| _base_ = '../fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py' | |
| model = dict( | |
| pretrained='open-mmlab://msra/hrnetv2_w32', | |
| backbone=dict( | |
| _delete_=True, | |
| type='HRNet', | |
| extra=dict( | |
| stage1=dict( | |
| num_modules=1, | |
| num_branches=1, | |
| block='BOTTLENECK', | |
| num_blocks=(4, ), | |
| num_channels=(64, )), | |
| stage2=dict( | |
| num_modules=1, | |
| num_branches=2, | |
| block='BASIC', | |
| num_blocks=(4, 4), | |
| num_channels=(32, 64)), | |
| stage3=dict( | |
| num_modules=4, | |
| num_branches=3, | |
| block='BASIC', | |
| num_blocks=(4, 4, 4), | |
| num_channels=(32, 64, 128)), | |
| stage4=dict( | |
| num_modules=3, | |
| num_branches=4, | |
| block='BASIC', | |
| num_blocks=(4, 4, 4, 4), | |
| num_channels=(32, 64, 128, 256)))), | |
| neck=dict( | |
| _delete_=True, | |
| type='HRFPN', | |
| in_channels=[32, 64, 128, 256], | |
| out_channels=256, | |
| stride=2, | |
| num_outs=5)) | |
| img_norm_cfg = dict( | |
| mean=[103.53, 116.28, 123.675], std=[57.375, 57.12, 58.395], to_rgb=False) | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict(type='LoadAnnotations', with_bbox=True), | |
| dict(type='Resize', img_scale=(1333, 800), 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']), | |
| ] | |
| test_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict( | |
| type='MultiScaleFlipAug', | |
| img_scale=(1333, 800), | |
| flip=False, | |
| transforms=[ | |
| dict(type='Resize', keep_ratio=True), | |
| dict(type='RandomFlip'), | |
| dict(type='Normalize', **img_norm_cfg), | |
| dict(type='Pad', size_divisor=32), | |
| dict(type='ImageToTensor', keys=['img']), | |
| dict(type='Collect', keys=['img']), | |
| ]) | |
| ] | |
| data = dict( | |
| train=dict(pipeline=train_pipeline), | |
| val=dict(pipeline=test_pipeline), | |
| test=dict(pipeline=test_pipeline)) | |