# TODO: Need to solve the problem of multiple backend_args parameters # _backend_args = dict( # backend='petrel', # path_mapping=dict({ # './data/': 's3://openmmlab/datasets/detection/', # 'data/': 's3://openmmlab/datasets/detection/' # })) _backend_args = None tta_model = dict( type='mmdet.DetTTAModel', tta_cfg=dict(nms=dict(type='nms', iou_threshold=0.65), max_per_img=300)) img_scales = [(640, 640), (320, 320), (960, 960)] # LoadImageFromFile # / | \ # (RatioResize,LetterResize) (RatioResize,LetterResize) (RatioResize,LetterResize) # noqa # / \ / \ / \ # RandomFlip RandomFlip RandomFlip RandomFlip RandomFlip RandomFlip # noqa # | | | | | | # LoadAnn LoadAnn LoadAnn LoadAnn LoadAnn LoadAnn # | | | | | | # PackDetIn PackDetIn PackDetIn PackDetIn PackDetIn PackDetIn # noqa _multiscale_resize_transforms = [ dict( type='Compose', transforms=[ dict(type='YOLOv5KeepRatioResize', scale=s), dict( type='LetterResize', scale=s, allow_scale_up=False, pad_val=dict(img=114)) ]) for s in img_scales ] tta_pipeline = [ dict(type='LoadImageFromFile', backend_args=_backend_args), dict( type='TestTimeAug', transforms=[ _multiscale_resize_transforms, [ dict(type='mmdet.RandomFlip', prob=1.), dict(type='mmdet.RandomFlip', prob=0.) ], [dict(type='mmdet.LoadAnnotations', with_bbox=True)], [ dict( type='mmdet.PackDetInputs', meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', 'scale_factor', 'pad_param', 'flip', 'flip_direction')) ] ]) ]