目标检测iou代码示例

IOU（交并比）是用于目标检测评估的常用度量。它表示两个区域的重叠部分占比。具体来说，它是两个区域的交集（重叠部分）除以两个区域的并集（总共的部分）。

IOU的计算公式如下:

IOU = Area of Intersection / Area of Union

IOU值越大，两个区域重叠度越大。通常来说，当IOU值大于0.5时，我们才认为两个区域是“相似”的。

下面是一个示例代码，用来计算两个矩形的IOU值：

def calculate_iou(box1, box2):
  # Calculate the x-y co-ordinates of the rectangles
  x1_left, y1_top, x1_right, y1_bottom = box1
  x2_left, y2_top, x2_right, y2_bottom = box2

  # Calculate the area of the rectangles
  rect1_area = (x1_right - x1_left) * (y1_bottom - y1_top)
  rect2_area = (x2_right - x2_left) * (y2_bottom - y2_top)

  # Find the overlapping area
  overlap_x1 = max(x1_left, x2_left)
  overlap_y1 = max(y1_top, y2_top)
  overlap_x2 = min(x1_right, x2_right)
  overlap_y2 = min(y1_bottom, y2_bottom)
  overlap_area = max(0, overlap_x2 - overlap_x1) * max(0, overlap_y2 - overlap_y1)

  # Calculate the IOU
  iou = overlap_area / (rect1_area + rect2_area - overlap_area)
  return iou

在上面的代码中，输入参数`box1`和`box2`是两个矩形的坐标。每个矩形都是由左上角和右下角的坐标表示的。坐标用4元组表示，分别是左上