LXXXXR
GitHub
parent
af83e981ac
commit
3f085026cf
|
|
@ -0,0 +1,32 @@
|
|||
# dataset settings
|
||||
dataset_type = 'CIFAR100'
|
||||
img_norm_cfg = dict(
|
||||
mean=[129.304, 124.070, 112.434],
|
||||
std=[68.170, 65.392, 70.418],
|
||||
to_rgb=True)
|
||||
train_pipeline = [
|
||||
dict(type='RandomCrop', size=32, padding=4),
|
||||
dict(type='RandomFlip', flip_prob=0.5, direction='horizontal'),
|
||||
dict(type='Normalize', **img_norm_cfg),
|
||||
dict(type='ImageToTensor', keys=['img']),
|
||||
dict(type='ToTensor', keys=['gt_label']),
|
||||
dict(type='Collect', keys=['img', 'gt_label'])
|
||||
]
|
||||
test_pipeline = [
|
||||
dict(type='Normalize', **img_norm_cfg),
|
||||
dict(type='ImageToTensor', keys=['img']),
|
||||
dict(type='Collect', keys=['img'])
|
||||
]
|
||||
data = dict(
|
||||
samples_per_gpu=16,
|
||||
workers_per_gpu=2,
|
||||
train=dict(
|
||||
type=dataset_type,
|
||||
data_prefix='data/cifar100',
|
||||
pipeline=train_pipeline),
|
||||
val=dict(
|
||||
type=dataset_type, data_prefix='data/cifar100',
|
||||
pipeline=test_pipeline),
|
||||
test=dict(
|
||||
type=dataset_type, data_prefix='data/cifar100',
|
||||
pipeline=test_pipeline))
|
||||
|
|
@ -26,6 +26,12 @@
|
|||
| ResNet-101-b16x8 | 42.51 | 2.52 | 95.66 | | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/resnet/resnet101_b16x8_cifar10.py) | [model](https://download.openmmlab.com/mmclassification/v0/resnet/resnet101_b16x8_cifar10_20200823-d9501bbc.pth) | [log](https://download.openmmlab.com/mmclassification/v0/resnet/resnet101_b16x8_cifar10_20200823-d9501bbc.log.json) |
|
||||
| ResNet-152-b16x8 | 58.16 | 3.74 | 95.96 | | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/resnet/resnet152_b16x8_cifar10.py) | [model](https://download.openmmlab.com/mmclassification/v0/resnet/resnet152_b16x8_cifar10_20200823-ad4d5d0c.pth) | [log](https://download.openmmlab.com/mmclassification/v0/resnet/resnet152_b16x8_cifar10_20200823-ad4d5d0c.log.json) |
|
||||
|
||||
## Cifar100
|
||||
|
||||
| Model | Params(M) | Flops(G) | Top-1 (%) | Top-5 (%) | Config | Download |
|
||||
|:---------------------:|:---------:|:--------:|:---------:|:---------:|:---------:|:--------:|
|
||||
| ResNet-50-b16x8 | 23.71 | 1.31 | 80.51 | 95.27 | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/resnet/resnet50_b16x8_cifar100.py) | [model](https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_batch256_cifar100_20210410-37f13c16.pth) | [log](https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_batch256_cifar100_20210410-37f13c16.log.json) |
|
||||
|
||||
### ImageNet
|
||||
|
||||
| Model | Params(M) | Flops(G) | Top-1 (%) | Top-5 (%) | Config | Download |
|
||||
|
|
|
|||
|
|
@ -0,0 +1,10 @@
|
|||
_base_ = [
|
||||
'../_base_/models/resnet50_cifar.py',
|
||||
'../_base_/datasets/cifar100_bs16.py',
|
||||
'../_base_/schedules/cifar10_bs128.py', '../_base_/default_runtime.py'
|
||||
]
|
||||
|
||||
model = dict(head=dict(num_classes=100))
|
||||
|
||||
optimizer = dict(type='SGD', lr=0.1, momentum=0.9, weight_decay=0.0005)
|
||||
lr_config = dict(policy='step', step=[60, 120, 160], gamma=0.2)
|
||||
|
|
@ -31,8 +31,8 @@ The ResNet family models below are trained by standard data augmentations, i.e.,
|
|||
| ResNeXt-32x4d-101 | 44.18 | 8.03 | 78.7 | 94.34 | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/resnext/resnext101_32x4d_b32x8_imagenet.py) | [model](https://download.openmmlab.com/mmclassification/v0/resnext/resnext101_32x4d_batch256_imagenet_20200708-87f2d1c9.pth) | [log](https://download.openmmlab.com/mmclassification/v0/resnext/resnext101_32x4d_batch256_imagenet_20200708-87f2d1c9.log.json) |
|
||||
