| _base_ = '../cascade_rcnn/cascade-rcnn_r50_fpn_1x_coco.py' | |
| model = dict( | |
| 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))), | |
| init_cfg=dict( | |
| type='Pretrained', checkpoint='open-mmlab://msra/hrnetv2_w32')), | |
| neck=dict( | |
| _delete_=True, | |
| type='HRFPN', | |
| in_channels=[32, 64, 128, 256], | |
| out_channels=256)) | |
| # learning policy | |
| max_epochs = 20 | |
| train_cfg = dict(max_epochs=max_epochs) | |
| 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, 19], | |
| gamma=0.1) | |
| ] | |