| 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')) | |
| ]]) | |
| ] | |