| _base_ = './paa_r50_fpn_1x_coco.py' | |
| img_norm_cfg = dict( | |
| mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict(type='LoadAnnotations', with_bbox=True), | |
| dict( | |
| type='Resize', | |
| img_scale=[(1333, 640), (1333, 800)], | |
| multiscale_mode='range', | |
| keep_ratio=True), | |
| dict(type='RandomFlip', flip_ratio=0.5), | |
| dict(type='Normalize', **img_norm_cfg), | |
| dict(type='Pad', size_divisor=32), | |
| dict(type='DefaultFormatBundle'), | |
| dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']), | |
| ] | |
| data = dict(train=dict(pipeline=train_pipeline)) | |
| lr_config = dict(step=[28, 34]) | |
| runner = dict(type='EpochBasedRunner', max_epochs=36) | |