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Merge pull request #26 from Jiahao000/places205

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update places205 linear classification config
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Xiaohang Zhan 2020-08-15 00:06:11 +08:00 committed by GitHub
commit d7eb74328e
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4 changed files with 21 additions and 20 deletions
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15
configs/benchmarks/linear_classification/places205/r50_multihead.py
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@ -1,4 +1,4 @@
_base_ = '../../base.py' _base_ = '../../../base.py'
# model settings # model settings
model = dict( model = dict(
type='Classification', type='Classification',
@ -31,16 +31,11 @@ data_test_root = 'data/places205/val'
dataset_type = 'ClassificationDataset' dataset_type = 'ClassificationDataset'
img_norm_cfg = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) img_norm_cfg = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
train_pipeline = [ train_pipeline = [
dict(type='RandomResizedCrop', size=224), dict(type='Resize', size=256),
dict(type='CenterCrop', size=256),
dict(type='RandomCrop', size=224),
dict(type='RandomHorizontalFlip'), dict(type='RandomHorizontalFlip'),
dict(
type='ColorJitter',
brightness=0.4,
contrast=0.4,
saturation=0.4,
hue=0.),
dict(type='ToTensor'), dict(type='ToTensor'),
dict(type='Lighting'),
dict(type='Normalize', **img_norm_cfg), dict(type='Normalize', **img_norm_cfg),
] ]
test_pipeline = [ test_pipeline = [
@ -86,4 +81,4 @@ optimizer = dict(
lr_config = dict(policy='step', step=[30, 60, 90]) lr_config = dict(policy='step', step=[30, 60, 90])
checkpoint_config = dict(interval=10) checkpoint_config = dict(interval=10)
# runtime settings # runtime settings
total_epochs = 90 total_epochs = 100

15
configs/benchmarks/linear_classification/places205/r50_multihead_sobel.py
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@ -1,4 +1,4 @@
_base_ = '../../base.py' _base_ = '../../../base.py'
# model settings # model settings
model = dict( model = dict(
type='Classification', type='Classification',
@ -31,16 +31,11 @@ data_test_root = 'data/places205/val'
dataset_type = 'ClassificationDataset' dataset_type = 'ClassificationDataset'
img_norm_cfg = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) img_norm_cfg = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
train_pipeline = [ train_pipeline = [
dict(type='RandomResizedCrop', size=224), dict(type='Resize', size=256),
dict(type='CenterCrop', size=256),
dict(type='RandomCrop', size=224),
dict(type='RandomHorizontalFlip'), dict(type='RandomHorizontalFlip'),
dict(
type='ColorJitter',
brightness=0.4,
contrast=0.4,
saturation=0.4,
hue=0.),
dict(type='ToTensor'), dict(type='ToTensor'),
dict(type='Lighting'),
dict(type='Normalize', **img_norm_cfg), dict(type='Normalize', **img_norm_cfg),
] ]
test_pipeline = [ test_pipeline = [
@ -86,4 +81,4 @@ optimizer = dict(
lr_config = dict(policy='step', step=[30, 60, 90]) lr_config = dict(policy='step', step=[30, 60, 90])
checkpoint_config = dict(interval=10) checkpoint_config = dict(interval=10)
# runtime settings # runtime settings
total_epochs = 90 total_epochs = 100

1
openselfsup/datasets/data_sources/__init__.py
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@ -1,3 +1,4 @@
from .cifar import Cifar10, Cifar100 from .cifar import Cifar10, Cifar100
from .image_list import ImageList from .image_list import ImageList
from .imagenet import ImageNet from .imagenet import ImageNet
from .places205 import Places205

10
openselfsup/datasets/data_sources/places205.py Normal file
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@ -0,0 +1,10 @@
from ..registry import DATASOURCES
from .image_list import ImageList
@DATASOURCES.register_module
class Places205(ImageList):
def __init__(self, root, list_file, memcached, mclient_path):
super(Places205, self).__init__(
root, list_file, memcached, mclient_path)