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Runtime error
| _base_ = './rtmdet-ins_l_8xb32-300e_coco.py' | |
| checkpoint = 'https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-s_imagenet_600e.pth' # noqa | |
| model = dict( | |
| backbone=dict( | |
| deepen_factor=0.33, | |
| widen_factor=0.5, | |
| init_cfg=dict( | |
| type='Pretrained', prefix='backbone.', checkpoint=checkpoint)), | |
| neck=dict(in_channels=[128, 256, 512], out_channels=128, num_csp_blocks=1), | |
| bbox_head=dict(in_channels=128, feat_channels=128)) | |
| train_pipeline = [ | |
| dict( | |
| type='LoadImageFromFile', | |
| file_client_args={{_base_.file_client_args}}), | |
| dict( | |
| type='LoadAnnotations', | |
| with_bbox=True, | |
| with_mask=True, | |
| poly2mask=False), | |
| dict(type='CachedMosaic', img_scale=(640, 640), pad_val=114.0), | |
| dict( | |
| type='RandomResize', | |
| scale=(1280, 1280), | |
| ratio_range=(0.5, 2.0), | |
| keep_ratio=True), | |
| dict( | |
| type='RandomCrop', | |
| crop_size=(640, 640), | |
| recompute_bbox=True, | |
| allow_negative_crop=True), | |
| dict(type='YOLOXHSVRandomAug'), | |
| dict(type='RandomFlip', prob=0.5), | |
| dict(type='Pad', size=(640, 640), pad_val=dict(img=(114, 114, 114))), | |
| dict( | |
| type='CachedMixUp', | |
| img_scale=(640, 640), | |
| ratio_range=(1.0, 1.0), | |
| max_cached_images=20, | |
| pad_val=(114, 114, 114)), | |
| dict(type='FilterAnnotations', min_gt_bbox_wh=(1, 1)), | |
| dict(type='PackDetInputs') | |
| ] | |
| train_pipeline_stage2 = [ | |
| dict( | |
| type='LoadImageFromFile', | |
| file_client_args={{_base_.file_client_args}}), | |
| dict( | |
| type='LoadAnnotations', | |
| with_bbox=True, | |
| with_mask=True, | |
| poly2mask=False), | |
| dict( | |
| type='RandomResize', | |
| scale=(640, 640), | |
| ratio_range=(0.5, 2.0), | |
| keep_ratio=True), | |
| dict( | |
| type='RandomCrop', | |
| crop_size=(640, 640), | |
| recompute_bbox=True, | |
| allow_negative_crop=True), | |
| dict(type='FilterAnnotations', min_gt_bbox_wh=(1, 1)), | |
| dict(type='YOLOXHSVRandomAug'), | |
| dict(type='RandomFlip', prob=0.5), | |
| dict(type='Pad', size=(640, 640), pad_val=dict(img=(114, 114, 114))), | |
| dict(type='PackDetInputs') | |
| ] | |
| train_dataloader = dict(dataset=dict(pipeline=train_pipeline)) | |
| custom_hooks = [ | |
| dict( | |
| type='EMAHook', | |
| ema_type='ExpMomentumEMA', | |
| momentum=0.0002, | |
| update_buffers=True, | |
| priority=49), | |
| dict( | |
| type='PipelineSwitchHook', | |
| switch_epoch=280, | |
| switch_pipeline=train_pipeline_stage2) | |
| ] | |