此代码基于官方代码基础上进行改写，主要是获取zed相机深度画面中心点的深度值，为yolo测距打基础。

1. 导入相关库

import pyzed.sl as sl
import math
import numpy as np
import sys
import math

2. 相机初始化设置

 zed = sl.Camera()
# 相机初始化设置init_params = sl.InitParameters()init_params.depth_mode = sl.DEPTH_MODE.ULTRA  # 使用高质量模式init_params.coordinate_units = sl.UNIT.MILLIMETER  # 单位设置为毫米

3. 获取中心点深度数据

if zed.grab(runtime_parameters) == sl.ERROR_CODE.SUCCESS:  # 相机成功获取图象zed.retrieve_image(image, sl.VIEW.LEFT)  # image：容器，sl.VIEW.LEFT：内容zed.retrieve_measure(depth, sl.MEASURE.DEPTH)   # 深度值zed.retrieve_measure(point_cloud, sl.MEASURE.XYZRGBA)  # 保留RGBA color的三维点云数据img = image.get_data()  # 转换成图像数组，便于后续的显示或者储存dep_map = dep.get_data()# 获取图像的像素坐标x = round(image.get_width() / 2)y = round(image.get_height() / 2)err, point_cloud_value = point_cloud.get_value(x, y)  # 将像素坐标转为三维坐标并存储

4. 计算中心点深度值

if math.isfinite(point_cloud_value[2]):      # 判断坐标不为空和无限大distance = math.sqrt(point_cloud_value[0] * point_cloud_value[0] +point_cloud_value[1] * point_cloud_value[1] +point_cloud_value[2] * point_cloud_value[2])   # 计算距离print(f"Distance to Camera at {{{x};{y}}}: {distance}")

5. 完整代码

import os
import cv2
import pyzed.sl as sl
import numpy as np
import mathdef main():# 创建相机对象zed = sl.Camera()# 相机初始化设置init_params = sl.InitParameters()init_params.camera_resolution = sl.RESOLUTION.HD1080  # Use HD1080 video modeinit_params.camera_fps = 30  # fps可选：15、30、60、100# 打开相机status = zed.open(init_params)if status != sl.ERROR_CODE.SUCCESS: #Ensure the camera has opened succesfullyprint("Camera Open : "+repr(status)+". Exit program.")exit()# Create and set RuntimeParameters after opening the cameraruntime_parameters = sl.RuntimeParameters()image = sl.Mat()   # 图像depth = sl.Mat()   # 深度值dep = sl.Mat()  # 深度图point_cloud = sl.Mat()   # 点云i = 0while True:if zed.grab(runtime_parameters) == sl.ERROR_CODE.SUCCESS:  # 相机成功获取图象zed.retrieve_image(image, sl.VIEW.LEFT)  # image：容器，sl.VIEW.LEFT：内容zed.retrieve_measure(depth, sl.MEASURE.DEPTH)   # 深度值zed.retrieve_image(dep, sl.VIEW.DEPTH)  # 深度图zed.retrieve_measure(point_cloud, sl.MEASURE.XYZRGBA)  # 保留RGBA color的三维点云数据img = image.get_data()  # 转换成图像数组，便于后续的显示或者储存dep_map = dep.get_data()# 获取图像的像素坐标x = round(image.get_width() / 2)y = round(image.get_height() / 2)err, point_cloud_value = point_cloud.get_value(x, y)  # 将像素坐标转为三维坐标并存储distance = math.sqrt(point_cloud_value[0] * point_cloud_value[0] +point_cloud_value[1] * point_cloud_value[1] +point_cloud_value[2] * point_cloud_value[2])   # 计算距离print(f"Distance to Camera at {{{x};{y}}}: {distance}")view = np.concatenate((cv2.resize(img,(640,360)),cv2.resize(dep_map,(640,360))),axis=1)  # 原图和深度图拼接cv2.imshow("View", view)key = cv2.waitKey(1)if key & 0xFF == 27:  # esc退出breakif key & 0xFF == ord('s'):  # 图像保存savePath = os.path.join("./images", "V{:0>3d}.png".format(i))  # 注意根目录是否存在"./images"文件夹cv2.imwrite(savePath, view)i = i + 1# 关闭相机zed.close()if __name__ == "__main__":main()

5. 实验效果

深度图和原图拼接

计算画面中心点深度值