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tta_model = dict(
type='DetTTAModel',
tta_cfg=dict(nms=dict(type='nms', iou_threshold=0.5), max_per_img=100))
img_scales = [3,4,5,6]
tta_pipeline = [
dict(type='LoadHyperspectralImageFromFiles', to_float32 =True, normalized_basis=3000),
dict(
type='TestTimeAug',
transforms=[[
dict(type='HSIResize', scale_factor=s, keep_ratio=True) for s in img_scales
], [
dict(type='RandomFlip', prob=1.),
dict(type='RandomFlip', prob=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'))
]])
]
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