mirror of
https://github.com/open-mmlab/mmclassification.git
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07bb15e5fd
* resolve conflicts add heads and config for multilabel tasks * minor change * remove evaluating mAP in head * add baseline config * add configs * reserve only one config * minor change * fix minor bug * minor change * minor change * add unittests and fix docstrings
26 lines
846 B
Python
26 lines
846 B
Python
_base_ = ['../_base_/datasets/voc_bs16.py', '../_base_/default_runtime.py']
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# use different head for multilabel task
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model = dict(
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type='ImageClassifier',
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backbone=dict(type='VGG', depth=16, num_classes=20),
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neck=None,
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head=dict(
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type='MultiLabelClsHead',
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loss=dict(type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0)))
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# load model pretrained on imagenet
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load_from = 'https://download.openmmlab.com/mmclassification/v0/vgg/vgg16_imagenet-91b6d117.pth' # noqa
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# optimizer
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optimizer = dict(
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type='SGD',
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lr=0.001,
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momentum=0.9,
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weight_decay=0,
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paramwise_cfg=dict(custom_keys={'.backbone.classifier': dict(lr_mult=10)}))
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optimizer_config = dict(grad_clip=None)
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# learning policy
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lr_config = dict(policy='step', step=20, gamma=0.1)
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runner = dict(type='EpochBasedRunner', max_epochs=40)
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