| _base_ = './fovea_r50_fpn_4xb4-1x_coco.py' | |
| model = dict( | |
| bbox_head=dict( | |
| with_deform=True, | |
| norm_cfg=dict(type='GN', num_groups=32, requires_grad=True))) | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}), | |
| dict(type='LoadAnnotations', with_bbox=True), | |
| dict( | |
| type='RandomChoiceResize', | |
| scales=[(1333, 640), (1333, 800)], | |
| keep_ratio=True), | |
| dict(type='RandomFlip', prob=0.5), | |
| dict(type='PackDetInputs') | |
| ] | |
| train_dataloader = dict(dataset=dict(pipeline=train_pipeline)) | |
| # learning policy | |
| max_epochs = 24 | |
| param_scheduler = [ | |
| dict( | |
| type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500), | |
| dict( | |
| type='MultiStepLR', | |
| begin=0, | |
| end=max_epochs, | |
| by_epoch=True, | |
| milestones=[16, 22], | |
| gamma=0.1) | |
| ] | |
| train_cfg = dict(max_epochs=max_epochs) | |