|
|
tta_model = dict( |
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|
type='DetTTAModel', |
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|
tta_cfg=dict(nms=dict(type='nms', iou_threshold=0.65), max_per_img=100)) |
|
|
|
|
|
img_scales = [(640, 640), (320, 320), (960, 960)] |
|
|
tta_pipeline = [ |
|
|
dict(type='LoadImageFromFile', backend_args=None), |
|
|
dict( |
|
|
type='TestTimeAug', |
|
|
transforms=[ |
|
|
[ |
|
|
dict(type='Resize', scale=s, keep_ratio=True) |
|
|
for s in img_scales |
|
|
], |
|
|
[ |
|
|
|
|
|
|
|
|
|
|
|
dict(type='RandomFlip', prob=1.), |
|
|
dict(type='RandomFlip', prob=0.) |
|
|
], |
|
|
[ |
|
|
dict( |
|
|
type='Pad', |
|
|
pad_to_square=True, |
|
|
pad_val=dict(img=(114.0, 114.0, 114.0))), |
|
|
], |
|
|
[dict(type='LoadAnnotations', with_bbox=True)], |
|
|
[ |
|
|
dict( |
|
|
type='PackDetInputs', |
|
|
meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', |
|
|
'scale_factor', 'flip', 'flip_direction')) |
|
|
] |
|
|
]) |
|
|
] |
|
|
|
