Target detection post-processing-finding points within the detection frame

Find fixed points within the prediction frame based on the prediction frame

import cv2


def draw_fixed_point(image, detection_box):
    # 计算目标检测框的中心点坐标
    x_center = (detection_box[0] + detection_box[2]) // 2
    y_center = (detection_box[1] + detection_box[3]) // 2

    # 计算固定距离框的边界坐标
    d = 2  # 固定距离框的距离
    fixed_box = [
        x_center - d,
        y_center - d,
        x_center + d,
        y_center + d
    ]

    # 绘制固定距离框的点
    cv2.circle(image, (x_center, y_center), 2, (0, 0, 255), -1)  # 绘制中心点
    cv2.rectangle(image, (fixed_box[0], fixed_box[1]), (fixed_box[2], fixed_box[3]), (0, 0, 255), 2)  # 绘制固定距离框

    return image


# 示例用法
image_path = 'image.jpg'  # 图像的文件路径
detection_box = [512, 512, 512, 512]  # 目标检测框的坐标 [x1, y1, x2, y2]

# 读取图像
image = cv2.imread(image_path)

# 在图像上绘制固定距离框的点
image_with_fixed_point = draw_fixed_point(image, detection_box)

# 显示结果图像
cv2.imshow('Image with Fixed Point', image_with_fixed_point)
cv2.waitKey(0)
cv2.destroyAllWindows()