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_base_ = 'mmdet::rtmdet/rtmdet_l_8xb32-300e_coco.py' |
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checkpoint = 'https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-s_imagenet_600e.pth' |
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model = dict( |
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backbone=dict( |
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deepen_factor=0.33, |
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widen_factor=0.5, |
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init_cfg=dict( |
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type='Pretrained', prefix='backbone.', checkpoint=checkpoint)), |
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neck=dict(in_channels=[128, 256, 512], out_channels=128, num_csp_blocks=1), |
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bbox_head=dict(in_channels=128, feat_channels=128, exp_on_reg=False)) |
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|
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train_pipeline = [ |
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dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}), |
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dict(type='LoadAnnotations', with_bbox=True), |
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dict(type='CachedMosaic', img_scale=(640, 640), pad_val=114.0), |
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dict( |
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type='RandomResize', |
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scale=(1280, 1280), |
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ratio_range=(0.5, 2.0), |
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keep_ratio=True), |
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dict(type='RandomCrop', crop_size=(640, 640)), |
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dict(type='YOLOXHSVRandomAug'), |
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dict(type='RandomFlip', prob=0.5), |
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dict(type='Pad', size=(640, 640), pad_val=dict(img=(114, 114, 114))), |
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dict( |
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type='CachedMixUp', |
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img_scale=(640, 640), |
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ratio_range=(1.0, 1.0), |
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max_cached_images=20, |
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pad_val=(114, 114, 114)), |
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dict(type='PackDetInputs') |
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] |
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|
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train_pipeline_stage2 = [ |
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dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}), |
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dict(type='LoadAnnotations', with_bbox=True), |
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dict( |
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type='RandomResize', |
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scale=(640, 640), |
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ratio_range=(0.5, 2.0), |
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keep_ratio=True), |
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dict(type='RandomCrop', crop_size=(640, 640)), |
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dict(type='YOLOXHSVRandomAug'), |
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dict(type='RandomFlip', prob=0.5), |
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dict(type='Pad', size=(640, 640), pad_val=dict(img=(114, 114, 114))), |
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dict(type='PackDetInputs') |
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] |
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|
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train_dataloader = dict(dataset=dict(pipeline=train_pipeline)) |
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|
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custom_hooks = [ |
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dict( |
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type='EMAHook', |
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ema_type='ExpMomentumEMA', |
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momentum=0.0002, |
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update_buffers=True, |
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priority=49), |
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dict( |
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type='PipelineSwitchHook', |
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switch_epoch=280, |
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switch_pipeline=train_pipeline_stage2) |
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] |
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