12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152 |
- _base_ = './fcos_r50-caffe_fpn_gn-head_1x_coco.py'
- # model settings
- model = dict(
- data_preprocessor=dict(
- type='DetDataPreprocessor',
- mean=[123.675, 116.28, 103.53],
- std=[58.395, 57.12, 57.375],
- bgr_to_rgb=True,
- pad_size_divisor=32),
- backbone=dict(
- type='ResNeXt',
- depth=101,
- groups=64,
- base_width=4,
- num_stages=4,
- out_indices=(0, 1, 2, 3),
- frozen_stages=1,
- norm_cfg=dict(type='BN', requires_grad=True),
- norm_eval=True,
- style='pytorch',
- init_cfg=dict(
- type='Pretrained', checkpoint='open-mmlab://resnext101_64x4d')))
- # dataset settings
- train_pipeline = [
- dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
- dict(type='LoadAnnotations', with_bbox=True),
- dict(
- type='RandomChoiceResize',
- scale=[(1333, 640), (1333, 800)],
- keep_ratio=True),
- dict(type='RandomFlip', prob=0.5),
- dict(type='PackDetInputs')
- ]
- train_dataloader = dict(dataset=dict(pipeline=train_pipeline))
- # training schedule for 2x
- max_epochs = 24
- train_cfg = dict(max_epochs=max_epochs)
- # learning rate
- param_scheduler = [
- dict(type='ConstantLR', factor=1.0 / 3, by_epoch=False, begin=0, end=500),
- dict(
- type='MultiStepLR',
- begin=0,
- end=max_epochs,
- by_epoch=True,
- milestones=[16, 22],
- gamma=0.1)
- ]
|