Jaccard index

def bb_intersection_over_union(boxA, boxB):
    # determine the (x, y)-coordinates of the intersection rectangle
    xA = max(boxA[0], boxB[0])
    yA = max(boxA[1], boxB[1])
    xB = min(boxA[2], boxB[2])
    yB = min(boxA[3], boxB[3])

    # compute the area of intersection rectangle
    interArea = max(0, xB - xA + 1) * max(0, yB - yA + 1)

    # compute the area of both the prediction and ground-truth
    # rectangles
    boxAArea = (boxA[2] - boxA[0] + 1) * (boxA[3] - boxA[1] + 1)
    boxBArea = (boxB[2] - boxB[0] + 1) * (boxB[3] - boxB[1] + 1)

    # compute the intersection over union by taking the intersection
    # area and dividing it by the sum of prediction + ground-truth
    # areas - the interesection area
    iou = interArea / float(boxAArea + boxBArea - interArea)

    # return the intersection over union value
    return iou

# -*- coding: utf-8 -*-

from typing import Tuple, Union

NumberType = Union[int, float]
RectType = Tuple[NumberType, NumberType, NumberType, NumberType]


def calculate_iou(rect1: RectType, rect2: RectType) -> float:
    lx1, ly1, lx2, ly2 = rect1
    rx1, ry1, rx2, ry2 = rect2

    # Calculate the coordinates of the intersection rectangle
    left = max(lx1, rx1)
    top = max(ly1, ry1)
    right = min(lx2, rx2)
    bottom = min(ly2, ry2)

    # If the rectangles do not intersect, return 0
    if right <= left or bottom <= top:
        return 0.0

    # Calculate the area of intersection
    intersection_area = (right - left) * (bottom - top)

    # Calculate the area of each rectangle
    area1 = (lx2 - lx1) * (ly2 - ly1)
    area2 = (rx2 - rx1) * (ry2 - ry1)

    # Calculate the union area
    union_area = area1 + area2 - intersection_area

    # Calculate IoU
    return intersection_area / union_area