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| _base_ = './yolox_s_fast_8xb8-300e_coco.py' | |
| # ========================modified parameters====================== | |
| deepen_factor = 0.33 | |
| widen_factor = 0.375 | |
| scaling_ratio_range = (0.5, 1.5) | |
| # =======================Unmodified in most cases================== | |
| img_scale = _base_.img_scale | |
| pre_transform = _base_.pre_transform | |
| test_img_scale = (416, 416) | |
| tta_img_scales = [test_img_scale, (320, 320), (640, 640)] | |
| # model settings | |
| model = dict( | |
| data_preprocessor=dict(batch_augments=[ | |
| dict( | |
| type='YOLOXBatchSyncRandomResize', | |
| random_size_range=(320, 640), | |
| size_divisor=32, | |
| interval=10) | |
| ]), | |
| backbone=dict(deepen_factor=deepen_factor, widen_factor=widen_factor), | |
| neck=dict(deepen_factor=deepen_factor, widen_factor=widen_factor), | |
| bbox_head=dict(head_module=dict(widen_factor=widen_factor))) | |
| train_pipeline_stage1 = [ | |
| *pre_transform, | |
| dict( | |
| type='Mosaic', | |
| img_scale=img_scale, | |
| pad_val=114.0, | |
| pre_transform=pre_transform), | |
| dict( | |
| type='mmdet.RandomAffine', | |
| scaling_ratio_range=scaling_ratio_range, # note | |
| # img_scale is (width, height) | |
| border=(-img_scale[0] // 2, -img_scale[1] // 2)), | |
| dict(type='mmdet.YOLOXHSVRandomAug'), | |
| dict(type='mmdet.RandomFlip', prob=0.5), | |
| dict( | |
| type='mmdet.FilterAnnotations', | |
| min_gt_bbox_wh=(1, 1), | |
| keep_empty=False), | |
| dict( | |
| type='mmdet.PackDetInputs', | |
| meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', 'flip', | |
| 'flip_direction')) | |
| ] | |
| test_pipeline = [ | |
| dict(type='LoadImageFromFile', backend_args=_base_.backend_args), | |
| dict(type='mmdet.Resize', scale=test_img_scale, keep_ratio=True), # note | |
| dict( | |
| type='mmdet.Pad', | |
| pad_to_square=True, | |
| pad_val=dict(img=(114.0, 114.0, 114.0))), | |
| dict(type='LoadAnnotations', with_bbox=True, _scope_='mmdet'), | |
| dict( | |
| type='mmdet.PackDetInputs', | |
| meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', | |
| 'scale_factor')) | |
| ] | |
| train_dataloader = dict(dataset=dict(pipeline=train_pipeline_stage1)) | |
| val_dataloader = dict(dataset=dict(pipeline=test_pipeline)) | |
| test_dataloader = val_dataloader | |
| # Config for Test Time Augmentation. (TTA) | |
| tta_pipeline = [ | |
| dict(type='LoadImageFromFile', backend_args=_base_.backend_args), | |
| dict( | |
| type='TestTimeAug', | |
| transforms=[ | |
| [ | |
| dict(type='mmdet.Resize', scale=s, keep_ratio=True) | |
| for s in tta_img_scales | |
| ], | |
| [ | |
| # ``RandomFlip`` must be placed before ``Pad``, otherwise | |
| # bounding box coordinates after flipping cannot be | |
| # recovered correctly. | |
| dict(type='mmdet.RandomFlip', prob=1.), | |
| dict(type='mmdet.RandomFlip', prob=0.) | |
| ], | |
| [ | |
| dict( | |
| type='mmdet.Pad', | |
| pad_to_square=True, | |
| pad_val=dict(img=(114.0, 114.0, 114.0))), | |
| ], | |
| [ | |
| dict( | |
| type='mmdet.PackDetInputs', | |
| meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', | |
| 'scale_factor', 'flip', 'flip_direction')) | |
| ] | |
| ]) | |
| ] | |