# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# 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
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# ==============================================================================
"""Operations for [N, 4] numpy arrays representing bounding boxes."""
import numpy as np
[docs]def area(boxes):
"""Computes area of boxes.
Args:
boxes (np.ndarray): A numpy array with shape [N, 4] holding N boxes.
Returns:
np.ndarray: A numpy array with shape [N*1] representing box areas.
"""
return (boxes[:, 2] - boxes[:, 0]) * (boxes[:, 3] - boxes[:, 1])
[docs]def intersection(boxes1, boxes2):
"""Compute pairwise intersection areas between boxes.
Args:
boxes1 (np.ndarray): A numpy array with shape [N, 4] holding N boxes.
boxes2 (np.ndarray): A numpy array with shape [M, 4] holding M boxes.
Returns:
np.ndarray: A numpy array with shape [N*M] representing pairwise
intersection area.
"""
[y_min1, x_min1, y_max1, x_max1] = np.split(boxes1, 4, axis=1)
[y_min2, x_min2, y_max2, x_max2] = np.split(boxes2, 4, axis=1)
all_pairs_min_ymax = np.minimum(y_max1, np.transpose(y_max2))
all_pairs_max_ymin = np.maximum(y_min1, np.transpose(y_min2))
intersect_heights = np.maximum(
np.zeros(all_pairs_max_ymin.shape),
all_pairs_min_ymax - all_pairs_max_ymin)
all_pairs_min_xmax = np.minimum(x_max1, np.transpose(x_max2))
all_pairs_max_xmin = np.maximum(x_min1, np.transpose(x_min2))
intersect_widths = np.maximum(
np.zeros(all_pairs_max_xmin.shape),
all_pairs_min_xmax - all_pairs_max_xmin)
return intersect_heights * intersect_widths
[docs]def iou(boxes1, boxes2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxes1 (np.ndarray): A numpy array with shape [N, 4] holding N boxes.
boxes2 (np.ndarray): A numpy array with shape [M, 4] holding M boxes.
Returns:
np.ndarray: A numpy array with shape [N, M] representing pairwise iou
scores.
"""
intersect = intersection(boxes1, boxes2)
area1 = area(boxes1)
area2 = area(boxes2)
union = np.expand_dims(
area1, axis=1) + np.expand_dims(
area2, axis=0) - intersect
return intersect / union
[docs]def ioa(boxes1, boxes2):
"""Computes pairwise intersection-over-area between box collections.
Intersection-over-area (ioa) between two boxes box1 and box2 is defined as
their intersection area over box2's area. Note that ioa is not symmetric,
that is, IOA(box1, box2) != IOA(box2, box1).
Args:
boxes1 (np.ndarray): A numpy array with shape [N, 4] holding N boxes.
boxes2 (np.ndarray): A numpy array with shape [M, 4] holding N boxes.
Returns:
np.ndarray: A numpy array with shape [N, M] representing pairwise ioa
scores.
"""
intersect = intersection(boxes1, boxes2)
areas = np.expand_dims(area(boxes2), axis=0)
return intersect / areas