postprocessing.py

"""
Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""

from typing import Tuple

import torch
from torch import Tensor

from nndet.core.boxes import batched_nms, nms
from nndet.inference.detection import batched_wbc


def batched_nms_model(
        boxes: Tensor,
        scores: Tensor,
        labels: Tensor,
        weights: Tensor,
        iou_thresh: float,
        *args, **kwargs,
        ) -> Tuple[Tensor, Tensor, Tensor, Tensor]:
    keep = batched_nms(boxes=boxes, scores=scores,
                       idxs=labels, iou_threshold=iou_thresh,
                       )
    return boxes[keep], scores[keep], labels[keep], weights[keep]


def batched_nms_ensemble(
        boxes: Tensor,
        scores: Tensor,
        labels: Tensor,
        weights: Tensor,
        iou_thresh: float,
        *args, **kwargs,
        ) -> Tuple[Tensor, Tensor, Tensor]:
    keep = batched_nms(boxes=boxes, scores=scores,
                       idxs=labels, iou_threshold=iou_thresh,
                       )
    return boxes[keep], scores[keep], labels[keep]


def batched_wbc_ensemble(
        boxes: Tensor,
        scores: Tensor,
        labels: Tensor,
        weights: Tensor,
        iou_thresh: float,
        n_exp_preds: Tensor,
        score_thresh: float,
        *args, **kwargs) -> Tuple[Tensor, Tensor, Tensor]:
    boxes, scores, labels = batched_wbc(
        boxes, scores, labels, weights=weights,
        n_exp_preds=n_exp_preds,
        iou_thresh=iou_thresh,
        score_thresh=score_thresh,
    )
    return boxes, scores, labels


def wbc_nms_no_label_ensemble(
        boxes: Tensor,
        scores: Tensor,
        labels: Tensor,
        weights: Tensor,
        iou_thresh: float,
        n_exp_preds: Tensor,
        score_thresh: float,
        *args, **kwargs) -> Tuple[Tensor, Tensor, Tensor]:
    boxes, scores, labels = batched_wbc(
        boxes, scores, labels, weights=weights,
        n_exp_preds=n_exp_preds,
        iou_thresh=iou_thresh,
        score_thresh=score_thresh,
    )
    keep = nms(boxes, scores, iou_thresh)
    return boxes[keep], scores[keep], labels[keep]