【Intel Realsense D435】16位深度图和RGB颜色图的视频显示、录制和保存（Python）-Toy模板网

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本文使用Intel Realsense D435深度相机，拍摄RGB颜色图及16位深度图。

同时实现了以深度图和RGB颜色图为图像帧的视频显示、录制与保存。

以下为总体程序：

'''
使用realsense相机录制视频
'''

#!/usr/bin/env python
# coding=utf-8
import time
import h5py         # 深度图格式所在库
import pyrealsense2 as rs
import numpy as np
import cv2
import os

class Camera(object):
    '''
    realsense相机处理类
    '''
    def __init__(self, width=1280, height=720, fps=30):   # 图片格式可根据程序需要进行更改

        self.width = width
        self.height = height
        self.pipeline = rs.pipeline()
        self.config = rs.config()
        self.config.enable_stream(rs.stream.color, self.width, self.height, rs.format.bgr8, fps)
        self.config.enable_stream(rs.stream.depth, self.width, self.height, rs.format.z16,  fps)
        # self.config.enable_stream(rs.stream.infrared, 1, self.width, self.height, rs.format.y8, fps)
        # self.config.enable_stream(rs.stream.infrared, 2, self.width, self.height, rs.format.y8, fps)
        self.pipeline.start(self.config)      # 获取图像视频流


    def get_frame(self):
        frames = self.pipeline.wait_for_frames()   # 获得frame (包括彩色，深度图)
        colorizer = rs.colorizer()                 # 创建伪彩色图对象
        depth_to_disparity = rs.disparity_transform(True)
        disparity_to_depth = rs.disparity_transform(False)

        # 创建对齐对象
        align_to = rs.stream.color                 # rs.align允许我们执行深度帧与其他帧的对齐
        align = rs.align(align_to)                 # “align_to”是我们计划对齐深度帧的流类型。
        aligned_frames = align.process(frames)
        # 获取对齐的帧
        aligned_depth_frame = aligned_frames.get_depth_frame()      # aligned_depth_frame是对齐的深度图
        color_frame   = aligned_frames.get_color_frame()
        # left_frame  = frames.get_infrared_frame(1)
        # right_frame = frames.get_infrared_frame(2)
        color_image     = np.asanyarray(color_frame.get_data())
        colorizer_depth = np.asanyarray(colorizer.colorize(aligned_depth_frame).get_data())
        depthx_image    = np.asanyarray(aligned_depth_frame.get_data())  # 原始深度图
        # left_frame   = np.asanyarray(left_frame.get_data())
        # right_frame  = np.asanyarray(right_frame.get_data())

        return color_image, depthx_image, colorizer_depth
        # left_frame, right_frame

    def release(self):
        self.pipeline.stop()


if __name__ == '__main__':

    # 视频保存路径
    os.mkdir(f'D://Realsense//Video//{int(time.time())}')
    video_path         = f'D://Realsense//Video//{int(time.time())}//targetvideo_rgb.mp4'
    video_depthc_path  = f'D://Realsense//Video//{int(time.time())}//targetvideo_depthcolor.mp4'
    video_depth16_path = f'D://Realsense//Video//{int(time.time())}//targetvideo_depth.h5'
    # video_left_path    = f'D://Realsense//Video//Stereo_left//{int(time.time())}_left.mp4'
    # video_right_path   = f'D://Realsense//Video//Stereo_right//{int(time.time())}_right.mp4'


    # 初始化参数
    fps, w, h = 30, 1280, 720
    # fps, w, h = 30, 640, 480
    mp4        = cv2.VideoWriter_fourcc(*'mp4v')   # 视频格式
             # 视频保存而建立对象
    # wr_left    = cv2.VideoWriter(video_left_path, mp4, fps, (w, h),      isColor=False)
    # wr_right   = cv2.VideoWriter(video_right_path, mp4, fps, (w, h),     isColor=False)


