双目摄像头获取深度视频python

双目摄像头获取深度视频的Python代码如下：

import cv2
import numpy as np

# 定义左右摄像头的索引
left_camera_index = 0
right_camera_index = 1

# 定义摄像头分辨率和帧率
camera_width = 640
camera_height = 480
camera_fps = 30

# 打开摄像头
left_camera = cv2.VideoCapture(left_camera_index)
left_camera.set(cv2.CAP_PROP_FRAME_WIDTH, camera_width)
left_camera.set(cv2.CAP_PROP_FRAME_HEIGHT, camera_height)
left_camera.set(cv2.CAP_PROP_FPS, camera_fps)

right_camera = cv2.VideoCapture(right_camera_index)
right_camera.set(cv2.CAP_PROP_FRAME_WIDTH, camera_width)
right_camera.set(cv2.CAP_PROP_FRAME_HEIGHT, camera_height)
right_camera.set(cv2.CAP_PROP_FPS, camera_fps)

# 定义StereoBM算法的参数
block_size = 15
num_disparities = 64
min_disparity = 0

# 创建StereoBM算法对象
stereo_bm = cv2.StereoBM_create(numDisparities=num_disparities, blockSize=block_size)

# 循环读取摄像头图像
while True:
    # 读取左右摄像头的图像
    _, left_image = left_camera.read()
    _, right_image = right_camera.read()

    # 将左右摄像头的图像转换为灰度图像
    left_gray = cv2.cvtColor(left_image, cv2.COLOR_BGR2GRAY)
    right_gray = cv2.cvtColor(right_image, cv2.COLOR_BGR2GRAY)

    # 计算左右摄像头的视差图
    disparity = stereo_bm.compute(left_gray, right_gray)

    # 将视差图进行归一化
    disparity_normalized = cv2.normalize(disparity, None, alpha=0, beta=255, norm_type=cv2.NORM_MINMAX, dtype=cv2.CV_8U)

    # 显示深度图像
    cv2.imshow("Disparity", disparity_normalized)

    # 按下q键退出循环
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# 释放摄像头资源
left_camera.release()
right_camera.release()

# 关闭窗口
cv2.destroyAllWindows()

以上代码使用了OpenCV库，在程序开始时，打开双目摄像头，设置摄像头的分辨率和帧率。然后创建StereoBM算法对象，并循环读取摄像头图像，将左右摄像头的图像转换为灰度图像，计算左右摄像头的视差图，将视差图进行归一化，最后显示深度图像。程序可以通过按下q键退出循环，释放摄像头资源并关闭窗口。