| ResNeXt-32x8d-101 | 88.79 | 16.5 | 79.22 | 94.52 | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/resnext/resnext101_32x8d_b32x8_imagenet.py) | [model](https://download.openmmlab.com/mmclassification/v0/resnext/resnext101_32x8d_batch256_imagenet_20200708-1ec34aa7.pth) | [log](https://download.openmmlab.com/mmclassification/v0/resnext/resnext101_32x8d_batch256_imagenet_20200708-1ec34aa7.log.json) |
|
||||
| ResNeXt-32x4d-152 | 59.95 | 11.8 | 79.06 | 94.47 | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/resnext/resnext152_32x4d_b32x8_imagenet.py) | [model](https://download.openmmlab.com/mmclassification/v0/resnext/resnext152_32x4d_batch256_imagenet_20200708-aab5034c.pth) | [log](https://download.openmmlab.com/mmclassification/v0/resnext/resnext152_32x4d_batch256_imagenet_20200708-aab5034c.log.json) |
|
||||
| SE-ResNet-50 | 28.09 | 4.13 | 77.74 | 93.84 | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/seresnet50/seresnet50_b32x8_imagenet.py) | [model](https://download.openmmlab.com/mmclassification/v0/se-resnet/se-resnet50_batch256_imagenet_20200804-ae206104.pth) | [log](https://download.openmmlab.com/mmclassification/v0/se-resnet/se-resnet50_batch256_imagenet_20200708-657b3c36.log.json) |
|
||||
| SE-ResNet-101 | 49.33 | 7.86 | 78.26 | 94.07 | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/seresnet101/seresnet101_b32x8_imagenet.py) | [model](https://download.openmmlab.com/mmclassification/v0/se-resnet/se-resnet101_batch256_imagenet_20200804-ba5b51d4.pth) | [log](https://download.openmmlab.com/mmclassification/v0/se-resnet/se-resnet101_batch256_imagenet_20200708-038a4d04.log.json) |
|
||||
| SE-ResNet-50 | 28.09 | 4.13 | 77.74 | 93.84 | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/seresnet/seresnet50_b32x8_imagenet.py) | [model](https://download.openmmlab.com/mmclassification/v0/se-resnet/se-resnet50_batch256_imagenet_20200804-ae206104.pth) | [log](https://download.openmmlab.com/mmclassification/v0/se-resnet/se-resnet50_batch256_imagenet_20200708-657b3c36.log.json) |
|
||||
| SE-ResNet-101 | 49.33 | 7.86 | 78.26 | 94.07 | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/seresnet/seresnet101_b32x8_imagenet.py) | [model](https://download.openmmlab.com/mmclassification/v0/se-resnet/se-resnet101_batch256_imagenet_20200804-ba5b51d4.pth) | [log](https://download.openmmlab.com/mmclassification/v0/se-resnet/se-resnet101_batch256_imagenet_20200708-038a4d04.log.json) |
|
||||
| ShuffleNetV1 1.0x (group=3) | 1.87 | 0.146 | 68.13 | 87.81 | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/shufflenet_v1/shufflenet_v1_1x_b64x16_linearlr_bn_nowd_imagenet.py) | [model](https://download.openmmlab.com/mmclassification/v0/shufflenet_v1/shufflenet_v1_batch1024_imagenet_20200804-5d6cec73.pth) | [log](https://download.openmmlab.com/mmclassification/v0/shufflenet_v1/shufflenet_v1_batch1024_imagenet_20200804-5d6cec73.log.json) |
|
||||
| ShuffleNetV2 1.0x | 2.28 | 0.149 | 69.55 | 88.92 | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/shufflenet_v2/shufflenet_v2_1x_b64x16_linearlr_bn_nowd_imagenet.py) | [model](https://download.openmmlab.com/mmclassification/v0/shufflenet_v2/shufflenet_v2_batch1024_imagenet_20200812-5bf4721e.pth) | [log](https://download.openmmlab.com/mmclassification/v0/shufflenet_v2/shufflenet_v2_batch1024_imagenet_20200804-8860eec9.log.json) |
|
||||
| MobileNet V2 | 3.5 | 0.319 | 71.86 | 90.42 | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/mobilenet_v2/mobilenet_v2_b32x8_imagenet.py) | [model](https://download.openmmlab.com/mmclassification/v0/mobilenet_v2/mobilenet_v2_batch256_imagenet_20200708-3b2dc3af.pth) | [log](https://download.openmmlab.com/mmclassification/v0/mobilenet_v2/mobilenet_v2_batch256_imagenet_20200708-3b2dc3af.log.json) |
|
||||
|
|
|
|||
Loading…
Reference in New Issue