    # 完成相机初始化

    cam = Camera(w, h, fps)
    flag_V = 0
    idx = 0
    id  = 0
    print('录制视频请按: s, 保存视频或退出请按：q')


    while True:
            # 读取图像帧，包括RGB图和深度图
            color_image, depthxy_image, colorizer_depth = cam.get_frame()
            cv2.namedWindow('RealSense', cv2.WINDOW_AUTOSIZE)
            cv2.imshow('RealSense', color_image)
            key = cv2.waitKey(1)

            if key & 0xFF == ord('s') :
                flag_V = 1
                # 创建视频文件
                wr = cv2.VideoWriter(video_path, mp4, fps, (w, h), isColor=True)
                wr_colordepth = cv2.VideoWriter(video_depthc_path, mp4, fps, (w, h), isColor=True)
                wr_depth = h5py.File(video_depth16_path, 'w')
                print('...录制视频中...')
            if flag_V == 1:
                # 保存图像帧
                wr.write(color_image)                          # 保存RGB图像帧
                wr_colordepth.write(colorizer_depth)           # 保存相机自身着色深度图
                # wr_left.write(left_image)                      # 保存左帧深度图
                # wr_right.write(right_image)                    # 保存右帧深度图
                # res, depth16_image = cv2.imencode('.png', depthxy_image)  # 深度图解码方式一：点云小，但是出错
                depth16_image = cv2.imencode('.png', depthxy_image)[1]      # 深度图解码方式二：文件较大，测试稳定
                depth_map_name = str(id).zfill(5) + '_depth.png'
                # wr_depth[str(idx).zfill(5)] = depth16_image          #  储存方法：1 前3帧和没11帧出现高质量点云，其他错误
                wr_depth[depth_map_name] = depth16_image           #  储存方法：2 所有点云准确，但是点云质量不高
                idx += 1
                id = id + 1
            if key & 0xFF == ord('q') or key == 27:
                cv2.destroyAllWindows()
                print('...录制结束/直接退出...')
                break
    # 录制完毕，释放对象
    wr.release()
    wr_colordepth.release()
    # wr_left.release()
    # wr_right.release()
    wr_depth.close()
    cam.release()
    print(f'若保存视频，则视频保存在：{video_path}')

程序阅读如下：

1.库引用

import time         # 获取时间信息，用于创建不同文件名称的文件夹
import h5py         # 深度图格式所在库
import pyrealsense2 as rs # 相机集成库，用于相机初始化与相机视频流获取
import numpy as np  # 将图像帧转换为数据信息以进行图像保存
import cv2          # 视觉图像库，用于保存图像帧与视频
import os           # 系统操作库，用于系统路径寻觅与文件夹创建

2.相机初始化函数

class Camera(object):
    '''
    realsense相机处理类
    '''
    def __init__(self, width=1280, height=720, fps=30):   # 图片格式可根据程序需要进行更改

        self.width = width                #获取图像帧设置
        self.height = height
        self.pipeline = rs.pipeline()     #开放图像帧管道
        self.config = rs.config()         #配置初始化
        self.config.enable_stream(rs.stream.color, self.width, self.height, rs.format.bgr8, fps)
        self.config.enable_stream(rs.stream.depth, self.width, self.height, rs.format.z16,  fps)
        # self.config.enable_stream(rs.stream.infrared, 1, self.width, self.height, rs.format.y8, fps)
        # self.config.enable_stream(rs.stream.infrared, 2, self.width, self.height, rs.format.y8, fps)
        self.pipeline.start(self.config)      # 获取图像视频流

3.图像流获取函数

    def get_frame(self):
        frames = self.pipeline.wait_for_frames()   # 获得frame (包括彩色，深度图)
        colorizer = rs.colorizer()                 # 创建伪彩色图对象
        depth_to_disparity = rs.disparity_transform(True)
        disparity_to_depth = rs.disparity_transform(False)
        # 创建对齐对象
        align_to = rs.stream.color                 # rs.align允许我们执行深度帧与其他帧的对齐
        align = rs.align(align_to)                 # “align_to”是我们计划对齐深度帧的流类型。
        aligned_frames = align.process(frames)
        # 获取对齐的帧
        aligned_depth_frame = aligned_frames.get_depth_frame()      # aligned_depth_frame是对齐的深度图
        color_frame   = aligned_frames.get_color_frame()
        # left_frame  = frames.get_infrared_frame(1)
        # right_frame = frames.get_infrared_frame(2)
        
