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- tta_model = dict(
- type='DetTTAModel',
- tta_cfg=dict(nms=dict(type='nms', iou_threshold=0.6), 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
- ],
- [
- # ``RandomFlip`` must be placed before ``Pad``, otherwise
- # bounding box coordinates after flipping cannot be
- # recovered correctly.
- dict(type='RandomFlip', prob=1.),
- dict(type='RandomFlip', prob=0.)
- ],
- [
- dict(
- type='Pad',
- size=(960, 960),
- pad_val=dict(img=(114, 114, 114))),
- ],
- [
- dict(
- type='PackDetInputs',
- meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
- 'scale_factor', 'flip', 'flip_direction'))
- ]
- ])
- ]
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