test/test_rd4ad.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'"
output_dir: ./results/
save_output: True
merge_option: merge # disabled if 'save_output' is False choices: [default, pass, merge]
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
network:
pretrained: True
checkpoint: ["results/cifar10_rd4ad_net_rd4ad_e200_lr0.005_default/bn_best.ckpt",
"results/cifar10_rd4ad_net_rd4ad_e200_lr0.005_default/decoder_best.ckpt"]
# ignore if pretrained is false
pipeline:
name: test_ad
evaluator:
name: ood
recorder:
save_scores: True
save_csv: True
| 599 | 22.076923 | 88 | yml |
null | OpenOOD-main/configs/pipelines/train/baseline.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'_'@{mark}'/s'@{seed}'"
output_dir: ./results/
save_output: True
merge_option: default
mark: default
seed: 0
num_gpus: 1
num_workers: 8
num_machines: 1
machine_rank: 0
preprocessor:
name: base
network:
pretrained: False
pipeline:
name: train
trainer:
name: base
evaluator:
name: base
optimizer:
name: sgd
num_epochs: 100
lr: 0.1
momentum: 0.9
weight_decay: 0.0005
recorder:
name: base
save_all_models: False
| 550 | 13.5 | 133 | yml |
null | OpenOOD-main/configs/pipelines/train/train_arpl.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'/s'@{seed}'"
output_dir: ./results/
save_output: True
merge_option: default
seed: 0
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
pipeline:
name: train
trainer:
name: arpl
evaluator:
name: arpl
optimizer:
name: sgd
num_epochs: 100
lr: 0.1
momentum: 0.9
weight_decay: 0.0001
recorder:
name: arpl
save_all_models: False
| 468 | 14.129032 | 123 | yml |
null | OpenOOD-main/configs/pipelines/train/train_arpl_gan.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'"
output_dir: ./results/
save_output: True
merge_option: default
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
loss:
beta: 0.1
pipeline:
name: train_arplgan
trainer:
name: arpl_gan
auxiliary: arpl
evaluator:
name: arpl
optimizer:
name: sgd
num_epochs: 100
lr: 0.1
gan_lr: 0.0002
momentum: 0.9
weight_decay: 0.0005
recorder:
name: arpl
save_all_models: False
| 515 | 13.742857 | 112 | yml |
null | OpenOOD-main/configs/pipelines/train/train_augmix.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'_'@{mark}'/s'@{seed}'"
output_dir: ./results/
save_output: True
merge_option: default
mark: default
seed: 0
num_gpus: 1
num_workers: 8
num_machines: 1
machine_rank: 0
pipeline:
name: train
trainer:
name: augmix
trainer_args:
jsd: True
lam: 12
evaluator:
name: base
optimizer:
name: sgd
num_epochs: 100
lr: 0.1
momentum: 0.9
weight_decay: 0.0005
recorder:
name: base
save_all_models: False
| 536 | 14.342857 | 133 | yml |
null | OpenOOD-main/configs/pipelines/train/train_cider.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'_protom'@{trainer.trainer_args.proto_m}'_'@{mark}'/s'@{seed}'"
output_dir: ./results/
save_output: True
merge_option: default
mark: default
seed: 0
num_gpus: 1
num_workers: 8
num_machines: 1
machine_rank: 0
preprocessor:
name: base
pipeline:
name: train
trainer:
name: cider
trainer_args:
proto_m: 0.95
temp: 0.1
w: 2
evaluator:
name: base
optimizer:
name: sgd
num_epochs: 100
lr: 0.5
momentum: 0.9
weight_decay: 0.0001
warm: True
cosine: True
lr_decay_rate: 0.1
lr_decay_epochs: [50, 75, 90]
recorder:
name: cider
save_all_models: False
| 700 | 15.302326 | 173 | yml |
null | OpenOOD-main/configs/pipelines/train/train_conf_branch.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'_'@{mark}'/s'@{seed}'"