        color_image     = np.asanyarray(color_frame.get_data())     # 将图像帧转换为矩阵格式
        colorizer_depth = np.asanyarray(colorizer.colorize(aligned_depth_frame).get_data())
        depthx_image    = np.asanyarray(aligned_depth_frame.get_data())  
        # left_frame   = np.asanyarray(left_frame.get_data())
        # right_frame  = np.asanyarray(right_frame.get_data())

        return color_image, depthx_image, colorizer_depth           # 返回图像数据值
        # left_frame, right_frame

4.相机功能释放函数

    def release(self):
        self.pipeline.stop()            # 停止相机拍摄

5.主程序：文件路径需要根据本地情况进行修改，图片格式根据需求进行修改

if __name__ == '__main__':

    # 视频保存路径   路径需要根据本地情况进行修改
    os.mkdir(f'D://Realsense//Video//{int(time.time())}')
    video_path         = f'D://Realsense//Video//{int(time.time())}//targetvideo_rgb.mp4'
    video_depthc_path  = f'D://Realsense//Video//{int(time.time())}//targetvideo_depthcolor.mp4'
    video_depth16_path = f'D://Realsense//Video//{int(time.time())}//targetvideo_depth.h5'
    # video_left_path    = f'D://Realsense//Video//Stereo_left//{int(time.time())}_left.mp4'
    # video_right_path   = f'D://Realsense//Video//Stereo_right//{int(time.time())}_right.mp4'


    # 初始化参数
    fps, w, h = 30, 1280, 720
    # fps, w, h = 30, 640, 480
    mp4        = cv2.VideoWriter_fourcc(*'mp4v')   # 视频格式
    # 视频保存对象
    # wr_left    = cv2.VideoWriter(video_left_path, mp4, fps, (w, h),      isColor=False)
    # wr_right   = cv2.VideoWriter(video_right_path, mp4, fps, (w, h),     isColor=False)
    # 相机初始化
    cam = Camera(w, h, fps)
    flag_V = 0
    idx = 0
    id  = 0
    print('录制视频请按: s, 保存视频或退出请按：q')
    # 循环保存图像帧以建立视频
    while True:
            # 读取图像帧，包括RGB图和深度图
            color_image, depthxy_image, colorizer_depth = cam.get_frame()
            cv2.namedWindow('RealSense', cv2.WINDOW_AUTOSIZE)
            cv2.imshow('RealSense', color_image)
            key = cv2.waitKey(1)

            if key & 0xFF == ord('s') :
                flag_V = 1
                # 创建视频文件
                wr = cv2.VideoWriter(video_path, mp4, fps, (w, h), isColor=True)
                wr_colordepth = cv2.VideoWriter(video_depthc_path, mp4, fps, (w, h), isColor=True)
                wr_depth = h5py.File(video_depth16_path, 'w')
                print('...录制视频中...')
            if flag_V == 1:
                # 保存图像帧
                wr.write(color_image)                          # 保存RGB图像帧
                wr_colordepth.write(colorizer_depth)           # 保存相机自身着色深度图
                # wr_left.write(left_image)                      # 保存左帧深度图
                # wr_right.write(right_image)                    # 保存右帧深度图
                depth16_image = cv2.imencode('.png', depthxy_image)[1]      # 深度图解码
                depth_map_name = str(id).zfill(5) + '_depth.png'
                wr_depth[depth_map_name] = depth16_image                    # 所有点云准确
                id = id + 1
            if key & 0xFF == ord('q') or key == 27:
                cv2.destroyAllWindows()
                print('...录制结束/直接退出...')
                break

    # 录制完毕，释放视频对象
    wr.release()
    wr_colordepth.release()
    # wr_left.release()
    # wr_right.release()
    wr_depth.close()
    cam.release()
    print(f'若保存视频，则视频保存在：{video_path}')

图片拍摄结果：

RGB图

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