output_dir: ./results/
save_output: True
merge_option: default # disabled if 'save_output' is False
num_classes: '@{dataset.num_classes}'
mark: default
num_gpus: 1
num_workers: 8
num_machines: 1
machine_rank: 0
seed: 0
baseline: False
pipeline:
name: train
trainer:
name: conf_branch
budget: 0.3
lmbda: 0.1
eps: 1.0e-12
evaluator:
name: base
optimizer:
num_epochs: 100
lr: 0.1
momentum: 0.9
nesterov: True
weight_decay: 5.0e-4
recorder:
name: base
save_all_models: False
| 638 | 15.815789 | 133 | yml |
null | OpenOOD-main/configs/pipelines/train/train_csi.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{mode}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'/s'@{seed}'"
output_dir: ./results/
save_output: True
merge_option: default
seed: 0
num_gpus: 1
num_workers: 8
num_machines: 1
machine_rank: 0
pipeline:
name: train
trainer:
name: csi
evaluator:
name: base
optimizer:
name: sgd
num_epochs: 100 # step 1 700 epochs, step 2 100 epochs
lr: 0.1
momentum: 0.9
weight_decay: 0.000001
warmup: 10 # warm-up epochs
recorder:
name: base
save_all_models: False
mode: csi_step2 # csi_step1, csi_step2
sim_lambda: 1.0 # Weight for SimCLR loss
temperature: 0.07 # Temperature for similarity
resize_factor: 0.08 # resize scale is sampled from [resize_factor, 1.0]
resize_fix: False # resize scale is fixed to resize_factor (not [resize_factor, 1.0])
| 863 | 21.736842 | 115 | yml |
null | OpenOOD-main/configs/pipelines/train/train_cutmix.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'_'@{mark}'"
output_dir: ./results/
save_output: True
merge_option: default
mark: default
num_gpus: 1
num_workers: 8
num_machines: 1
machine_rank: 0
pipeline:
name: train
trainer:
name: cutmix
trainer_args:
beta: 1.0
cutmix_prob: 1.0 # cutmix probability
evaluator:
name: base
optimizer:
name: sgd
num_epochs: 100
lr: 0.1
momentum: 0.9
weight_decay: 0.0005
recorder:
name: base
save_all_models: False
| 549 | 15.176471 | 122 | yml |
null | OpenOOD-main/configs/pipelines/train/train_cutpaste.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'"
output_dir: ./results/
save_output: True
merge_option: default
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
pipeline:
name: train_ad
trainer:
name: cutpaste
evaluator:
name: ad
optimizer:
name: sgd
num_epochs: 100
lr: 0.03
momentum: 0.9
weight_decay: 0.0005
recorder:
name: ad
save_all_models: False
save_csv: False
| 471 | 14.225806 | 112 | yml |
null | OpenOOD-main/configs/pipelines/train/train_dcae.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'"
save_output: True
merge_option: default
normal_class: 3
output_dir: ./results/
lr: 0.0001
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
lr_milestones: [50]
weight_decay: 0.5e-6
R: 0
c: None
pipeline:
name: train_ad
evaluator:
name: dcae
trainer:
name: dcae
recorder:
name: dcae
save_all_models: False
optimizer:
name: adam
num_epochs: 150
| 463 | 13.967742 | 92 | yml |
null | OpenOOD-main/configs/pipelines/train/train_draem.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_train_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'"
output_dir: ./results/
save_output: True
merge_option: merge
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
pipeline:
name: train_ad
trainer:
name: draem
evaluator:
name: ad
optimizer:
name: MultiStep
num_epochs: 700
steps: [0.8, 0.9]
lr: 0.0001
gamma: 0.2
recorder:
name: ad
best_model_basis: image_auroc
save_all_models: False
| 470 | 14.193548 | 100 | yml |
null | OpenOOD-main/configs/pipelines/train/train_dropout.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'_dropout"
output_dir: ./results/
save_output: True
merge_option: default
num_gpus: 1
num_workers: 0
pipeline:
name: train
trainer:
name: dropout
dropout_p: 0.5
evaluator:
name: base
optimizer:
name: sgd
num_epochs: 100
lr: 0.1
momentum: 0.9
weight_decay: 0.0005
recorder:
name: base
save_all_models: False
| 445 | 14.37931 | 120 | yml |
null | OpenOOD-main/configs/pipelines/train/train_dsvdd.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'"
save_output: True
merge_option: default
normal_class: 3
output_dir: ./results/
lr: 0.0001
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
lr_milestones: [50]
weight_decay: 0.5e-6
warm_up_n_epochs: 10
R: 0
c: None
pipeline:
name: train_ad
evaluator:
name: ad
trainer:
name: dsvdd
recorder:
name: ad
save_all_models: False
optimizer:
name: adam
num_epochs: 150
| 484 | 12.857143 | 92 | yml |
null | OpenOOD-main/configs/pipelines/train/train_ece.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'"
output_dir: ./results/
save_output: True
merge_option: default
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
preprocessor:
name: base
pipeline:
name: train
trainer:
name: base
evaluator:
name: ece
optimizer:
name: sgd
num_epochs: 100
lr: 0.1
momentum: 0.9
weight_decay: 0.0005
recorder:
name: base
save_all_models: False
| 476 | 13.454545 | 112 | yml |
null | OpenOOD-main/configs/pipelines/train/train_kdad.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'"
output_dir: ./results/
save_output: True
merge_option: default # disabled if 'save_output' is False
normal_class: 3
lamda: 0.01
dataset_name: '@{dataset.name}'
direction_loss_only: False
learning_rate: 1e-3
metrics: roc_auc
last_checkpoint: 201
continue_train: False
num_gpus: 1
num_workers: 0
num_machines: 1
machine_rank: 0
pipeline:
name: train_ad
evaluator:
name: kdad
trainer:
name: kdad
recorder:
name: kdad
save_all_models: False
optimizer:
num_epochs: 201
| 544 | 17.166667 | 65 | yml |
null | OpenOOD-main/configs/pipelines/train/train_logitnorm.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'_alpha'@{trainer.trainer_args.tau}'_'@{mark}'/s'@{seed}'"
output_dir: ./results/
save_output: True
merge_option: default
mark: default
seed: 0
num_gpus: 1
num_workers: 8
num_machines: 1
machine_rank: 0
preprocessor:
name: base
pipeline:
name: train
trainer:
name: logitnorm
trainer_args:
tau: 0.04
evaluator:
name: base
optimizer:
name: sgd
num_epochs: 100
lr: 0.1
momentum: 0.9
weight_decay: 0.0005
recorder:
name: base
save_all_models: False
| 590 | 14.972973 | 168 | yml |
null | OpenOOD-main/configs/pipelines/train/train_mcd.yml | pipeline:
name: train_oe
trainer:
name: mcd
lambda_oe: 1
margin: 1.2
start_epoch_ft: 90
| 99 | 10.111111 | 20 | yml |
null | OpenOOD-main/configs/pipelines/train/train_mixoe.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'_alpha'@{trainer.alpha}'_beta'@{trainer.beta}'_'@{trainer.mix_op}'_lam'@{trainer.lambda_oe}'_'@{mark}'/s'@{seed}'"
pipeline:
name: train_oe
trainer:
name: mixoe
lambda_oe: 1.0
alpha: 0.1
beta: 1.0
mix_op: cutmix
| 337 | 27.166667 | 225 | yml |
null | OpenOOD-main/configs/pipelines/train/train_mixup.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'\
_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'\
_alpha'@{trainer.trainer_args.alpha}'_'@{mark}'"
output_dir: ./results/
save_output: True
merge_option: default
mark: default
num_gpus: 1
num_workers: 8
num_machines: 1
machine_rank: 0
pipeline:
name: train
trainer:
name: mixup
trainer_args:
alpha: 0.2
evaluator:
name: base
optimizer:
name: sgd
num_epochs: 100
lr: 0.1
momentum: 0.9
weight_decay: 0.0005
recorder:
name: base
save_all_models: False
| 547 | 14.222222 | 65 | yml |
null | OpenOOD-main/configs/pipelines/train/train_mos.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'/s'@{seed}'"
output_dir: ./results/
save_output: True
merge_option: default
seed: 0
num_gpus: 1
num_workers: 8
num_machines: 1
machine_rank: 0
pipeline:
name: train
trainer:
name: mos
# group_config: ./data/group_config/cifar100_group_config.txt
group_config: Auto # if set to none the program will auto re-compute it
# group_config is a list that the num of classes in each super classes
# It should be noted that the configuration of automatic calculation may be inconsistent with
# the category classification used in training, resulting in errors
evaluator:
name: mos
optimizer:
name: sgd
num_epochs: 100
lr: 0.003
recorder:
name: base
save_all_models: False
| 806 | 22.735294 | 123 | yml |
null | OpenOOD-main/configs/pipelines/train/train_npos.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'_'@{mark}'/s'@{seed}'"
output_dir: ./results/
save_output: True
merge_option: default
mark: default
seed: 0
num_gpus: 1
num_workers: 8
num_machines: 1
machine_rank: 0
preprocessor:
name: base
pipeline:
name: train
trainer:
name: npos
trainer_args:
proto_m: 0.95
temp: 0.1
sample_number: 1000
sample_from: 600
start_epoch_KNN: 40
K: 300
cov_mat: 0.1
select: 200
ID_points_num: 200
pick_nums: 2
w_disp: 0.5
w_comp: 1
loss_weight: 0.1
evaluator:
name: base
optimizer:
name: sgd
num_epochs: 100
lr: 0.5
momentum: 0.9
weight_decay: 0.0001
warm: True
cosine: True
lr_decay_rate: 0.1
lr_decay_epochs: [30, 50, 120]
mlp_decay_rate: 0.1
recorder:
name: cider
save_all_models: False
| 877 | 15.259259 | 133 | yml |
null | OpenOOD-main/configs/pipelines/train/train_oe.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'_lam'@{trainer.lambda_oe}'_'@{mark}'/s'@{seed}'"
pipeline:
name: train_oe
trainer:
name: oe
lambda_oe: 0.5
| 226 | 24.222222 | 159 | yml |
null | OpenOOD-main/configs/pipelines/train/train_opengan.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{trainer.name}'_e'@{optimizer.num_epochs}'_lr'@{optimizer.lr}'_'@{mark}'/s'@{seed}'"
output_dir: ./results/
save_output: True
merge_option: default
mark: default
seed: 0
dataset:
# cached features extracted from classifier
feat_root: './results/cifar10_resnet18_32x32_feat_extract_opengan_default/s0'
num_gpus: 1
num_workers: 8
num_machines: 1
machine_rank: 0
pipeline:
name: train_opengan
trainer:
name: opengan
evaluator:
name: ood
optimizer:
name: Adam
num_epochs: 100
lr: 0.0001
beta1: 0.5
recorder:
name: opengan
save_all_models: False
| 619 | 16.714286 | 133 | yml |
null | OpenOOD-main/configs/pipelines/train/train_opengan_feat_extract.yml | exp_name: "'@{dataset.name}'_'@{network.name}'_'@{pipeline.name}'_'@{mark}'/s'@{seed}'"
output_dir: ./results/
save_output: True
merge_option: default # disabled if 'save_output' is False
mark: default
seed: 0
num_gpus: 1
num_workers: 8
num_machines: 1
machine_rank: 0
network:
pretrained: True
pipeline:
name: feat_extract_opengan
evaluator:
name: base
| 364 | 16.380952 | 87 | yml |